DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 03/05/26 have been fully considered but they are not persuasive.
With respect to the 35 U.S.C. 101 rejection, the applicant argues:
PNG
media_image1.png
577
632
media_image1.png
Greyscale
This argument is not persuasive because the majority of limitations addressed under step 2A, prong one were made on the basis of reciting abstract mathematical concepts. The applicant’s arguments do not appear to have refuted the recitation of abstract mathematical concepts.
Also, just because an operation happens to be performed by a computer does not mean that it cannot also be performed by the human mind.
It should also be noted, in view of the applicant’s argument that “Such operations are inherently tied to computer-based processing,” that one of the key indicators that a limitation is not indicative of integration into a practical application under step 2A, prong two is implementing an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)).
Next, the applicant argues:
PNG
media_image2.png
783
641
media_image2.png
Greyscale
PNG
media_image3.png
707
651
media_image3.png
Greyscale
This argument is not persuasive because there is a distinction between an improvement in the judicial exception itself and an improvement in technology. Simply incorporating “better math” is not necessarily an improvement the functioning of a computer or to any other technology or technical field under MPEP 2106.05(a)).
In the current claims, data is being gathered and then processed using a mathematical data processing technique. However, the output of the data processing technique appears to simply sit on the computer, rather than being applied to a particular machine (see MPEP 2106.05(b)) or effecting a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05(c)).
In the latest response, the applicant has amended the claims to generically recite a transmitter and receiver. However, the claims do not disclose anything happening to the transmitter or receiver, as a result of the final noise floor level estimation value determination? Is something being changed with the transmitter and/or receiver? Is one being turned on or off? Is the relationship between the two changing? What is the net effect of the noise floor level estimation value being determined, beyond just sitting on the computer?
The examiner suggests that any transformation or reduction of a particular article to a different state or thing that is effected, be positively recited in the claims.
Next, the applicant makes a number of arguments, with respect to 35 U.S.C. 103.
Before addressing the arguments individually, the examiner notes that a key theme of the arguments is that the applicant is attempting to distinguish its invention from the CFAR method. However, it should be noted that CFAR is not mentioned in the claims, and the examiner’s basis of examination is broadest reasonable interpretation (BRI) and not necessarily living up to a narrow, unclaimed standard imposed by the applicant.
In a sense, the applicant’s arguments set up CFAR as a straw man and then attempt to knock that straw man down. However, while CFAR is disclosed by the art, broadest reasonable interpretation in this case is not necessarily the same as CFAR. The applicant’s attempts to establish CFAR as the base standard is considered by the examiner to read in an overly narrow interpretation to broad claims.
With respect to the applicant’s specific 103 arguments, the applicant argues:
PNG
media_image4.png
751
592
media_image4.png
Greyscale
PNG
media_image5.png
752
608
media_image5.png
Greyscale
PNG
media_image6.png
255
598
media_image6.png
Greyscale
This argument is not persuasive because as alluded to above, by grounding the argument in Kronauge’s CFAR teachings, and then distinguishing away from it, the applicant appears to read in a number of narrow, unclaimed elements.
For example, the applicant argues, “The claimed invention takes a different approach … the nonlinear mapping (e.g., a logarithm operation) is performed to make the data distribution more suitable for subsequent histogram-based analysis, thereby providing a more robust estimation that is less affected by strong target returns.”
Although dependent claim 12 does mention histograms, the independent claims do not. And none of the claims describe what makes the nonlinear mapping more suitable for histogram-based analysis. There also does not appear to be any mention in the claims about “target returns.”
Here, the applicant appears to read in narrow, unclaimed elements and then argue that the art does not teach these unclaimed elements. Whether that is true or not is moot. The examiner examines claimed elements under a standard of BRI.
With respect to the applicant’s first argument of “in Kronauge the noise floor estimation is performed by using the CFAR, and no nonlinear mapping is performed …” the examiner made an obviousness argument regarding Kronauge’s teaching of a logarithmic term, and that one of ordinary skill in the art would recognize that the disclosure of the square law detector and logarithmic term would imply a nonlinear transformation of data. The applicant does not appear to have addressed that particular argument.
With respect to the applicant’s second argument that, “in Kronauge the two-dimensional reference window, rather than the range gate is the basis to estimate the average noise floor …” the examiner notes that the concept of “average noise floor” does not appear to be in the independent claims, and the examiner could not find any claim that stated that the range gate was the “basis” for estimating the average noise floor. Claim 1 merely states, “for a range gate, performing the following acts …” and then listing multiple limitations. This is not the same thing as the range gate being a “basis” for estimating average noise floor. This is another example of where the applicant appears to read in an overly narrow interpretation to broad claims. If the intention is to directly link the range gate with the average noise floor, the examiner suggested directly claiming this in the independent claims in such a manner that the nexus between the range gate and average noise floor is explicit and detailed, rather than tangentially implied.
With respect to the applicant’s third argument that, “in Kronauge, the arithmetic mean of all random variables inside the two-dimensional reference window is used for estimating the noise floor … In contrast in distinguishing features of claim 1 of the present application, for a range gate, a nonlinear mapping is performed …” the examiner contends that the applicant is reading in a narrow interpretation and extra meaning to the broad phrase, “for a range gate.” The limitation of “performing a nonlinear mapping on a plurality of two-dimensional Fourier transform energy data, and then setting a number of preset intervals and ranges of the preset intervals according to the nonlinearly mapped data” does not mention “range gates.” If the applicant intends for there to be a more direct link between the range gates and the nonlinear mapping limitation, it is suggested that the direct nexus between the two be explicitly claimed.
With respect to the applicant’s fourth argument that, “the CFAR is the existing art of the present application, and the technology solution of the present application overcomes the defects of the CFAR, and they are different in essence …” the examiner again notes that the claims do not mention CFAR, and CFAR was not the standard that the examiner was interpreting the claims. The examiner gives broadest reasonable interpretation to the claims, and given the broadness of the claims, the examiner maintains that a reasonable rejection was made, even if the interpretation may not match the applicant’s interpretation.
With respect to Sakamoto, the applicant argues:
PNG
media_image7.png
128
574
media_image7.png
Greyscale
This argument is not persuasive because Sakamoto did not exist in a vacuum. It was specifically applied to teach the obviousness of LFMCW, in view of Kronauge’s teachings of FMCW. Whether or not it relates to features about determining the noise floor level estimation value of one range gate is moot, in view of why it was incorporated. Also, the applicant argues the concept of “per-range-gate statistical analysis.” However, this concept does not appear to be claimed. This is another example of the applicant reading in a narrow, unclaimed element to broad claims.
With respect to Dizaji, the applicant argues:
PNG
media_image8.png
347
604
media_image8.png
Greyscale
PNG
media_image9.png
174
603
media_image9.png
Greyscale
This argument is not persuasive because, similar to what was described above, the applicant argues that “Dizaji’s approach … is a variation of the CFAR technique.” Again, the applicant is basing the standard on CFAR, rather than BRI of what is claimed.
The applicant argues, “It provides no motivation to estimate a noise floor for an entire range gate based on the statistical distribution of its own data.” However, this concept of “an entire range gate based on the statistical distribution of its own data” does not appear to be claimed.
Again, the applicant appears to be reading in a narrow, unclaimed limitation to broad claims.
The applicant’s arguments with respect to claim 21 are not persuasive for similar reasons as those given above.
With respect to Bekooij, the applicant argues:
PNG
media_image10.png
285
590
media_image10.png
Greyscale
This argument is not persuasive because Bekooij specifically mentions FMCW and CFAR (paragraph 0003), which belong to the same field of endeavor as both the applicant’s invention and primary reference Kronauge. The examiner does not agree that Bekkooij is directed to a different technical field. Bekooij is serving as a secondary reference to Krogauge and specifically addresses techniques taught by Kronauge, such as CFAR.
With respect to the applicant’s argument that, it does not teach or suggest applying this technique to 2D FFT energy data along the Doppler dimension of a single range gate in an FMCW radar for the purpose of estimating a noise floor level to improve target direction in multi-target scenarios …” the examiner would contend that the claims also do not disclose this. The only claim that mentions histograms is the applicant’s claim 12, and that claim does not mention anything about “target direction” or “multi-target scenarios.” Here, again, the applicant appears to be reading in narrow, unclaimed interpretations to broad claims.
For the reasons discussed above, the rejection is maintained.
Information Disclosure Statement
The IDS of 03/13/26 has been considered.
Priority
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in China on 02/18/22. It is noted, however, that applicant has not filed a certified copy of the CN 202210153294.6 application as required by 37 CFR 1.55. The applicant did file a certified copy of the CN 202210162853.X application.
In the applicant’s 03/05/26 arguments, this issue does not appear to have been addressed.
Drawings
The specification and drawing amendments of 03/05/26 are accepted.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7-9, and 11-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
With respect to step 1 of the patent subject matter eligibility analysis, the claims are directed to a process, machine, manufacture, or composition of matter. Claims 1-5 are directed to a method, which is a process. Claims 7-9 and 21 are directed to a target detection method, which is a process. Claims 11-16 are directed to an apparatus, which is a machine. Claims 17-18 and 22 are directed to an electronic device, which is a machine. Claims 19-20 are directed to a non-transitory computer-readable storage medium, which is a manufacture. As such, claims 1-5, 7-9, and 11-22 are directed to a statutory category.
With respect to step 2A, prong one, the claims recite an abstract idea, law of nature, or natural phenomenon. Specifically, the following limitations recite mathematical concepts and/or mental processes.
Claim 1
A method for determining a noise floor level estimation value (The overall method for determining a noise floor level estimation value recites abstract mathematical concepts, for the reasons discussed below.)
acquiring a two-dimensional Fourier data plane, wherein the two-dimensional Fourier data plane comprises a range dimension and a Doppler dimension, and the range dimension comprises a plurality of range gates (This limitation recites abstract mathematical concepts in the form of mathematical relationships between data, a range dimension, a Doppler dimension, and range gates. Furthermore, Fourier transforms represent a specific mathematical calculation.)
for a range gate, performing the following acts:
acquiring a plurality of coordinate points of the range gate along the Doppler dimension and two-dimensional Fourier transform energy data corresponding to each coordinate point of the plurality of coordinate points of the range gate (This limitation recites abstract mathematical concepts in the form of mathematical relationships between data, a range dimension, a Doppler dimension, and range gates. Furthermore, Fourier transforms represent a specific mathematical calculation.)
performing a nonlinear mapping on a plurality of two-dimensional Fourier transform energy data, and then setting a number of preset intervals and ranges of the preset intervals according to the nonlinearly mapped data (This limitation recites abstract mathematical concepts. Performing a nonlinear mapping defines specific mathematical relationships. Furthermore, Fourier transforms represent a specific mathematical calculation.)
dividing the plurality of two-dimensional Fourier transform energy data into the preset intervals to obtain a number of two-dimensional Fourier transform energy data in each preset interval based on the nonlinear mapping (This limitation recites abstract mathematical concepts. Dividing the data into preset intervals to obtain data in each preset interval based on a nonlinear mapping is a mathematical calculation that defines specific mathematical relationships.)
determining an interval in which a number of two-dimensional Fourier transform energy data is the largest or an interval in which a median of the plurality of two-dimensional Fourier transform energy data is located, as a target preset interval (This limitation recites abstract mathematical concepts. The claimed intervals and numerical estimation of values, such as “largest” and “median,” define specific mathematical relationships. Furthermore, Fourier transforms represent a specific mathematical calculation. Furthermore, “determination,” in this context, is an observation, evaluation, judgment, and/or opinion that can be performed in the human mind. The limitation therefore also recites an abstract mental process.)
determining the noise floor level estimation value in the target preset interval (This limitation recites an abstract mental process. As stated, in paragraph 0107 of the applicant’s original specification, “As can be seen from FIG. 7, the energy value in the interval of which the occurrence frequencies are highest in the multiple power values of the range gate is about -13.8 dB, and the energy value in the interval, where the median of the multiple power values is located, is also about – 13.8 dB, so the noise floor level estimation value of the range gate may be -13.8 dB.” Here, it is apparent that the determination is a simple observation of looking at a chart or a graph, which is something that can be done in the human mind.)
Claim 11
acquiring a two-dimensional Fourier data plane, wherein the two-dimensional Fourier data plane comprises a range dimension and a Doppler dimension, and the range dimension comprises a plurality of range gates (This limitation recites abstract mathematical concepts in the form of mathematical relationships between data, a range dimension, a Doppler dimension, and range gates. Furthermore, Fourier transforms represent a specific mathematical calculation.)
for a range gate, acquiring a plurality of coordinate points of the range gate along the Doppler dimension and two-dimensional Fourier transform energy data corresponding to each coordinate point of the plurality of coordinate points of the range gate (This limitation recites abstract mathematical concepts in the form of mathematical relationships between data, a range dimension, a Doppler dimension, and range gates. Furthermore, Fourier transforms represent a specific mathematical calculation.)
performing a preprocessing on the acquired two-dimensional Fourier transform energy data to remove a part of the plurality of two-dimensional Fourier transform energy data (This limitation appears to be supported by paragraph 0056 of the applicant’s original specification, which states, “when a noise floor level estimation is performed for each target range gate respectively, the noise floor level estimation may be performed according to respective corresponding energy data based on part energy data (the noise floor level estimation of the embodiment of the present disclosure may be performed after the energy data corresponding to each selected range gate is preprocessed, for example, removing the partial energy maximum value and/or the minimum value, or based on a manner of such as presetting threshold values) or all energy data, in accordance with a manner of such as an average value, a median value, etc. …” The claimed removal appears to be a “subtraction” of certain data points from analysis consideration. This recites both a mathematical calculation and a mental process that can be performed in the human mind.)
and determining a noise floor level estimate value of the range gate according to remaining two-dimensional Fourier transform energy data (This limitation recites an abstract mental concept. As discussed with respect to claim 1 above, the claimed determination appears to be making a simple judgment based on a graph or chart, such as a histogram.)
Claim 21
A target detection method based on a noise floor level estimation value (The overall target detection method recites abstract mathematical concepts, for the reasons discussed below.)
acquiring noise floor level estimation values of a plurality of range gates in a two-dimensional Fourier data plane (This limitation recites abstract mathematical concepts in the form of mathematical relationships between data values and the dimensions of the two-dimensional Fourier data plane.)
for a range gate of the plurality of range gates, determining two-dimensional Fourier transform energy data larger than a noise floor level estimation value of the range gate as two-dimensional Fourier transform energy data corresponding to a target (This limitation defines abstract mathematical concepts in the form of mathematical relationships between the noise floor level estimation value and the Fourier transform energy data that is larger than it. Also, determining such data, such as by simple analysis of a chart or histogram, recites an abstract mental process that can be performed in the human mind.)
and determining a detection result of the target according to the two-dimensional Fourier transform energy data corresponding to the target (This limitation recites abstract mathematical concepts because a Fourier transform is a mathematical calculation, and determining a result based on a mathematical calculation forms a mathematical relationship. Also, a simple determination, in the form of an observation, evaluation, judgment, and/or opinion, is a mental process that can be performed in the human mind.)
wherein the determining the two-dimensional Fourier transform energy data larger than the noise floor level estimation value as the two-dimensional Fourier transform energy data corresponding to the target (As discussed above, this limitation recites abstract mathematical concepts and abstract mental processes.) comprises:
calculating a difference value between each two-dimensional Fourier transform energy data and the noise floor level estimation value (This limitation recites a mathematical calculation.)
determining two-dimensional Fourier transform energy data corresponding to a difference value larger than a preset threshold value as the two-dimensional Fourier transform energy data corresponding to the target (This limitation recites an abstract mathematical concept in the form of a mathematical relationship expressed through a difference value relative to a preset threshold. Comparing a value to a threshold and making a simple determination as a result is also an abstract mental process that can be performed in the human mind.)
Claims 2-5, 7-9, and 17-20 depend on independent claim 1 and also recite its abstract limitations by virtue of their dependence. Claims 12-16 depend on independent claim 11 and also recite its abstract limitations by virtue of their dependence. Claim 22 depends on independent claim 21 and also recites its abstract limitations by virtue of its dependence. In addition, some of these limitations also recite their own abstract mathematical concepts and/or mental processes.
Claim 2 is further directed to performing nonlinear mapping on the plurality of two-dimensional Fourier transform energy data. It recites abstract mathematical concepts for similar reasons as described above.
Claim 3 discloses removing parts of energy data. This recites abstract mathematical concepts in the form of subtraction. It also recites an abstract mental process of disregarding certain data when performing analysis.
Claim 4 discloses that preset intervals are non-uniformly distributed. This recites mathematical relationships.
Claim 5 is further directed to various mathematical relationships and calculations, such as taking an average value or a median of values.
Claim 7 is further directed to mathematical relationships between data values and the dimensions of the Fourier data plane.
Claim 8 is further directed to mathematical relationships between values
Claim 9 recites specific mathematical calculations and relationships, such as calculating a difference value and determining data based on difference values larger than a preset threshold value.
Claim 12 discloses performing a statistic by using a histogram, which shows mathematical relationships.
Claim 13 discloses dividing data into intervals, which recites mathematical relationships. Dividing can also be construed as a mathematical calculation.
Claim 14 discloses intervals being non-uniformly distributed, which recites mathematical relationships between the intervals.
Claim 15 discloses various mathematical relationships and calculations, such as taking an average value or median.
With respect to step 2A, prong two, the claims do not recite additional elements that integrate the judicial exception into a practical application. The following limitations are considered “additional elements” and explanation will be given as to why these “additional elements” do not integrate the judicial exception into a practical application.
Claim 1
applied to a frequency modulation continuous wave radar comprising a transmitter and a receiver (This limitation is not indicative of integration into a practical application because it merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). The inclusion of a generic transmitter and receiver to a frequency modulation continuous wave radar merely serves to illustrate a conventional method of gathering data. It is not considered to be a core part of the “solution” presented by the claims as a whole.)
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW) received by the receiver, the received LFMCW is an echo signal, reflected from a target, of a LMFCW transmitted by the transmitter (This limitation is not indicative of integration into a practical application because it merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). In this case, the inclusion of the structural elements of a receiver and transmitter (with echo signal) merely serve as generic structural elements that describe how a conventional LFMCW system works, rather than distinguishing themselves as a core part of the “solution” presented by the claims. Their purpose in this claim is merely to give technological context to the data collection mechanism, which is merely adding insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). The claims, as a whole, are directed to data processing about LFMCW data and not a structural use with LFMCW technology.)
Claim 11
An apparatus for determining a noise floor level estimation value, comprising a processor, wherein the processor is configured to execute computer-executable instructions to perform the following acts (This limitation is not indicative of integration into a practical application because it merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)).)
a frequency modulation continuous wave radar comprising a transmitter and a receiver (This limitation is not indicative of integration into a practical application because it merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). The inclusion of a generic transmitter and receiver to a frequency modulation continuous wave radar merely serves to illustrate a conventional method of gathering data. It is not considered to be a core part of the “solution” presented by the claims as a whole.)
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW) received by the receiver, wherein the received LFMCW is an echo signal, reflected from a target, of a LMFCW transmitted by the transmitter (This limitation is not indicative of integration into a practical application because it merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). In this case, the inclusion of the structural elements of a receiver and transmitter (with echo signal) merely serve as generic structural elements that describe how a conventional LFMCW system works, rather than distinguishing themselves as a core part of the “solution” presented by the claims. Their purpose in this claim is merely to give technological context to the data collection mechanism, which is merely adding insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). The claims, as a whole, are directed to data processing about LFMCW data and not a structural use with LFMCW technology.)
Claim 21
applied to a frequency modulation continuous wave radar comprising a transmitter and a receiver (This limitation is not indicative of integration into a practical application because it merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). The inclusion of a generic transmitter and receiver to a frequency modulation continuous wave radar merely serves to illustrate a conventional method of gathering data. It is not considered to be a core part of the “solution” presented by the claims as a whole.)
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW) received by the receiver, wherein the received LFMCW is an echo signal, reflected from a target, of a LMFCW transmitted by the transmitter (This limitation is not indicative of integration into a practical application because it merely serves to generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). In this case, the inclusion of the structural elements of a receiver and transmitter (with echo signal) merely serve as generic structural elements that describe how a conventional LFMCW system works, rather than distinguishing themselves as a core part of the “solution” presented by the claims. Their purpose in this claim is merely to give technological context to the data collection mechanism, which is merely adding insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)). The claims, as a whole, are directed to data processing about LFMCW data and not a structural use with LFMCW technology.)
Claims 2-5, 7-9, and 17-20 depend on independent claim 1 and also recite its limitations that are not indicative of integration into a practical application, by virtue of their dependence. Claims 12-16 depend on independent claim 11 and also recite its limitations that are not indicative of integration into a practical application, by virtue of their dependence. Claim 22 depends on independent claim 21 and also recites its limitations that are not indicative of integration into a practical application, by virtue of its dependence. In addition, some of these limitations also recite their own limitations that are not indicative of integration into a practical application.
Claim 16 discloses a processor that outputs data values. This is not indicative of integration into a practical application because it merely uses a computer as a tool to perform an abstract idea.
Claims 17-20 disclose a generic electronic device and/or generic computer processing components. These limitations are not indicative of integration into a practical application because they 1) merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); 2) add insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)); and/or 3) generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).
With respect to step 2B, the claims do not recite additional elements that amount to significantly more than the judicial exception. The claimed invention does not add significantly more because, as discussed above in step 2A, prong two, the claims do nothing more than merely use a computer as a tool to perform an abstract idea; add insignificant extra-solution activity to the judicial exception; and/or generally link the use of the judicial exception to a particular technological environment or field of use. The claims are directed to receiving and processing data. This is well-understood, routine, and conventional. Simply appending well-understood, routine, and conventional activities previously known to the industry, and specified at a high level of generality, to the judicial exception is not indicative of an inventive concept (aka “significantly more”) (see MPEP 2106.05(d) and Berkheimer Memo).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-5, 7-9, 11-12, and 16-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kronauge et al NPL (Kronauge, Matthias and Rohling, Hermann - “Fast Two-Dimensional CFAR Procedure”; IEEE Transactions on Aerospace and Electronic Systems; Vol. 49, No. 3 July 2013) in view of Sakamoto (US PgPub 20080231496) and Dizaji et al (US PgPub 20030174088).
With respect to claim 1, Kronauge et al NPL discloses:
A method for determining a noise floor level estimation value, applied to a frequency modulation continuous wave radar comprising a transmitter and a receiver (Figure 2 discloses “Noise Estimation.” Page 1818 column 2, paragraph 2 states, “This paper proposes a CFAR procedure with a small but two-dimensional sliding reference window to identify the average noise floor inside a local environment of the RDM … This two-dimensional reference window is the basis for a high quality procedure to estimate the average noise floor for the specific test cell.” The abstract discloses, “An FMCW radar system, which transmits a sequence of rapid chirp signals … applied to the received echo signal …” (emphasis mine).)
acquiring a two-dimensional Fourier data plane corresponding to a Frequency Modulation Continuous Wave (FMCW) received by the receiver, wherein the received FMCW is an echo signal, reflected from a target, of a FMCW transmitted by the transmitter (abstract), and the two-dimensional Fourier data plane comprises a range dimension and a Doppler dimension, and the range dimension comprises a plurality of range gates (figure 1; abstract states, “An FMCW radar system, which transmits a sequence of rapid chirp signals, is considered to measure target range and radial velocity simultaneously even in multitarget situations. The main outcome of the coherent processing procedure applied to the received echo signal is the two-dimensional range-Doppler-matrix (RDM), which is the basis for an adaptive constant false alarm rate (CFAR) target detection technique.”; page 1818; column 1, paragraph 1 states, “Therefore the first FFT is applied to each chirp signal. The FFT splits the radar echo signal into different range gates.”)
for a range gate (page 1818, column 1, paragraph 1), performing the following acts:
acquiring a plurality of coordinate points of the range gate along the Doppler dimension and two-dimensional Fourier transform energy data corresponding to each coordinate point of the plurality of coordinate points of the range gate (figure 1; page 1818, column 1, paragraphs 1-4)
With respect to claim 1, Kronauge et al NPL differs from the claimed invention in that it does not explicitly disclose:
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW)
performing a nonlinear mapping on a plurality of two-dimensional Fourier transform energy data, and then setting a number of preset intervals and ranges of the preset intervals according to the nonlinearly mapped data
dividing the plurality of two-dimensional Fourier transform energy data into the preset intervals to obtain a number of two-dimensional Fourier transform energy data in each preset interval based on the nonlinear mapping
determining an interval in which a number of two-dimensional Fourier transform energy data is the largest or an interval in which a median of the plurality of two-dimensional Fourier transform energy data is located, as a target preset interval: and
determining the noise floor level estimation value in the target preset interval
With respect to claim 1, the following limitations are obvious in view of the total teachings of Kronauge et al NPL:
performing a nonlinear mapping on a plurality of two-dimensional Fourier transform energy data, and then setting a number of preset intervals and ranges of the preset intervals according to the nonlinearly mapped data (Although Kronauge et al NPL does not explicitly use the term “nonlinear mapping,” it does state, “A square law detector is assumed and the received signal magnitude squared values inside the RDM are considered as random variables … In a square law detector this random variable Y0 is exponentially distributed with the following probability density function …” (page 1818, column 2, paragraphs 3-4). Equation 6 explicitly show a logarithmic term e-y/µ. One of ordinary skill in the art would recognize that the disclosure of the square law detector and logarithmic term would imply a nonlinear transformation of data. As stated in paragraph 0071 of the applicant’s original specification, “a nonlinear mapping may be performed on the multiple two-dimensional Fourier transform energy data, for example, a logarithm operation …”)
dividing the plurality of two-dimensional Fourier transform energy data into the preset intervals to obtain a number of two-dimensional Fourier transform energy data in each preset interval based on the nonlinear mapping (obvious in view of applying the nonlinear transformation processing to the two-dimensional Fourier transform energy data for the range-Doppler-matrix (RDM))
With respect to claim 1, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the total teachings of Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of converting complex signal information into information that can be more relevant for purposes, such as CFAR detection.
With respect to claim 1, Sakamoto discloses:
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW) (Kronauge et al NPL discloses frequency modulation continuous wave (FMCW), but it does not explicitly disclose linear frequency modulation continuous wave (LFMCW). Sakamoto paragraph 0009 states, “the FMCW radar transmits a radar wave via a directional antenna unit. The frequency of the radar wave is modulated so as to linearly vary in time.” One of ordinary skill in the art recognizes that LFMCW is a subset of FMCW that is common for accurate measurements in radar systems.)
With respect to claim 1, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Sakamoto into the invention of Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of accurate measurements in radar systems.
With respect to claim 1, Dizaji et al discloses:
determining an interval in which a number of two-dimensional Fourier transform energy data is the largest or an interval in which a median of the plurality of two-dimensional Fourier transform energy data is located, as a target preset interval (Dizaji et al abstract states, “The detection module calculates an estimated target amplitude and an estimated noise floor amplitude based on the range-doppler data … The detection module detects a target when the difference between the estimated target amplitude and the estimated noise floor amplitude is larger than the threshold value.” Paragraph 0009 of Dizaji et al states, “To determine a target’s range, azimuth and velocity, a detector processes the generated range, azimuth and doppler information for a give CIT. In general, the detector looks for peaks at a given cell (i.e. a data value or pixel) in a two dimensional plot known as a range-doppler plot. Target detection usually comprises comparing the amplitude in a given cell …” The claimed limitation is obvious in view of the combination of Dizaji et al and Kronauge et al NPL. Kronauge et al NPL discloses range gates and intervals. Dizaji et al discloses identifying amplitude data, which represents when energy data is “largest”.)
determining the noise floor level estimation value in the target preset interval (obvious in view of combination. Both Kronauge et al NPL and Dizaji et al disclose noise floor level estimation, as discussed above.)
With respect to claim 1, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Dizaji et al into the invention of Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of identifying amplitude information in the data and performing analysis based on the amplitude information.
With respect to claim 2, Kronauge et al NPL, as modified, discloses:
wherein the performing the nonlinear mapping on the plurality oftwo-dimensional Fourier transform energy data, comprises: performing the nonlinear mapping on remaining two-dimensional Fourier transform energy data after performing a preprocessing on the plurality of two-dimensional Fourier transform energy data to remove a part of the plurality of two-dimensional Fourier transform energy data (obvious in view of combination; The claimed preprocessing appears to be a filtering operation. Dizaji et al discloses filtering of data throughout its disclosure, such as in paragraphs 0005-0006, 0008-0009, and 0054. Filtering certain parts of data, in order to aid in the analysis of other data would be obvious to one of ordinary skill in the art. As stated in para 0054 of Dizaji et al, “As is known to those skilled in the art, the radar data in each range-doppler plot 16 has been subjected to conventional signal processing operations for pre-processing which includes bandpass filtering …”)
With respect to claim 3, Kronauge et al NPL, as modified, discloses:
wherein the preprocessing comprises: removing the part of the plurality of two-dimensional Fourier transform energy data with an energy maximum value or an energy minimum value; or removing the part of the plurality of two-dimensional Fourier transform energy data based on a preset threshold value (obvious in view of filtering and threshold difference between amplitude/noise floor teachings of Dizaji et al)
With respect to claim 4, Kronauge et al NPL, as modified, discloses:
wherein the plurality of preset intervals are non-uniformly distributed (obvious in view of exponential distribution teachings of Kronauge et al NPL on page 1818, column 2, paragraph 4)
With respect to claim 5, Kronauge et al NPL, as modified, discloses:
wherein the determining the noise floor level estimation value in the target preset interval comprises any one of the following: taking any two-dimensional Fourier transform energy data in the target preset interval as the noise floor level estimation value; taking an average value of all two-dimensional Fourier transform energy data in the target preset interval as the noise floor level estimation value; and taking a median of all two-dimensional Fourier transform energy data in the target preset interval as the noise floor level estimation value (Kronauge et al NPL page 1818, column 2, paragraph 2 states, “This paper proposes a CFAR procedure with a small but two-dimensional sliding reference window to identify the average noise floor …”)
With respect to claim 7, Kronauge et al NPL, as modified, discloses:
A target detection method based on a noise floor level estimation value, wherein the noise floor level estimation value is determined adopting the method of claim 1 (as discussed in claim 1 above)
the target detection method comprising: acquiring noise floor level estimation values of a plurality of range gates in a two-dimensional Fourier data plane corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW) (obvious for reasons discussed above)
for a range gate of the plurality of range gates, determining two-dimensional Fourier transform energy data larger than a noise floor level estimation value of the range gate as two-dimensional Fourier transform energy data corresponding to a target (obvious for reasons discussed above)
determining a detection result of the target according to the two-dimensional Fourier transform energy data corresponding to the target (obvious for reasons discussed above)
With respect to claim 8, Kronauge et al NPL, as modified, discloses:
wherein the determining the detection result of the target according to the two-dimensional Fourier transform energy data corresponding to the target comprises: determining a range gate corresponding to the two-dimensional Fourier transform energy data corresponding to the target as a range of the target, and determining a Doppler gate corresponding to the two-dimensional Fourier transform energy data corresponding to the target as a speed of the target (obvious in view of combination; para 0057 of Sakamoto states, “The FMCW radar detects the distance to a target object located in a measuring range and/or a relative speed of the target object …” See further “speed” teachings of Sakamoto.)
With respect to claim 9, Kronauge et al NPL, as modified, discloses:
wherein the determining the two-dimensional Fourier transform energy data larger than the noise floor level estimation value as the two-dimensional Fourier transform energy data corresponding to the target (obvious for reasons discussed above) comprises:
calculating a difference value between each two-dimensional Fourier transform energy data and the noise floor level estimation value (obvious in view of combination; see amplitude/noise floor threshold difference teachings of Dizaji et al.)
determining two-dimensional Fourier transform energy data corresponding to a difference value larger than a preset threshold value as the two-dimensional Fourier transform energy data corresponding to the target (obvious in view of combination; see amplitude/noise floor threshold difference teachings of Dizaji et al.)
With respect to claim 17, Kronauge et al NPL, as modified, discloses:
An electronic device, comprising: a processor, and a memory communicatively connected to the processor; wherein the memory stores computer-executable instructions; and the processor executes the computer-executable instructions stored in the memory to implement the method of claim 1 (This limitation is directed to generic computer operations. Such operations are obvious to the teachings of modified Kronauge et al NPL. Page 1817, column 1, paragraph 2 discloses, “CFAR is very robust in multitarget situations but requires a high computation power.” This implies a computer. As discussed above, Kronauge et al NPL also discloses a CFAR processor. Sakamoto paragraph 0063 discloses a CPU, ROM, and RAM. Dizaji et al para 0057 discloses memory and computer readable medium, and computer platform.)
With respect to claim 18, Kronauge et al NPL, as modified, discloses:
An electronic device, comprising: a processor, and a memory communicatively connected to the processor; wherein the memory stores computer-executable instructions; and the processor executes the computer-executable instructions stored in the memory to implement the method of claim 7 (This limitation is directed to generic computer operations. Such operations are obvious to the teachings of modified Kronauge et al NPL. Page 1817, column 1, paragraph 2 discloses, “CFAR is very robust in multitarget situations but requires a high computation power.” This implies a computer. As discussed above, Kronauge et al NPL also discloses a CFAR processor. Sakamoto paragraph 0063 discloses a CPU, ROM, and RAM. Dizaji et al para 0057 discloses memory and computer readable medium, and computer platform.)
With respect to claim 19, Kronauge et al NPL, as modified, discloses:
A non-transitory computer-readable storage medium having computer-executable instructions stored thereon, wherein when the computer-executable instructions are executed by a processor, the method of claim 1 is implemented (This limitation is directed to generic computer operations. Such operations are obvious to the teachings of modified Kronauge et al NPL. Page 1817, column 1, paragraph 2 discloses, “CFAR is very robust in multitarget situations but requires a high computation power.” This implies a computer. As discussed above, Kronauge et al NPL also discloses a CFAR processor. Sakamoto paragraph 0063 discloses a CPU, ROM, and RAM. Dizaji et al para 0057 discloses memory and computer readable medium, and computer platform.)
With respect to claim 20, Kronauge et al NPL, as modified, discloses:
A non-transitory computer-readable storage medium having computer-executable instructions stored thereon, wherein when the computer-executable instructions are executed by a processor, the method of claim 7 is implemented (This limitation is directed to generic computer operations. Such operations are obvious to the teachings of modified Kronauge et al NPL. Page 1817, column 1, paragraph 2 discloses, “CFAR is very robust in multitarget situations but requires a high computation power.” This implies a computer. As discussed above, Kronauge et al NPL also discloses a CFAR processor. Sakamoto paragraph 0063 discloses a CPU, ROM, and RAM. Dizaji et al para 0057 discloses memory and computer readable medium, and computer platform.)
With respect to claim 11, Kronauge et al NPL discloses:
An apparatus for determining a noise floor level estimation value (Figure 2 discloses “Noise Estimation.” Page 1818 column 2, paragraph 2 states, “This paper proposes a CFAR procedure with a small but two-dimensional sliding reference window to identify the average noise floor inside a local environment of the RDM … This two-dimensional reference window is the basis for a high quality procedure to estimate the average noise floor for the specific test cell.”), comprising a frequency modulation continuous wave radar comprising a transmitter and a receiver (abstract) and a processor, wherein the processor is configured to execute computer-executable instructions to perform the following acts (Page 1818, column 2, paragraph 2 states, “Therefore the CFAR processor should be able to adapt …”; Page 1821, column 1, paragraph 1 states, “The computation complexity of the described OSCA CFAR technique is already quite low, however certain system designs may require even faster CFAR processors.”):
acquiring a two-dimensional Fourier data plane corresponding to a Frequency Modulation Continuous Wave (FMCW) received by the receiver, wherein the received FMCW is an echo signal, reflected from a target, of a FMCW transmitted by the transmitter, and the two-dimensional Fourier data plane comprises a range dimension and a Doppler dimension, and the range dimension comprises a plurality of range gates (figure 1; abstract states, “An FMCW radar system, which transmits a sequence of rapid chirp signals, is considered to measure target range and radial velocity simultaneously even in multitarget situations. The main outcome of the coherent processing procedure applied to the received echo signal is the two-dimensional range-Doppler-matrix (RDM), which is the basis for an adaptive constant false alarm rate (CFAR) target detection technique.”; page 1818; column 1, paragraph 1 states, “Therefore the first FFT is applied to each chirp signal. The FFT splits the radar echo signal into different range gates.”)
for a range gate, acquiring a plurality of coordinate points of the range gate along the Doppler dimension and two-dimensional Fourier transform energy data corresponding to each coordinate point of the plurality of coordinate points of the range gate (figure 1; page 1818, column 1, paragraphs 1-4)
With respect to claim 11, Kronauge et al NPL differs from the claimed invention in that it does not explicitly disclose:
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW)
performing a preprocessing on the acquired two-dimensional Fourier transform energy data to remove a part of the plurality of two-dimensional Fourier transform energy data
and determining a noise floor level estimate value of the range gate according to remaining two-dimensional Fourier transform energy data
With respect to claim 11, Sakamoto discloses:
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW) (Kronauge et al NPL discloses frequency modulation continuous wave (FMCW), but it does not explicitly disclose linear frequency modulation continuous wave (LFMCW). Sakamoto paragraph 0009 states, “the FMCW radar transmits a radar wave via a directional antenna unit. The frequency of the radar wave is modulated so as to linearly vary in time.” One of ordinary skill in the art recognizes that LFMCW is a subset of FMCW that is common for accurate measurements in radar systems.)
With respect to claim 11, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Sakamoto into the invention of Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of accurate measurements in radar systems.
With respect to claim 11, Dizaji et al discloses:
performing a preprocessing on the acquired two-dimensional Fourier transform energy data to remove a part of the plurality of two-dimensional Fourier transform energy data (The claimed preprocessing appears to be a filtering operation. Dizaji et al discloses filtering of data throughout its disclosure, such as in paragraphs 0005-0006, 0008-0009, and 0054. Filtering certain parts of data, in order to aid in the analysis of other data would be obvious to one of ordinary skill in the art. As stated in para 0054 of Dizaji et al, “As is known to those skilled in the art, the radar data in each range-doppler plot 16 has been subjected to conventional signal processing operations for pre-processing which includes bandpass filtering …”)
and determining a noise floor level estimate value of the range gate according to remaining two-dimensional Fourier transform energy data (obvious in view of combination; Both Kronauge et al NPL and Dizaji disclose determining a noise floor level estimate value, as discussed above.
With respect to claim 11, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Dizaji et al into the invention of Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of filtering out unneeded data, in order to enhance analysis of important data.
With respect to claim 12, Kronauge et al NPL, as modified, discloses:
wherein the processor is configured to perform a statistic on the remaining two-dimensional Fourier transform energy data by using a histogram, and determine the noise floor level estimation value according to a statistical result of the histogram (obvious in view of combination; Sakamoto abstract states, “The method includes steps of: calculating a histogram of intensities …” See further Sakamoto histogram teachings in paragraphs 0022, 0024, 0026, 0028, 0030, 0095, and 0101-0106. Dizaji et al discloses histograms in paragraphs 0036-0039, 0059-0062. Para 0059 states, “The analysis comprised constructing histograms based on the amplitude values (in dB) from all of the range-doppler-azimuth data …”)
With respect to claim 16, Kronauge et al NPL, as modified, discloses:
wherein the processor is further configured to output noise floor level estimation values of all range gates in the two-dimensional Fourier data plane (obvious in view of combination; Kronauge et al NPL discloses many equations. It would be obvious to one of ordinary skill in the art to “output” the results of the various calculations performed by modified Kronauge et al, in order to arrive at the noise floor level estimation values.)
With respect to claim 21, Kronauge et al NPL discloses:
A target detection method based on a noise floor level estimation value, applied to a frequency modulation continuous wave radar comprising a transmitter and a receiver (abstract states, “An FMCW radar system, which transmits a sequence of rapid chirp signals, is considered to measure target range … applied to the received echo signal …”; Figure 1 is directed to “Radar target detection based on RDM.”; Figure 2 is directed to “Signal processing procedure for target detection.”; page 1818, column 1, last paragraph states, “The task of an adaptive target detection scheme …”)
acquiring noise floor level estimation values of a plurality of range gates in a two-dimensional Fourier data plane corresponding to a Frequency Modulation Continuous Wave (FMCW) received by the receiver, wherein the received FMCW is an echo signal, reflected from a target, of a FMCW transmitted by the transmitter (figure 1; abstract states, “An FMCW radar system, which transmits a sequence of rapid chirp signals, is considered to measure target range and radial velocity simultaneously even in multitarget situations. The main outcome of the coherent processing procedure applied to the received echo signal is the two-dimensional range-Doppler-matrix (RDM), which is the basis for an adaptive constant false alarm rate (CFAR) target detection technique.”; page 1818; column 1, paragraph 1 states, “Therefore the first FFT is applied to each chirp signal. The FFT splits the radar echo signal into different range gates.”; page 1818 states, “Changes in the average noise floor will be observed even in a local environment of the RDM.”)
With respect to claim 21, Kronauge et al NPL differs from the claimed invention in that it does not explicitly disclose:
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW)
for a range gate of the plurality of range gates, determining two-dimensional Fourier transform energy data larger than a noise floor level estimation value of the range gate as two-dimensional Fourier transform energy data corresponding to a target
and determining a detection result of the target according to the two-dimensional Fourier transform energy data corresponding to the target
wherein the determining the two-dimensional Fourier transform energy data larger than the noise floor level estimation value as the two-dimensional Fourier transform energy data corresponding to the target comprises:
calculating a difference value between each two-dimensional Fourier transform energy data and the noise floor level estimation value
determining two-dimensional Fourier transform energy data corresponding to a difference value larger than a preset threshold value as the two-dimensional Fourier transform energy data corresponding to the target
With respect to claim 21, Sakamoto discloses:
corresponding to a Linear Frequency Modulation Continuous Wave (LFMCW) (Kronauge et al NPL discloses frequency modulation continuous wave (FMCW), but it does not explicitly disclose linear frequency modulation continuous wave (LFMCW). Sakamoto paragraph 0009 states, “the FMCW radar transmits a radar wave via a directional antenna unit. The frequency of the radar wave is modulated so as to linearly vary in time.” One of ordinary skill in the art recognizes that LFMCW is a subset of FMCW that is common for accurate measurements in radar systems.)
With respect to claim 21, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Sakamoto into the invention of Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of accurate measurements in radar systems.
With respect to claim 21, Dizaji et al discloses:
for a range gate of the plurality of range gates, determining two-dimensional Fourier transform energy data larger than a noise floor level estimation value of the range gate as two-dimensional Fourier transform energy data corresponding to a target (As discussed above, with respect to claim 1, Dizaji et al discloses amplitude data that represents transform energy data larger than a noise floor level, such as in the abstract. The claimed limitation is obvious in view of applying the amplitude teachings of Dizaji et al to the range-Doppler-matrix (RDM) teachings of Kronauge et al NPL.)
and determining a detection result of the target according to the two-dimensional Fourier transform energy data corresponding to the target (obvious in view of combination; Both Kronauge et al NPL and Dizaji et al disclose target detection (see abstract of each).)
wherein the determining the two-dimensional Fourier transform energy data larger than the noise floor level estimation value as the two-dimensional Fourier transform energy data corresponding to the target (obvious in view of applying amplitude teachings of Dizaji et al to the range-Doppler-matrix (RDM) teachings of Kronauge et al NPL) comprises:
calculating a difference value between each two-dimensional Fourier transform energy data and the noise floor level estimation value (obvious in view of combination; Dizaji et al abstract states, “The detection module detects a target when the difference between the estimated target amplitude and the estimated noise floor amplitude is larger than the threshold value.”)
determining two-dimensional Fourier transform energy data corresponding to a difference value larger than a preset threshold value as the two-dimensional Fourier transform energy data corresponding to the target (obvious in view of combination; Kronauge et al NPL discloses the two-dimensional Fourier transform energy data. Dizaji et al discloses difference value between amplitude and noise floor.)
With respect to claim 21, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Dizaji et al into the invention of Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of accurately detecting varying detection parameters.
With respect to claim 22, Kronauge et al NPL, as modified, discloses:
An electronic device, comprising: a processor, and a memory communicatively connected to the processor; wherein the memory stores computer-executable instructions; and the processor executes the computer-executable instructions stored in the memory to implement the method of claim 21 (This limitation is directed to generic computer operations. Such operations are obvious to the teachings of modified Kronauge et al NPL. Page 1817, column 1, paragraph 2 discloses, “CFAR is very robust in multitarget situations but requires a high computation power.” This implies a computer. As discussed above, Kronauge et al NPL also discloses a CFAR processor. Sakamoto paragraph 0063 discloses a CPU, ROM, and RAM. Dizaji et al para 0057 discloses memory and computer readable medium, and computer platform.)
Claim(s) 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kronauge et al NPL (Kronauge, Matthias and Rohling, Hermann - “Fast Two-Dimensional CFAR Procedure”; IEEE Transactions on Aerospace and Electronic Systems; Vol. 49, No. 3 July 2013) in view of Sakamoto (US PgPub 20080231496) and Dizaji et al (US PgPub 20030174088), as applied to claims 1-5, 7-9, 11-12, and 16-22 above, and further in view of Bekooij et al (US PgPub 20210389443).
With respect to claim 13, Kronauge et al NPL, as modified, discloses:
The apparatus according to claim 11 (as applied to claim 11 above)
With respect to claim 13, Kronauge et al NPL, as modified, differs fromthe claimed invention in that it does not explicitly disclose:
wherein the processor is configured to, divide a plurality of preset intervals according to a data range corresponding to remaining two-dimensional Fourier transform energy data, wherein the plurality of preset intervals are arranged in an increasing or decreasing order according to a data range corresponding to each preset interval
divide the remaining two-dimensional Fourier transform energy data into the plurality of preset intervals to obtain a number of two-dimensional Fourier transform energy data in each preset interval
determine an interval in which a number of two-dimensional Fourier transform energy data is the largest or an interval in which a median of the remaining two-dimensional Fourier transform energy data is located, as a target preset interval
determine the noise floor level estimation value in the target preset interval
With respect to claim 13, Bekooij et al discloses:
wherein the processor is configured to, divide a plurality of preset intervals according to a data range corresponding to remaining two-dimensional Fourier transform energy data, wherein the plurality of preset intervals are arranged in an increasing or decreasing order according to a data range corresponding to each preset interval (paragraph 0026 of Bekooij et al states, “the selection circuit may process a plurality of numerical aggregation-based data as corresponding to the received or input signals, for processing in bins via an assessment and differentiation of the data based on numerical value(s) … a counter/register is incremented and stored as the high-level bins value. Subsequent incoming data has its value compared at each high-level bin’s assigned differentiating numerical range and if the new data value lies within the assigned differentiating numerical range for the high-level bin, a counter is incremented and stored, anew, as the high-level bins value.” Bekooij et al discloses various “bins” of data, which are analogous to the claimed intervals. Bekooij’ teachings of incrementing and storing the data allows for obvious organization of data, such for increasing or decreasing order. The claimed limitation is obvious in view of the combination of Bekooij et al with modified Kronauge et al NPL. Modified Kronauge et al NPL teaches the two-dimensional Fourier transform energy data with range gates. Bekooij et al teaches a specific was of organizing data into bins/intervals.)
divide the remaining two-dimensional Fourier transform energy data into the plurality of preset intervals to obtain a number of two-dimensional Fourier transform energy data in each preset interval (obvious in view of combination)
determine an interval in which a number of two-dimensional Fourier transform energy data is the largest or an interval in which a median of the remaining two-dimensional Fourier transform energy data is located, as a target preset interval (obvious in view of combination; As discussed above, Dizaji et al discloses amplitude data that is broadly construed to serve as “largest” data. Also, Bekooij et al paragraph 0007 states, “In a more specific example embodiment, the discovered noise floor value may be used as the median of the range of the bin that crossed the threshold …”)
determine the noise floor level estimation value in the target preset interval (obvious in view of combination; As discussed above, modified Kronauge discloses noise floor level estimation value, as does Bekooij et al (paragraph 0005).
With respect to claim 13, it would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to incorporate the teachings of Bekooij et al into the invention of modified Kronauge et al NPL. The motivation for the skilled artisan in doing so is to gain the benefit of more efficiently organizing and processing data.
With respect to claim 14, Kronauge et al NPL, as modified, discloses:
wherein the plurality of preset intervals are non-uniformly distributed (obvious in view of combination; Bekooij et al NPL paragraph 0007 states, “The selection circuit is to: for a set of data including targeted data and other data characterized or represented by a numerical aggregation-based distribution of the data in a plurality of high-level bins …” One of ordinary skill in the art would recognize that the numerical aggregation-based distribution of the data implies that the distribution is based on the specific data. If the data is not uniform, it would be obvious that the plurality of preset intervals would not be uniformly distributed.)
With respect to claim 15, Kronauge et al NPL, as modified, discloses:
wherein the processor is configured to determine the noise floor level estimation value in the target preset interval through any one of the following: taking any two-dimensional Fourier transform energy data in the target preset interval as the noise floor level estimation value; taking an average value of all two-dimensional Fourier transform energy data in the target preset interval as the noise floor level estimation value; and taking a median of all two-dimensional Fourier transform energy data in the target preset interval as the noise floor level estimation value (obvious in view of combination; Kronauge et al NPL, as modified, discloses concepts, such as average and median values above)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Baheti et al (US PgPub 20190216393) discloses a system and method for vital signal sensing using a millimeter-wave radar sensor.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEONARD S LIANG whose telephone number is (571)272-2148. The examiner can normally be reached M-F 10:00 AM - 7 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, ARLEEN M VAZQUEZ can be reached at (571)272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/LEONARD S LIANG/Examiner, Art Unit 2857 04/18/26
/ARLEEN M VAZQUEZ/Supervisory Patent Examiner, Art Unit 2857
Prosecution Insights