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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. EP 23171093, filed on May 2, 2023.
Information Disclosure Statement
The information disclosure statement (IDS) submitted is not in compliance with the provisions of 37 CFR 1.97 because Applicant did not sign the certification page. Nonetheless, the Examiner considered the references in the IDS.
NOTE: Applicant needs to sign certification statement of the IDS.
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 – 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite the abstract ideas as explained in the Step 2A, Prong I analysis below. This judicial exception is not integrated into a practical application as explained in Step 2A, Prong 2 analysis below. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as explained in Step 2B analysis below.
Step 2A, Prong 1:
Step 2A, prong 1, of the 2019 Guidance, first looks to whether the claim recites any judicial exceptions, including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activities such as a fundamental economic practice, or mental processes). 84 Fed. Reg. at 52–54.
Under the broadest reasonable interpretation the features of the independent claims are directed to mathematical concepts as evidenced by the following features: determining, based on the obtained measurement data, one or more data sets indicative of a variation of the one or more radar signals (variation can be simple subtraction – difference. Could also be mathematical variance or standard deviation.); determining, based on the one or more data sets and/or based on the obtained measurement data, angle data relating to the object (geometry/trigonometry); and calibrating, based on the one or more data sets and the angle data, the radar sensor (this is done by a matrix as shown in claim 11 which mathematical as evidenced by Para. 57 diagonal calibration matrix. See also equations in Para. 111.). see claim 1 and similar language in claims 13 and 15.
Dependent claim 2 is directed to more processing in general.
Dependent claim 3 is directed to weighting which can be considered multiplication.
Dependent 4 is directed to beam vectors which is similar to weighting similar to multiplication as broadly claimed.
Dependent 5 as broadly claimed can be mathematical.
Dependent claims 6 – 7 are directed to accumulation which is mathematical, e.g. summing or averaging.
Dependent claim 8, angle projected onto line-of-sight of radar and radial velocity are mathematically related.
Dependent claim 9 as broadly claimed is a mental process wherein a user can determine based on each calibration when to stop.
Dependent claim 10 is directed to more than one optional feature and at least the feature of the range determination is mathematical, e.g., roundtrip delay.
Dependent claim 11 is directed to a mathematical matrix as discussed supra.
Dependent claim 12 is directed to more than one optional feature and at least the feature of the display of a detected object is data gathering considered extra-solution activity.
Dependent claims 43 – 48 further define mathematical concepts.
Step 2A, Prong 2:
Step 2A, prong 2, of the 2019 Guidance, next analyzes whether claims 22, 33, 36 and 41 recite additional elements that individually or in combination integrate the judicial exception into a practical application. 2019 Guidance, 84 Fed. Reg. at 53–55. The 2019 Guidance identifies considerations indicative of whether an additional element or combination of elements integrate the judicial exception into a practical application, such as an additional element reflecting an improvement in the functioning of a computer or an improvement to other technology or technical field. Id. at 55; MPEP § 2106.05(a).
In addition to reciting the above-noted abstract ideas, the issue is whether the claims as a whole including various additional elements integrate the abstract ideas into a practical application. In other words, do the claims as a whole produce any meaningful limits, i.e. improvement in technology?
The improvement as stated by the specification is that the matrix calibration can be performed in a single chamber measurement. See Para. 57. Whereas traditional offline chamber calibration requires several offline measurements. See Para. 6.
The additional limitation of the claims is the claimed “obtaining measurement data from a radar sensor by one or more radar signals, wherein the measurement data is indicative of a radial velocity of an object and includes a range dimension.” See claim 1 and similar language in claims 13 and 15). This limitation is data gathering thus considered extra-solution activity. The claims also appear to describe a general-purpose computer. Using generic computer components to implement an abstract idea does not integrate the abstract idea into a practical application. See, e.g., Alice, 573 U.S. at 223–24; see also Memorandum, 84 Fed. Reg. at 55 (explaining that courts have identified merely using a computer as a tool to perform an abstract idea as an example of when a judicial exception has not been integrated into a practical application).
The radar is not positively recited a being part of the invention. Nonetheless, the radar is claimed at a high level of generality for the purpose of data gathering is considered extra-solution activity.
Here, the improvement appears to be a result of the mathematical concepts and not necessarily due to the arrangement of the hardware as claimed.
Even though an improvement exists, the claimed subject matter is still abstract because all of the features discussed supra are either abstract, e.g., mathematical, or extra-solution activity. A claim for a useful or beneficial abstract idea is still an abstract idea. See Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, 1379–80 (Fed. Cir. 2015).
None of the additional limitations provide a meaningful limit on the claim invention. Rather, the additional limitations are directed to data gathering and data processing which is an extra-solution activity.
Step 2B:
Under step 2B of the 2019 Guidance, the issue is whether the claims adds any specific limitations beyond the judicial exception that, either alone or as an ordered combination, amount to more than “well-understood, routine, conventional” activity in the field. 84 Fed. Reg. at 56; MPEP § 2106.05(d).
More specifically, the issue is whether the ordered combination of structural features and/or steps are considered well-understand, routine and conventional or whether the ordered combination itself provides for an improvement of a particular structure. For example, the integration of a computer with a sensor is conventional because a sensor collects data and a computer performs calculations and processing on data from said sensors. Again, the claims do not positively recite a radar. Even if the radar were positively recited, the combination of a processor and radar is well-understood, conventional and routine as discussed.
BASCOM Global Internet v. AT&T Mobility LLC, 119 USPQ2d 1236 (Fed. Cir. 2016) (BASCOM) provides, in summary, an example wherein the local computer, ISP server, internet computer network and controlled access network are generic computer and networking components that when taken individually do not amount to significantly more but taken together provided for an unconventional and non-generic combination of known elements that result in an improvement of filtering content thus amounting to significantly more.
Overall, all of the claimed features directed to mathematical concepts that are applied using a well-understood, routine and conventional setup of processing circuitry with sensor circuitry wherein the sensor circuitry is used mostly for data gathering.
The improvement, as mentioned earlier, appears to be a result of the mathematical concepts and not necessarily due to the arrangement of the hardware as claimed, at least under the broadest reasonable interpretation of the claims as currently written.
Again, a claim for a useful or beneficial abstract idea is still an abstract idea. See Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, 1379–80 (Fed. Cir. 2015). As such, the ordered combination of features is directed solely to abstract ideas, extra-solution activity and activity that is considered well-understood, routine and conventional as discussed supra. The same reasoning applies to the dependent claims.
The dependent claims 2 – 12 discussed supra further define the abstract idea in the independent claims or add limitations which recite abstract ideas similar to the ones addressed above or provide for extra-solution activity and/or intended use.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 – 5, 7 – 8 and 10 – 15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Alcalde (US 20180120414 A1).
Examiner’s Note: the language wherein the measurement data is indicative of a radial velocity of an object and includes a range dimension as written may be partially, e.g., indicative of radial velocity, interpreted as being inherent. The Examiner suggests obtaining radar (or raw) data from a radar sensor by one or more radar signals, wherein the radar data is processed to obtain measurement data; wherein the measurement data is indicative of a radial velocity of an object and includes a range dimension.
As to claims 1 and 13 – 15, Alcalde discloses the computer-implemented method for calibration of a radar sensor, the method comprising:
obtaining measurement data from a radar sensor by one or more radar signals, wherein the measurement data is indicative of a radial velocity of an object and includes a range dimension (Fig. 1 items 58, 60);
determining, based on the obtained measurement data, one or more data sets indicative of a variation of the one or more radar signals (Para. 24 “the controller 40 determines a calibration-matrix 54 of the system 10 based on a difference between the plurality of detections 48 and the ideal-response 52 when the object 20 is stationary, where the difference is based on an angle difference between an indicated-angle 66 at an indicated-range-rate 60 and an ideal-angle at an ideal-range-rate indicated by the ideal-response 52 for the condition that the ideal-range-rate is equal to the indicated-range-rate 60.”);
determining, based on the one or more data sets and/or based on the obtained measurement data, angle data relating to the object (Fig. 1 item 54 adjusted-angle); and
calibrating, based on the one or more data sets and the angle data, the radar sensor (Para. 24 calibration matrix and Fig. 1 adjusted-angle item 54).
Alcalde also discloses a vehicle. See Alcalde Fig. 1.
As to claim 2, Alcalde discloses the computer-implemented method of claim 1 further comprising: obtaining information of one or more antennas of the radar sensor and of expected ideal measurements (Paras. 24 and 32 describe ideal response related to antennae.); and
calculating, based on the one or more data sets, the angle data, and the information, one or more processed data sets, wherein the calibrating is based on the one or more processed data sets (Fig. 1 Controller having calibration-matrix 54 and all other relevant item numbers).
As to claim 3, Alcalde discloses the computer-implemented method of claim 2 wherein the calculating includes weighting of one or more values of the one or more data sets (Para. 24 The ordinarily skilled understand steering vectors to be weights that reshape and/or steer the antennae lobes.).
As to claim 4, Alcalde discloses the computer-implemented method of claim 3 wherein: the weighting of the one or more values of the one or more data sets is performed by scaling ideal beamvectors (Para. 24 Steering vectors); and the ideal beamvectors are based on a structural arrangement of the radar sensor and/or on an additional angle data of the object (Fig. 4 – the steering vectors have to take into account time delays related to structure.).
As to claim 5, Alcalde discloses the computer-implemented method of claim 1 wherein: the angle data of the object includes ambiguous angle data; and the method further includes a disambiguation process (Para. 30 wherein Alcalde discloses a face-linearity to select suitable objects while discarding non-suitable objects in order to avoid angular ambiguities.).
As to claim 7, Alcalde discloses the computer-implemented method of claim 3 wherein calculating the one or more processed data sets includes accumulation over the radial velocity dimension of the measurement data (Para. 18 “collecting/averaging range-rates”).
As to claim 8, Alcalde discloses the computer-implemented method of claim 1 wherein determining the angle data of the object includes determining the angle data from the radial velocity of the measurement data (Fig. 3).
As to claim 10, Alcalde discloses the computer-implemented method of claim 1 wherein the measurement data is further indicative of at least one of:
a range of the object (Fig. 1 item 58 indicated distance),
an ego-motion of the radar sensor, an ego-motion of a vehicle including the radar sensor (Fig. 1 stationary object such as a road sign provides ego-motion), or
information of a radar sensor arrangement including a structural arrangement of the radar sensor in a vehicle (Fig. 4, Para. 2 “At each angle, a response in the form of complex voltages is collected for each element of the antenna, and these responses can be used to fully determine a default or initial calibration of the system. That is, where the responses deviate from an expected or ideal-response is noted and a correction factor or calibration-matrix is established to correct or compensate the complex-voltages from each element of the antenna for each of the angles tested.”).
As to claim 11, Alcalde discloses the computer-implemented method of claim 1 wherein the calibrating the radar sensor includes determining, based on one or more accumulated data sets and the angle data, a calibration matrix for the radar sensor (Fig. 1 item 54 Calibration-matrix and Para. 18 “collecting/averaging range-rates associated with stationary-objects located near the bore-site 46 (FIGS. 2A and 2B) of the system 10.”)
As to claim 12, Alcalde discloses the computer-implemented method of claim 1 further comprising: determining, based on the calibration of the radar sensor, an operating instruction for a vehicle affecting a task of a vehicle assistance system, wherein the task includes at least one of: displaying a detected object on a display of the vehicle, conducting a vehicle path planning, triggering a warning, affecting control of the vehicle during a parking process, affecting control of the vehicle during driving, mapping, based on the calibration of the radar sensor, reference maps for further applications, or creating, based on the calibration of the radar sensor, reference maps for further applications (Fig. 1 Vehicle Controls: steering, accelerator and brakes.).
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 5 is rejected under 35 U.S.C. 103 as being obvious over Alcalde in view of Li (US 20230131090 A1).
In the event that Applicant successively argues for a stricter interpretation of disambiguation, the Examiner introduces a secondary reference.
In the same field of endeavor, Li teaches “subsampling on the Doppler dimension may be used to disambiguate Doppler ambiguity introduced as a result of low computational overhead Doppler transformations such as Doppler FFT operations, and subsampling on elevation and/or azimuth angles may be used to disambiguate angle or aperture ambiguity introduced as a result of low computational overhead beamforming transformations such as beamforming FFT operations (Para. 89).”
In view of the teachings of Li, it would have been obvious to the ordinarily skilled before filing to include subsampling in order to mitigate ambiguities thereby improving accuracy.
Claim 6 is rejected under 35 U.S.C. 103 as being obvious over Alcalde in view of Kato (US 20130282236 A1).
As to claim 6, Alcalde does not disclose the computer-implemented method of claim 1 wherein determining the one or more data sets indicative of a variation of the one or more radar signals includes accumulation over the range dimension of the measurement data.
In the same field of endeavor, Kato discloses “the sensor data buffer 212 is used, values resulting from mixing (addition, averaging or the like with prescribed weights) of the relative distances 602, the relative position angles 603, the relative speeds 604 and the directions 605 of data on two detected vehicles in the pre-integration processing data buffer 213 are stored (Para. 105).”
In view of the teachings of Kato, it would have been obvious to the ordinarily skilled before filing to include averaging as a way to reduce noise effects thereby improving accuracy.
Claim 9 is rejected under 35 U.S.C. 103 as being obvious over Alcalde in view of Burri (US 20090195442 A1).
As to claim 9, Alcalde does not teach the computer-implemented method of claim 1 wherein the obtaining the measurement data, the determining the one or more data sets, and the determining the angle data are performed one or more times and are stopped being performed in response to a stopping criteria being fulfilled.
In the same field of endeavor, Burri discloses “This iterative correction is performed until a satisfaction criterion or stopping condition is achieved. (Para. 90).”
In view of the teachings of Burri, it would have been obvious to the ordinarily skilled before filing to include iterative calibration until satisfied in order to give a reasoanble result ensuring accuracy while not committing waste by continually calibration once a condition has been satisfied thereby reducing computation.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL W JUSTICE whose telephone number is (571)270-7029. The examiner can normally be reached 7:30 - 5:30 M-F.
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/MICHAEL W JUSTICE/Examiner, Art Unit 3648