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
Examiner acknowledges no foreign priority is claimed.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 3/1/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered if signed and initialed by the Examiner.
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 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.
For applicant’s benefit portions of the cited reference(s) have been cited to aid in the review of the rejection(s). While every attempt has been made to be thorough and consistent within the rejection it is noted that the PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS. See MPEP 2141.02 VI.
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 1-3, 11-12 and 18-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sentelle et al. (US 2015/0301167 A1).
Regarding claim 1, Sentelle et al. (‘167) anticipates “a system comprising:
a radar device configured to transmit a radar signal and receive a return of the radar signal (paragraph 4: a device includes a radar system configured to be placed in a hiding mechanism. In one general aspect, the radar system includes one or more transmit antennas oriented within the hiding mechanism and configured to transmit one or more radar signals…the radar system includes one or more receive antennas oriented within the hiding mechanism and configured to receive reflection signals of the transmitted radar signal); and
circuitry configured to: generate a first data set representative of a range profile based at least in part on the return (paragraph 19: the electronic processor is further configured to determine, based on data corresponding to the received reflection signals, a distance range between the one or more objects and the one or more receive antennas; paragraph 26: identifying, at the processing system, a target in the generated range profile comprises analyzing the generated distance range profile to determine local maxima, comparing the local maxima to a threshold, identifying, based on the analyzing the generated distance range profile and comparing the local maxima to a threshold, one or more portions of the generated distance range profile as being associated with the target);
generate a second data set representative of a shifted version of the range profile by applying a matched filter to the return (paragraph 23: generating, at the processing system, filtered multi-frequency radar signal data that includes the identified target, extracting, at the processing system, a Doppler-induced phase of the target at the plurality of frequencies; paragraph 310: the multi-frequency radar signal may be processed by an additional process…to separate a portion of the Doppler return that arises from cardiac activity of a person monitored by the radar sensor and a portion of the return that arises from respiratory activity…any suitable processing method may be used such as, for example…matched-filter processing, or adaptive filtering techniques); and
characterizing at least one frequency-dependent object (paragraph 4: analysis and processing of multi-frequency radar signals) detected in the range profile based at least in part on the first data set and the second data set (paragraph 23: a method includes accessing, at a processing system, a multi-frequency radar signal, the multi-frequency radar signal including a plurality of frequencies, generating, at the processing system, a distance range profile based on the accessed multi-frequency radar signal, identifying, at the processing system, a target in the generated range profile, determining, at the processing system, a distance range to the identified target).”
Regarding claim 2, which is dependent on independent claim 1, Sentelle et al. (‘167) anticipates the system of claim 1. Sentelle et al. (‘167) further anticipates “the circuitry is further configured to determine a distance between the radar device and the at least one frequency-dependent object detected in the range profile based at least in part on the first data set and the second data set (paragraph 23: a method includes accessing, at a processing system, a multi-frequency radar signal, the multi-frequency radar signal including a plurality of frequencies, generating, at the processing system, a distance range profile based on the accessed multi-frequency radar signal, identifying, at the processing system, a target in the generated range profile, determining, at the processing system, a distance range to the identified target).”
Regarding claim 3, which is dependent on claim 2, Sentelle et al. (‘167) anticipates the system of claim 2. Sentelle et al. (‘167) further anticipates “the circuitry is further configured to: detect the distance between the radar device and the at least one frequency-dependent object based at least in part on the first data set; and increase a resolution of the distance between the radar device and the at least one frequency-dependent object based at least in part on the first data set and the second data set (paragraph 191: data from a SFCW radar may be processed as an ensemble of fixed-frequency CW radars, allowing for the optimum detection of the Doppler shift of a moving target over time via spectral analysis. The stepped-frequency radar data may also be processed to compress the bandwidth and obtain a high range resolution profile of the target…the data may be processed to remove stationary or fixed time delay data, leaving the moving target data to be evaluated in both the range and Doppler (velocity) dimensions; paragraph 160: the data output from the MTI filter (940A) is input to the high range resolution (HRR) processor (945A)…the Doppler processor (950A) may provide additional coherent integration gain to further improve the signal-to-noise ratio…a region detector (955A) then selects a Doppler bin with amplitude regions from range resolution cells).”
Regarding claim 11, which is dependent on independent claim 1, Sentelle et al. (‘167) anticipates the system of claim 1. Sentelle et al. (‘167) further anticipates “the circuitry is further configured to: generate the first set of data by applying a first matched filter to the return; and generate the second set of data by shifting the first matched filter by at least one offset to form the matched filter (paragraph 23: generating, at the processing system, filtered multi-frequency radar signal data that includes the identified target, extracting, at the processing system, a Doppler-induced phase of the target at the plurality of frequencies; paragraph 310: the multi-frequency radar signal may be processed by an additional process…to separate a portion of the Doppler return that arises from cardiac activity of a person monitored by the radar sensor and a portion of the return that arises from respiratory activity…any suitable processing method may be used such as, for example…FIR filtering to extract Doppler frequency region of interest…matched-filter processing, or adaptive filtering techniques).”
Regarding claim 12, which is dependent on claim 11, Sentelle et al. (‘167) anticipates the system of claim 11. Sentelle et al. (‘167) further anticipates “the circuitry is further configured to detect at least one additional frequency-dependent object in the range profile by applying the first matched filter and the matched filter to the first set of data and the second set of data (paragraph 303: the filtered multi-frequency data is generated by applying a filter to the accessed radar signal of (2810) to remove energy from the signal that is not attributable to a reflection from the target…frequency in the frequency domain data (original radar data, the accessed radar signal, or I/Q data for a stepped CW radar) corresponds to range in the range-domain…band-pass filtering the I/Q or frequency domain data entails identifying a band of frequencies corresponding to a particular range and, designing a filter, and, then, running that filter across the I/Q data so as to remove all or most of the frequency content with the exception of that corresponding to the target of interest…zeroing out entries in the range-profile and then performing a transform to the frequency domain with a FFT is equivalent to band-pass filtering in the frequency domain…one technique for filtering is to perform an inverse Fast Fourier Transform (iFFT) on the multi-frequency data to generate a range profile…after the target range is calculated from the range profile iFFT data, all ranges not associated with the target are set to have zero values…a second Fast Fourier Transform (FFT) is then used to create a new multi-frequency data set containing data for only the target of interest).”
Regarding independent claim 18, which is a corresponding apparatus claim of independent system claim 1, Sentelle et al. (‘167) anticipates all the claimed invention as shown above for claim 1. Sentelle et al. (‘167) further anticipates transmit and receive via “one or more polarimetric channels (paragraph 318: linear polarized antennas, circularly (elliptical) polarized antennas, or combinations of both may be used).”
Regarding claim 19, which is dependent on claim 18, and which is a corresponding apparatus claim of system claim 2, Sentelle et al. (‘167) anticipates all the claimed invention as shown above for claim 2.
Regarding independent claim 20, which is a corresponding method claim of independent system claim 1, Sentelle et al. (‘167) anticipates all the claimed invention as shown above for claim 1.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 4 is rejected under 35 U.S.C. 103 as being unpatentable over Sentelle et al. (US 2015/0301167 A1), and further in view of Arool Emmanuel et al. (US 11,841,455 B1).
Regarding claim 4, which is dependent on claim 3, Sentelle et al. (‘167) discloses the system of claim 3. Sentelle et al. (‘167) does not explicitly disclose “the circuitry is further configured to: determine a first reflection coefficient of the at least one frequency-dependent object based at least in part on the first data set; determine a second reflection coefficient of the at least one frequency-dependent object based at least in part on the second data set.”
Arool Emmanuel et al. (‘455) relates to radar system. Arool Emmanuel et al. (‘455) teaches “the circuitry is further configured to: determine a first reflection coefficient of the at least one frequency-dependent object based at least in part on the first data set; determine a second reflection coefficient of the at least one frequency-dependent object based at least in part on the second data set (column 14 lines 38-56: Figure 2 illustrates one or more signal representations 204 of the signal(s) 202…a signal 202 may be mathematically represented as including a coupled signal 206 (undesired) and a target reflection signal 208 (desired)…the coupled signal 206 may be represented as a product of the power/energy at which the signal 202 was transmitted by one or more of the transmitters 110 and the coupling coefficients 144 determined for pairs of the transmitters 110 and receivers 112. Similarly, the target reflection signal 208 may be represented as a product of the power/energy at which the signal 202 was transmitted by one or more of the transmitters 110 and the reflectivity of the object(s) that reflect the emitted radar signals 114 as transmitted by transmitters and that are received by receivers 112 that are paired with the transmitters 110…the signal 202 is also illustrated in FIG. 2 as corresponding to the coupling coefficient(s) multiplied by the emitted signal 210 power/energy in combination with the reflection target the reflection target coefficients 212 multiplied by the emitted signal 210 power/energy); and
increase the resolution of the distance between the radar device and the at least one frequency-dependent object based at least in part on a relationship between the first reflection coefficient and the second reflection coefficient (Figure 2: lower part…signal representations).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the system of Sentelle et al. (‘167) with the teaching of Arool Emmanuel et al. (‘455) to achieve accurate detection and resolution of objects (Arool Emmanuel et al. (‘455) – column 2 lines 42-55). In addition, both of the prior art references, (Sentelle et al. (‘167) and Arool Emmanuel et al. (‘455)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, radar system for target movement detection.
Claims 5 and 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Sentelle et al. (US 2015/0301167 A1)/Arool Emmanuel et al. (US 11,841,455 B1), and further in view of Edmonson et al. (US 2004/0118292 A1).
Regarding claim 5, which is dependent on claim 4, Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455) discloses the system of claim 4. Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455) does not explicitly disclose “the circuitry is further configured to: generate a convolution matrix with values corresponding to select ranges of interest from the range profile based at least in part on the return; and resolve the relationship between the first reflection coefficient and the second reflection coefficient based at least in part on the convolution matrix.”
Edmonson et al. (‘292) sensor detection system. Edmonson et al. (‘292) teaches “the circuitry is further configured to: generate a convolution matrix with values corresponding to select ranges of interest from the range profile based at least in part on the return; and resolve the relationship between the first reflection coefficient and the second reflection coefficient based at least in part on the convolution matrix (paragraph 33: Figure 7 shows normalized magnitude and phase graphs of a MUD encoded IDT array after a convolution of its reflected image from a set of reflectors with a reflection coefficient,
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; paragraph 34: FIG.8 shows normalized magnitude and phase graphs of two separate SAW RFID MUD encoded IDT arrays after a convolution process with a reflection coefficient,
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for both RFIDs).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the system of Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455) with the teaching of Edmonson et al. (‘292) for more accurate detection and resolution of objects (Edmonson et al. (‘292) – paragraph 25). In addition, both of the prior art references, (Sentelle et al. (‘167), Arool Emmanuel et al. (‘455) and Edmonson et al. (‘292)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, target detection through sensor.
Regarding claim 7, which is dependent on claim 5, Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455)/Edmonson et al. (‘292) discloses the system of claim 5. Sentelle et al. (‘167) further discloses “the circuitry is further configured to modify the range profile to account for a frequency dependence of the frequency-dependent object based at least in part on the relationship (paragraph 236: the range to the target may be provided by stepping through multiple transmit frequencies so that the amount of difference in phase between the transmitted signal and its received (returned) signal may be measured and used to calculate the distance, or range, to the target…the more frequency steps that are transmitted, the better the range resolution becomes; paragraph 262: the tracker 1760A maintains a history of range values 2110a-d for target 1810. When the tracker 1760A receives range value 2110e sometime after time t.sub.1, the tracker 1760A determines if the range value 2110e falls within the association window of the existing track (track 2110) for the target 1810…as shown in FIG. 21, the range value 2110e does fall within the association window of the existing track 2110 and the range value 2110e is added to the existing track 2110 for target 1810…the range value 2110e is added to the existing history for the track 2110).”
Regarding claim 7, which is dependent on claim 5, Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455)/Edmonson et al. (‘292) discloses the system of claim 5. Sentelle et al. (‘167) further discloses “the circuitry is further configured to: mitigate noise in one of the select ranges of interest via range filtering; and resolve at least one additional frequency-dependent object in the one of the select ranges of interest via range filtering (paragraph 303: the filtered multi-frequency data is generated by applying a filter to the accessed radar signal of (2810) to remove energy from the signal that is not attributable to a reflection from the target…frequency in the frequency domain data (original radar data, the accessed radar signal, or I/Q data for a stepped CW radar) corresponds to range in the range-domain…band-pass filtering the I/Q or frequency domain data entails identifying a band of frequencies corresponding to a particular range and, designing a filter, and, then, running that filter across the I/Q data so as to remove all or most of the frequency content with the exception of that corresponding to the target of interest. Zeroing out entries in the range-profile and then performing a transform to the frequency domain with a FFT is equivalent to band-pass filtering in the frequency domain…one technique for filtering is to perform an inverse Fast Fourier Transform (iFFT) on the multi-frequency data to generate a range profile…after the target range is calculated from the range profile iFFT data, all ranges not associated with the target are set to have zero values…a second Fast Fourier Transform (FFT) is then used to create a new multi-frequency data set containing data for only the target of interest).”
Claims 6 is rejected under 35 U.S.C. 103 as being unpatentable over Sentelle et al. (US 2015/0301167 A1)/Arool Emmanuel et al. (US 11,841,455 B1)/Edmonson et al. (US 2004/0118292 A1), and further in view of Thayer et al. (US 2019/0018143 A1).
Regarding claim 6, which is dependent on claim 5, Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455)/Edmonson et al. (‘292) discloses the system of claim 5. Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455)/Edmonson et al. (‘292) does not explicitly disclose “the circuitry is further configured to: generate a convolution matrix with values corresponding to select ranges of interest from the range profile based at least in part on the return; and resolve the relationship between the first reflection coefficient and the second reflection coefficient based at least in part on the convolution matrix.”
Thayer et al. (‘143) relates to sensing measurements. Thayer et al. (‘143) teaches “the circuitry is further configured to mitigate depolarization from polarimetric channels of the radar device based at least in part on the relationship (paragraph 186: to evaluate multiple scattering was to take a ratio of the returns from the cross- and co-polarized channels called the linear depolarization ratio; paragraph 316: FIG. 16 illustrates a picture of an office building measured with depolarization ratio…record data on both the co-polarized and cross-polarized channels…the ratio of these two signals provides what is called the depolarization ratio and allows for surfaces with different polarization scattering characteristics to be identified…a polarization calibration technique is performed before making the observations…the reflected signal from the glass was recorded by the lidar receiver in both the co-polarized and cross-polarized channels…this allows any differences in polarization caused by the system to be determined and accounted for when observing targets; paragraph 319: the lidar allows for precise range determination to underwater objects and can simultaneously record information about the intensity of scattered returns …the polarization discrimination of the technique uses the relative intensity between the two polarization channels to allow for the classification of objects based on their depolarization ratio…natural and man-made objects depolarize scattered light dependent on the micro-properties of the material, e.g. whether it is rough or smooth or whether the material is a dielectric or a conductor…by recording the depolarization ratio…can classify a target… in FIG. 16 can discern the difference between scattering from glass and from brick, and we can even observe differences between two types of brick…this scatterometry measurement can differentiate between materials and objects that may prove useful in autonomous vehicle advancements).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the system of Sentelle et al. (‘167)/Arool Emmanuel et al. (‘455)/Edmonson et al. (‘292) with the teaching of Thayer et al. (‘143) to provide enhanced range resolution and precise measurement (Thayer et al. (‘143) – paragraph 8). In addition, both of the prior art references, (Sentelle et al. (‘167), Arool Emmanuel et al. (‘455), Edmonson et al. (‘292) and Thayer et al. (‘143)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, radar system for target movement detection.
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Sentelle et al. (US 2015/0301167 A1), and further in view of Geralh (US H001005 H).
Regarding claim 9, which is dependent on independent claim 1, Sentelle et al. (‘167) discloses the system of claim 1. Sentelle et al. (‘167) does not explicitly disclose “the circuitry is further configured to: generate a convolution matrix with values corresponding to select ranges of interest from the radar device based at least in part on the return; and apply a Gram Schmidt filter to the convolution matrix to filter out at least one additional frequency-dependent object from the range profile.”
Geralh (‘005) relates to radar signal processing. Geralh (‘005) teaches “the circuitry is further configured to: generate a convolution matrix with values corresponding to select ranges of interest from the radar device based at least in part on the return; and apply a Gram Schmidt filter to the convolution matrix to filter out at least one additional frequency-dependent object from the range profile (column 4 lines 3-8: the adaptive noise filter comprises a plurality of transverse orthonormal ladder filters arranged in a Gram-Schmidt configuration for sequentially decorrelating each of the input signals from each of the other input signals to thereby yield said one filtered output signal; column 2 lines 18-22:
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represents the
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input covariance matrix of the auxiliary inputs and r is the
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length cross-covariance vector between the main and the
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auxiliary inputs, or more formally, column 7 lines 18-21: u(t) is an un-orthonormalized input signal,
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is the LxL covariance matrix of the u(t) and v(t) signals and
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is the cross-covariance vector of length L between u(t) and v(t)).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the system of Sentelle et al. (‘167) with the teaching of Geralh (‘005) to achieve more accurate detection and resolution of objects (Geralh (‘005) – column 1 lines 7-12). In addition, both of the prior art references, (Sentelle et al. (‘167) and Geralh (‘005)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, radar system using adaptive filtering for return signal processing.
Regarding claim 10, which is dependent on claim 9, Sentelle et al. (‘167) discloses the system of claim 9. Sentelle et al. (‘167) further discloses “the circuitry is further configured to detect at least one further object in the range profile upon filtering out the at least one additional frequency-dependent object (paragraph 223: Figure 16 is a flow chart of an example process 1600 to identify, track and classify multiple objects; paragraph 245: the CFAR filter may find targets by comparing the energy in each cell of the range-Doppler map with the average of its surrounding cells; paragraph 256: Figure 20 is a flow chart of an example process 2000 to detect multiple objects).”
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Sentelle et al. (US 2015/0301167 A1), and further in view of Yang et al. (US 2022/0357423 A1).
Regarding claim 13, which is dependent on claim 11, Sentelle et al. (‘167) discloses the system of claim 11. Sentelle et al. (‘167) does not explicitly disclose “the range profile comprises a plurality of range resolution cells corresponding to discrete ranges from the radar device; and the offset corresponds to a fraction of the size of each of the plurality of range resolution cells.”
Yang et al. (‘423) relates to radar detection. Yang et al. (‘423) teaches “the range profile comprises a plurality of range resolution cells corresponding to discrete ranges from the radar device; and the offset corresponds to a fraction of the size of each of the plurality of range resolution cells (paragraph 15: FMCW radar uses a linear frequency modulated signal to obtain range…the beat frequency is a function of the round-trip time to the reflecting target, and therefore can be mapped directly to its range… multiple radar signal chirps may be transmitted in a train of equally spaced pulses in time…radial motion occurring between pulses within a range of resolution cell induces a shift over the pulses, which may be used to compute the Doppler radial velocity in that cell…received radar data may be expressed as a three-dimensional (3D) tensor, with the first two dimensions (range and DoA) making up polar space, and the third dimension (Doppler radial velocity) containing velocity information; paragraph 51: FMCW radar uses a linear frequency modulated signal to obtain range…the beat frequency may be a function of the round-trip time to the reflecting target, and therefore can be mapped directly to its range…multiple radar signal chirps may be transmitted in a train of equally spaced pulses in time…radial motion occurring between pulses within a range of resolution cell induces a shift over the pulses, which may be used to compute the Doppler radial velocity in that cell).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the system of Sentelle et al. (‘167) with the teaching of Yang et al. (‘423) for more reliable object detection (Yang et al. (‘423) – paragraph 4). In addition, both of the prior art references, (Sentelle et al. (‘167) and Yang et al. (‘423)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, radar system for target movement detection.
Regarding claim 14, which is dependent on claim 13, Sentelle et al. (‘167)/Yang et al. (‘423) discloses the system of claim 13. Sentelle et al. (‘167) further discloses “the first set of data comprises a collection of samples that: are based at least in part on the radar signal and the return; and correspond to the discrete ranges; and the circuitry is further configured to apply at least one matched filter to each sample included in the collection of samples (paragraph 304: a Doppler-induced phase of the target at the multiple frequencies is determined (2860)…Doppler may be considered to be the time rate of change of the phase shift between samples of the frequency-domain radar data, which is I/Q (quadrature and phase) data…phase deltas (or differences in phase) measured between each frequency sample include both Doppler as well as information regarding the range to all targets within the scene…removal or minimization of the change in phase as a function of frequency allows determination of the Doppler-induced phase for each of the multiple frequencies…a linear phase ramp may be created, the ramp having a slope is a function of range to a target…by taking out this linear phase ramp (or removing the ramp from the Doppler-induced phase of the target at the multiple frequencies), only the phase that is due to Doppler remains; paragraph 305: this variation of phase as a function of frequency and range to the target is expressed in Equation 1: where “n” is the step time index, or number of frequency step periods from a reference time, “Tr” is the step time or time between frequency steps in a SFCW radar, “R.sub.o” is the range to the target, and “x” is the displacement of the target over time. In Equation 1, the returned signal on the first line contains two terms, the first term in the expression that is last on the first line contains the phase as a function of frequency for a given range and describes the phase slope that occurs as a function of range, and the second term contains the component of phase that will vary based upon target displacement x( ) that is estimated or otherwise determined…the phase is both a function of x( ) the displacement and frequency step number…the first term may be eliminated with a complex conjugate, if the range to the target Ro is known… the phase of the second term may be determined, and we normalize by the term (f/(f+ndelta_f)) to obtain an effective phase that is our desired Doppler return that is sampled at a much higher rate…the complex conjugate is estimated to take out the first term, the second term is measured, and the equivalent phase is obtained; paragraph 308: the process 2800 may be used to convert the reflected return of one pulse of multi-frequency radar data that includes Doppler-induced phase shifts at each of the multi-frequencies into an estimate of the Doppler-induced phase shift at a single frequency sampled multiple times; paragraph 310: the multi-frequency radar signal may be processed by an additional process that employs Empirical Mode Decomposition (EMD) to separate a portion of the Doppler return that arises from cardiac activity of a person monitored by the radar sensor and a portion of the return that arises from respiratory activity. In other implementations, any suitable processing method may be used such as, for example, Joint-Time Frequency Analysis, i.e. Wavelet Decomposition, Wigner-Ville transform, STFT processing, FIR filtering to extract Doppler frequency region of interest, autocorrelation analysis, peaks in autocorrelation might correspond to heart rate and/or respiration rate, matched-filter processing, or adaptive filtering techniques).”
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Sentelle et al. (US 2015/0301167 A1), and further in view of Roger et al. (US 12,189,052 B2).
Regarding claim 16, which is dependent on independent claim 1, Sentelle et al. (‘167) discloses the system of claim 1. Sentelle et al. (‘167) does not explicitly disclose “the circuitry is further configured to determine a distance between the radar device and one or more scattering components associated with the at least one frequency-dependent object based at least in part on the first data set and the second data set.”
Roger et al. (‘052) relates to radar signal processing. Roger et al. (‘052) teaches “the circuitry is further configured to determine a distance between the radar device and one or more scattering components associated with the at least one frequency-dependent object based at least in part on the first data set and the second data set (column 21 line 62- column 22 line 6: When there is a single object in one range-Doppler bin, the situation is preferable since the sample groups 1001, 1002 each lie (approximately) on a respective straight line (even if there is a phase shift between the sample groups and thus a shift between the two lines). In case there are more objects in one range-Doppler bin, the samples within the sample groups 1001, 1002 may typically be more scattered. Still, a line (i.e. linear model) can be found for each sample group 1001, 1002 and the above approach can similarly be applied to determine the shift between the lines (and thus the error compensation vector). In this case, complex mathematics may be used to find the linear model for a sample group).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the system of Sentelle et al. (‘167) with the teaching of Roger et al. (‘052) to achieve more accurate detection and resolution of objects (Roger et al. (‘052) – column 4 line 58-column 5 line 13). In addition, both of the prior art references, (Sentelle et al. (‘167) and Roger et al. (‘052)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, radar signal processing for target detection.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Sentelle et al. (US 2015/0301167 A1), and further in view of Thayer et al. (US 2019/0018143 A1).
Regarding claim 17, which is dependent on independent claim 1, Sentelle et al. (‘167) discloses the system of claim 1. Sentelle et al. (‘167) does not explicitly disclose “the circuitry is further configured to characterize a polarization response of the frequency-dependent object based at least in part on the first data set and the second data set.”
Thayer et al. (‘143) relates to sensing measurements. Thayer et al. (‘143) teaches “the circuitry is further configured to characterize a polarization response of the frequency-dependent object based at least in part on the first data set and the second data set (paragraph 186: evaluate multiple scattering was to take a ratio of the returns from the cross- and co-polarized channels called the linear depolarization ratio; paragraph 316: FIG. 16: measured with lidar depolarization ratio…record data on both the co-polarized and cross-polarized channels…the ratio of these two signals provides what is called the depolarization ratio and allows for surfaces with different polarization scattering characteristics to be identified…a polarization calibration technique is performed before making the observations …the reflected signal from the glass was recorded by the lidar receiver in both the co-polarized and cross-polarized channels…this allows any differences in polarization caused by the system to be determined and accounted for when observing targets; paragraph 319: the polarization discrimination of the technique uses the relative intensity between the two polarization channels to allow for the classification of objects based on their depolarization ratio…natural and man-made objects depolarize scattered light dependent on the micro-properties of the material, e.g. whether it is rough or smooth or whether the material is a dielectric or a conductor…by recording the depolarization ratio we can classify a target… this single-axis characterization of the material is limited but does provide valuable information as to the microphysical properties of the object…in FIG. 16 we can discern the difference between scattering from glass and from brick, and we can even observe differences between two types of brick…this scatterometry measurement can differentiate between materials and objects that may prove useful in autonomous vehicle advancements).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the system of Sentelle et al. (‘167) with the teaching of Thayer et al. (‘143) to provide enhanced range resolution and precise measurement (Thayer et al. (‘143) – paragraph 8). In addition, both of the prior art references, (Sentelle et al. (‘167) and Thayer et al. (‘143)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, target detection by return signal processing.
Allowable Subject Matter
Claim 15 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Allowable subject matter:
“the circuitry is further configured to: identify, within the plurality of range resolution cells, a remote range resolution cell in which no objects are detected; identify a matched filter corresponding to the remote range resolution cell in which no objects are detected; repurpose the matched filter for an additional range resolution cell in which the at least one frequency-dependent object is detected; and increase a resolution of the additional range resolution cell based at least in part on the repurposed matched filter.”
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Vacanti (US 10,613,198 B2) describes that the processing system 116 is coupled to the first signal generator 114 and controls the frequency of the sinusoidal waveform, and hence the simulated RADAR return signal 102B…the processing system 16 is also configured to be coupled to the integrated RADAR system 102, e.g. to activate the integrated RADAR system 102, control the integrated RADAR system 102, and record and analyze the data generated by the integrated RADAR system 102. Data generated by the integrated RADAR system 102 includes data representative of the simulated range of the simulated RADAR return signal 102B (column 4 lines 54-64).
Picciolo et al. (US 8082286 B1) describes that for a Gram-Schmidt cascaded canceller, the Gram-Schmidt weight is multiplied by the soft-weight value to produce the desired results…for any other cascaded canceller, the adaptive weight, whether Gram-Schmidt or another weight, value is multiplied by the soft-weight value…for a Multi-Stage Weiner Filter with Gram-Schmidt weights applied to the synthesis stage, the adaptive, Gram-Schmidt weight is multiplied by the soft-weight value. In certain embodiments, such as the multi-stage median cascaded canceller, pseudo-median cascaded canceller, Gram-Schmidt cascaded canceller, or any other generic cascaded canceller, the soft weight value may be reiteratively applied to further improve the convergence and produce reduced-rank characteristics (column 4 lines 33-45).
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/NUZHAT PERVIN/Primary Examiner, Art Unit 3648