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 Amendment
The amendment filed 1/23/2056 has been entered. Claims 1-20 are pending
Response to Arguments
Applicant’s arguments, see ‘Rejections of Claims 1-13 under 35 USC 101’, filed 1/23/2026, with respect to Claims 1-13 have been fully considered and are persuasive. The 35 USC 101 rejection of claims 1-13 have been withdrawn.
Applicant’s arguments, see: section 3 on page 9, sections 4 and 5 on page 10, section 6 on page 11, section 7 and 8 on page 12, filed 1/23/2026, with respect to the rejection(s) of claim(s) 1, 2, 5-15, 17-19 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Bonta (US 5245347 A).
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 14-18 and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claims 14 and 19
Step 1: Claims 14-18 are directed to an apparatus, which is a machine; and claims 19-20 are directed to a processor, which is a machine. Therefore, the claims fall within one of the four statutory categories.
Step 2A Prong 1: Claims 14 and 19 recite the limitations of taking a radar signal, determining a threshold, suppressing signal and identifying a range of a target. These series of steps is a process that, under the broadest reasonable interpretation, covers limitations that can be performed in the human mind using mathematical calculations/formulas on a piece of paper, these steps are observations, evaluations, judgments, and/or opinions, which fall into the mental process group and the mathematical concepts group of abstract ideas. Nothing in the claim precludes them from being performed in the human mind, with or without the aid of a physical aid such as pen and paper (See MPEP 2016.04(a) and MPEP 2106.04 (III) B and 2019 PEG )
Step 2A Prong 2: The judicial exception is not integrated into a practical application because the claim does not recite any additional elements that amount to significantly more than the judicial exception. Claims 14 and 19 recites receiving a radar signal and producing a frequency data set from digitized samples, these are routine steps are discussed at a high level of generality. A radar processor has been claimed however it is not a particular machines as a processor is a generic machine. A person could receive the data and input it into a program such as Excel or create their own table of data with pen and paper. The steps of receiving a signal and producing a data set amounts to mere data gathering/data manipulation and data inputs and does not add more than insignificant extra solution activity to the abstract idea. A vehicle control system, for example, needs to be provided with the modified range data in order to implement an improvement. For at least the above reasons the receiving and producing limitations do not integrate the abstract idea into a practical application.
Step 2B: The claim does not provide an inventive concept because as recited in the paragraphs above, the claim recites the limitations of receiving a radar signal and producing a frequency data set, an insignificant extra-solution activity that does not amount to an inventive concept. The use of digitized data does not make the limitations other than abstract. Moreover, the limitations do not reflect an improvement that can be implemented, or include the use of a particular machine. Therefore, the claims are not eligible under 35 U.S.C. 101.
The claims 15-18, which depend from claim 14; and claim 20, which depend from claim 19, similarly only recite the abstract ideas through mental processes and/or mathematical concepts as they produce data sets, apply algorithms, and identify results but do not use the results to implement an improvement. As such, they are also not eligible under 35 USC 101.
Claim Rejections - 35 USC § 103
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 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 1, 5, 14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Melzer (US20190113600A1) in view of Bonta (US 5245347 A).
Regarding claim 1 Melzer discloses
A method comprising: receiving at a radar processor of an apparatus a radar signal comprising a plurality of radar chirp reflections based on a transmitted radar signal reflecting from one or more targets ( Figure 5; Paragraph 0036, "As mentioned before with reference to FIG. 5, the outgoing radar signal is composed of a sequence of “frequency ramps” also referred to as “chirp pulses” or “chirps”. Dependent on the application, a defined modulation pause may be inserted between two contiguous chirps"; Paragraph 0045, “Interference signals received by the RF frontend of a radar sensor superpose on the radar echoes caused by real targets and may at least temporarily increase the overall noise floor to values so high that detection of radar targets becomes impossible or at least prone to error”; Paragraph 0008, “Furthermore, a radar device is described herein. In accordance with one embodiment, the radar device includes a radar receiver configured to provide a digital radar signal and a processor”); producing, by the radar processor, a plurality of frequency data sets from digitized samples generated from the received radar signal, wherein each frequency data set of the plurality of frequency data sets is associated with a corresponding received chirp reflection of the plurality of radar chirp reflections (Paragraph 0015, “FIG. 5 is a timing diagram illustrating a sequence of chirps used for data acquisition in a radar sensor”; Paragraph 0044, “ As mentioned the Range Maps R[n, m], the Range-Doppler Maps X[n, m] or the radar data cubes may be used as input data for various signal processing techniques to detect radar targets in the surrounding (field of view) of the radar sensor”); and identifying, by the radar processor, a range associated with the one or more targets based on the plurality of modified frequency data sets to produce range data: (Paragraph 0069, "Finally, the Range/Doppler Map X[n, m] may be calculated from the Range Map or the smoothed Range Map (step S 3 ), and the target detection (e.g. detection of distance, speed, angle) may be performed based on the Range/Doppler Map (step S 4 ). The results of the interference detection (Step S 2 ′) may be used for the target detection, e.g. to assess the reliability of the target detection and the related position (distance and angle) and speed measurements”) providing the range data to a vehicular control system via a data interface (Paragraph 0031, “The digital signal processor 40 (DSP) may be part of the system controller 50 or separate therefrom”; Paragraph 0067, “This interference detection may be done before the smoothing operation and those chirps, in which interference has been detected, may be digitally communicated to a superordinate (higher level) controller to signal that measurements based on those chirps may be unreliable”; Paragraph 0008, “In this embodiment, the processor is configured to calculate a Range Map based on the digital radar signal”). Melzer does not disclose determining, by the radar processor, a threshold based on magnitudes of samples across the plurality of frequency data sets; suppressing, by the radar processor, samples in the plurality of frequency data sets based on the threshold to produce a plurality of modified frequency data sets; recovering, by the radar processor, selected portions of the radar signal in the plurality of modified frequency data sets that were removed by suppressing the samples to fill in gaps.
Bonta discloses
Determining, by the radar processor, a threshold based on magnitudes of samples across the plurality of frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "; Abstract, "The SAR consists, in effect, of four frequency-agile radars"; Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process."); suppressing, by the radar processor, samples in the plurality of frequency data sets based on the threshold to produce a plurality of modified frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "); recovering, by the radar processor, selected portions of the radar signal in the plurality of modified frequency data sets that were removed by suppressing the samples to fill in gaps (Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process.").
Melzer discloses suppressing interference to produce a modified dataset but not with a threshold based on magnitude. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Additionally, with the removal and fill process of Bonta, Melzer can retain local variations that a smoothing function may erase. Leading to higher quality data where there is data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold instead of a smoothing function to ease the computational load on the radar device and have higher quality data.
Regarding claim 5 the combination of Melzer and Bonta discloses
The method of claim 1. Melzer further discloses wherein determining the threshold comprises executing, by the radar processor, a constant false alarm rate (CFAR) detection or median detection (Column 1 lines 17-20, "Automatic detection radars use an interference thresholding circuit called CFAR (constant false alarm rate). A CFAR establishes threshold levels at a plurality of radar resolution cells to automatically reject clutter and noise").
Regarding claim 14 Melzer discloses
An apparatus comprising: a radar front end configured to convert a received radar signal from one or more targets to digitized samples (Figure 3 elements 10 and 30; Paragraph 0015, “FIG. 5 is a timing diagram illustrating a sequence of chirps used for data acquisition in a radar sensor”; Paragraph 0044, “ As mentioned the Range Maps R[n, m], the Range-Doppler Maps X[n, m] or the radar data cubes may be used as input data for various signal processing techniques to detect radar targets in the surrounding (field of view) of the radar sensor”); a radar processor configured to execute instructions from a memory that cause the radar processor to (Paragraph 0008, “In accordance with one embodiment, the radar device includes a radar receiver configured to provide a digital radar signal and a processor. In this embodiment, the processor is configured to calculate a Range Map based on the digital radar signal” where storing values in a range map requires memory): produce a plurality of frequency data sets from the digitized samples, wherein each frequency data set of the plurality of frequency data sets is associated with a corresponding received chirp reflection of a plurality of radar chirp reflections in the received radar signal (Paragraph 0015, “FIG. 5 is a timing diagram illustrating a sequence of chirps used for data acquisition in a radar sensor”; Paragraph 0044, “ As mentioned the Range Maps R[n, m], the Range-Doppler Maps X[n, m] or the radar data cubes may be used as input data for various signal processing techniques to detect radar targets in the surrounding (field of view) of the radar sensor”); and identify a range associated with the one or more targets based on the plurality of modified frequency data sets (Paragraph 0069, "Finally, the Range/Doppler Map X[n, m] may be calculated from the Range Map or the smoothed Range Map (step S 3 ), and the target detection (e.g. detection of distance, speed, angle) may be performed based on the Range/Doppler Map (step S 4 ). The results of the interference detection (Step S 2 ′) may be used for the target detection, e.g. to assess the reliability of the target detection and the related position (distance and angle) and speed measurements”). Melzer does not disclose determining a threshold based on magnitudes of samples across the plurality of frequency data sets; suppressing samples in the plurality of frequency data sets based on the threshold to produce a plurality of modified frequency data sets; recover selected portions of the radar signal in the plurality of modified frequency data sets that were removed by suppressing the samples to fill in gaps.
Bonta discloses
Determining a threshold based on magnitudes of samples across the plurality of frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "; Abstract, "The SAR consists, in effect, of four frequency-agile radars"; Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process."); suppressing samples in the plurality of frequency data sets based on the threshold to produce a plurality of modified frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "); recover selected portions of the radar signal in the plurality of modified frequency data sets that were removed by suppressing the samples to fill in gaps (Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process.").
Melzer discloses suppressing interference to produce a modified dataset but not with a threshold based on magnitude. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Additionally, with the removal and fill process of Bonta, Melzer can retain local variations that a smoothing function may erase. Leading to higher quality data where there is data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold instead of a smoothing function to ease the computational load on the radar device and have higher quality data.
Regarding claim 19 Melzer discloses
A radar processor configured to (Paragraph 0008, “In accordance with one embodiment, the radar device includes a radar receiver configured to provide a digital radar signal and a processor. In this embodiment, the processor is configured to calculate a Range Map based on the digital radar signal”): produce a plurality of frequency data sets from digitized samples generated from a received radar signal, wherein each frequency data set of the plurality of frequency data sets is associated with a corresponding received chirp reflection of a plurality of radar chirp reflections in the received radar signal (Paragraph 0015, “FIG. 5 is a timing diagram illustrating a sequence of chirps used for data acquisition in a radar sensor”; Paragraph 0044, “ As mentioned the Range Maps R[n, m], the Range-Doppler Maps X[n, m] or the radar data cubes may be used as input data for various signal processing techniques to detect radar targets in the surrounding (field of view) of the radar sensor”); and identify a range associated with one or more targets based on the plurality of modified frequency data sets (Paragraph 0069, "Finally, the Range/Doppler Map X[n, m] may be calculated from the Range Map or the smoothed Range Map (step S 3 ), and the target detection (e.g. detection of distance, speed, angle) may be performed based on the Range/Doppler Map (step S 4 ). The results of the interference detection (Step S 2 ′) may be used for the target detection, e.g. to assess the reliability of the target detection and the related position (distance and angle) and speed measurements”). Melzer does not disclose determining a threshold based on magnitudes of samples across the plurality of frequency data sets; suppressing samples in the plurality of frequency data sets based on the threshold to produce a plurality of modified frequency data sets; recover selected portions of the radar signal in the plurality of modified frequency data sets that were removed by suppressing the samples to fill in gaps.
Bonta discloses
Determining a threshold based on magnitudes of samples across the plurality of frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "; Abstract, "The SAR consists, in effect, of four frequency-agile radars"; Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process."); suppressing samples in the plurality of frequency data sets based on the threshold to produce a plurality of modified frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "); recover selected portions of the radar signal in the plurality of modified frequency data sets that were removed by suppressing the samples to fill in gaps (Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process.").
Melzer discloses suppressing interference to produce a modified dataset but not with a threshold based on magnitude. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Additionally, with the removal and fill process of Bonta, Melzer can retain local variations that a smoothing function may erase. Leading to higher quality data where there is data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold instead of a smoothing function to ease the computational load on the radar device and have higher quality data.
Claims 2 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Melzer (US20190113600A1) in view of Bonta (US 5245347 A) further in view of Hameed 2022 [S. W. Hameed, “Peaks Detector Algorithm after CFAR for Multiple Targets Detection”, EAI Endorsed Trans AI Robotics, vol. 1, p. e11, Jul. 2022.].
Regarding claim 2 the combination of Melzer and Bonta discloses
The method of claim 1 including the radar processor. Melzer does not disclose wherein determining the threshold comprises: computing, by the radar processor, a magnitude at each sample position across the plurality of frequency data sets, wherein each sample position comprises a similar time and frequency index in each of the plurality of frequency data sets; and identifying, by the radar processor, a maximum of the computed magnitudes for all of the sample positions across the plurality of frequency data sets to produce a plurality of maxima.
Bonta discloses
Wherein determining the threshold comprises: computing a magnitude at each sample position across the plurality of frequency data sets, wherein each sample position comprises a similar time and frequency index in each of the plurality of frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "; Abstract, "The SAR consists, in effect, of four frequency-agile radars"; Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process.").
Melzer discloses suppressing interference but not with a threshold based on magnitude and not by calculating the magnitude at every position. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Also, every position in the sample data would need to be considered to accurately calculate the noise floor. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold and consider all the positions to ease the computational load on the radar device and accurately calculate the noise floor.
Hameed discloses
Identifying a maximum of the computed magnitudes for all of the sample positions across the plurality of frequency data sets to produce a plurality of maxima (Abstract, "The novelty of the algorithm is that it works well to extract a single peak for each of all targets in the multiple targets environment, as compared to the conventional global maxima finding techniques which outputs only one target of the maximum amplitude while suppressing the rest of the small targets. The algorithm is basically a local maxima finder algorithm termed as peaks detector algorithm").
Melzer and Hameed are analogous art as they both concern radar interference mitigation. Melzer discloses suppressing interference but not finding the maximum magnitudes in the signal. It would be advantageous to know all of the local maximums in the signal, especially when using a threshold, to avoid confusing noise with a potential target. Multiple peaks in the signal could be the same target multiple times or different targets, it would be a more efficient use all of that data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Hameed to including finding the maximum magnitude in the data to avoid removing target data.
Regarding claim 15 the combination of Melzer and Bonta discloses
The apparatus of claim 14 including a processor. Melzer does not disclose the radar processor configured to: compute a magnitude at each sample position across the plurality of frequency data sets, wherein each sample position comprises a similar time and frequency index in each of the plurality of frequency data sets; and identify a maximum of the computed magnitudes for all of the sample positions across the plurality of frequency data sets to produce a plurality of maxima.
Bonta discloses
Computing a magnitude at each sample position across the plurality of frequency data sets, wherein each sample position comprises a similar time and frequency index in each of the plurality of frequency data sets (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A "; Abstract, "The SAR consists, in effect, of four frequency-agile radars"; Column 51 lines 24-36, "The adaptive compression process involves rearranging the data samples in each of the four maps in accordance with their amplitude distribution… The amplitude corresponding to the greatest number of samples is then used to form the mean and four bit magnitude words formed about such mean. The resulting four bit magnitude maps are then incoherently added to form a single display map. The incoherent addition tends to fill in the gaps in the individual maps identified in the ECM editing process.").
Melzer discloses suppressing interference but not with a threshold based on magnitude and not by calculating the magnitude at every position. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Also, every position in the sample data would need to be considered to accurately calculate the noise floor. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold and consider all the positions to ease the computational load on the radar device and accurately calculate the noise floor.
Hameed discloses
Identifying a maximum of the computed magnitudes for all of the sample positions across the plurality of frequency data sets to produce a plurality of maxima (Abstract, "The novelty of the algorithm is that it works well to extract a single peak for each of all targets in the multiple targets environment, as compared to the conventional global maxima finding techniques which outputs only one target of the maximum amplitude while suppressing the rest of the small targets. The algorithm is basically a local maxima finder algorithm termed as peaks detector algorithm").
Melzer and Hameed are analogous art as they both concern radar interference mitigation. Melzer discloses suppressing interference but not finding the maximum magnitudes in the signal. It would be advantageous to know all of the local maximums in the signal, especially when using a threshold, to avoid confusing noise with a potential target. Multiple peaks in the signal could be the same target multiple times or different targets, it would be a more efficient use all of that data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Hameed to including finding the maximum magnitude in the data to avoid removing target data.
Claims 6, 7, 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Melzer (US20190113600A1) in view of Bonta (US 5245347 A) further in view of Corbett (US 201700010344).
Regarding claim 6 the combination of Melzer and Bonta discloses
The method of claim 1 including the radar processor. Melzer discloses wherein producing the plurality of frequency data sets from digitized samples generated from the received radar signal comprises: receiving the digitized samples from one or more analog-to-digital converters (ADC) at a radar front end (Figure 3 element ADC 30). The combination of Melzer and Bonta does not disclose and applying a Short-Time Fourier Transform (STTF) to the digitized samples to produce the plurality of frequency data sets, each of the plurality of frequency data sets comprising samples in a time domain and a frequency domain.
Corbett discloses
Applying a Short-Time Fourier Transform (STTF) to the digitized samples to produce the plurality of frequency data sets, each of the plurality of frequency data sets comprising samples in a time domain and a frequency domain (Paragraph 0033, "In one implementation, the radar interference mitigation module 200 of FIG. 2 refers to a technique, method, or process flow that uses a short-time Fourier transform (STFT) to detect and repair interference in FMCW waveforms."; Paragraph 0051, "Next, a reverse time-frequency transform may be performed on the repaired time-frequency signal. FIG. 10 shows an example repaired signal 1000 in time domain, where the repaired T-F representation is transformed back to the time domain using the inverse T-F transform (e.g., in this case, inverse STFT)").
Melzer and Corbett are analogous art as they both concern radar interference mitigation. Melzer discloses performing a FFT on the chirps but not a STFT. It would be advantageous to use a STFT method instead of/in addition to a FFT since a STFT analysis can be superior at tracking moving or transient targets. Tracking moving/transient targets is of particular concern in a driving environment. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Corbett to use an STFT analysis to improve the tracking/recognition of moving or transient targets.
Regarding claim 7 the combination of Melzer, Bonta and Corbett discloses
The method of claim 6 including the radar processor. Melzer discloses wherein identifying the range associated with the one or more targets is performed based on a range spectrum generated based on the plurality of modified digitized samples (Paragraph 0063, "The smoothed Range Map R′ [n, m] can be further processed in any particular manner, e.g. by applying the second stage of FFTs to the lines of the Range Map R′ [n, m] in order to obtain the Range-Doppler Map X[n,m], which allows, inter alia, detection of target velocities"). The combination of Melzer and Bonta does not disclose further comprising: computing an inverse STFT of each modified frequency data set in the plurality of modified frequency data sets to generate a plurality of modified digitized samples.
Corbett discloses
Further comprising: computing an inverse STFT of each modified frequency data set in the plurality of modified frequency data sets to generate a plurality of modified digitized samples (Paragraph 0051, "Next, a reverse time-frequency transform may be performed on the repaired time-frequency signal. FIG. 10 shows an example repaired signal 1000 in time domain, where the repaired T-F representation is transformed back to the time domain using the inverse T-F transform (e.g., in this case, inverse STFT). Next, a windowing and FFT processing of the repaired time domain signal may be performed").
Melzer and Corbett are analogous art as they both concern radar interference mitigation. Melzer discloses performing a FFT on the chirps but does not explicitly mention an inverse method. It would be advantageous to use a reverse FFT/STFT method instead so that the device can extract information (like target detection) from the time domain signal after cleaning the data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Corbett to explicitly include an inverse Fourier transform so that data can be extracted from time domain data, instead of skipping a processing step.
Regarding claim 8 the combination of Melzer, Bonta and Corbett discloses
The method of claim 7. Melzer further discloses further comprising generating, by the radar processor, the range spectrum by taking a fast Fourier Transform (FFT) of the plurality of modified digitized samples (Paragraph 0063, "The smoothed Range Map R′ [n, m] can be further processed in any particular manner, e.g. by applying the second stage of FFTs to the lines of the Range Map R′ [n, m] in order to obtain the Range-Doppler Map X[n,m], which allows, inter alia, detection of target velocities").
Regarding claim 17 the combination of Melzer and Bonta discloses
The apparatus of claim 14. Melzer discloses the radar processor configured to produce the plurality of frequency data sets from the digitized samples (Figure 3 element ADC 30; Paragraph 0015, “FIG. 5 is a timing diagram illustrating a sequence of chirps used for data acquisition in a radar sensor”; Paragraph 0044, “ As mentioned the Range Maps R[n, m], the Range-Doppler Maps X[n, m] or the radar data cubes may be used as input data for various signal processing techniques to detect radar targets in the surrounding (field of view) of the radar sensor”). The combination of Melzer and Bonta does not disclose producing data sets by applying a Short-Time Fourier Transform (STTF) to the digitized samples to produce the plurality of frequency data sets, each of the plurality of frequency data sets comprising samples in a time domain and a frequency domain.
Corbett discloses
Applying a Short-Time Fourier Transform (STTF) to the digitized samples to produce the plurality of frequency data sets, each of the plurality of frequency data sets comprising samples in a time domain and a frequency domain (Paragraph 0033, "In one implementation, the radar interference mitigation module 200 of FIG. 2 refers to a technique, method, or process flow that uses a short-time Fourier transform (STFT) to detect and repair interference in FMCW waveforms."; Paragraph 0051, "Next, a reverse time-frequency transform may be performed on the repaired time-frequency signal. FIG. 10 shows an example repaired signal 1000 in time domain, where the repaired T-F representation is transformed back to the time domain using the inverse T-F transform (e.g., in this case, inverse STFT)").
Melzer and Corbett are analogous art as they both concern radar interference mitigation. Melzer discloses performing a FFT on the chirps but not a STFT. It would be advantageous to use a STFT method instead of/in addition to a FFT since a STFT analysis can be superior at tracking moving or transient targets. Tracking moving/transient targets is of particular concern in a driving environment. Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Corbett to use an STFT analysis to improve the tracking/recognition of moving or transient targets.
Claims 9, 10, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Melzer (US20190113600A1) in view of Bonta (US 5245347 A) further in view of Meissner (US 11693085 B2).
Regarding claim 9 the combination of Melzer and Bonta discloses
The method of claim 1 including the radar processor. Melzer discloses the plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets (Paragraph 0069, "Finally, the Range/Doppler Map X[n, m] may be calculated from the Range Map or the smoothed Range Map (step S 3 ), and the target detection (e.g. detection of distance, speed, angle) may be performed based on the Range/Doppler Map (step S 4 ). The results of the interference detection (Step S 2 ′) may be used for the target detection, e.g. to assess the reliability of the target detection and the related position (distance and angle) and speed measurements). Melzer does not disclose wherein recovering the selected portions comprises recovering samples of the plurality of modified frequency data that were suppressed during suppressing the samples in the plurality of frequency data sets based on the threshold.
Bonta discloses
The plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets based on the threshold (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A ").
Melzer discloses suppressing interference to produce a modified dataset but not with a threshold based on magnitude. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Additionally, with the removal and fill process of Bonta, Melzer can retain local variations that a smoothing function may erase. Leading to higher quality data where there is data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold instead of a smoothing function to ease the computational load on the radar device and have higher quality data.
Meissner discloses
Recovering samples of the plurality of modified frequency data that was suppressed (Column 13 lines 11-17, "Since both the absolute value spectrum |Y*.sub.1[k]| (cf. equation 9) and the phase spectrum arg{Y.sub.I*[k]} (cf. equation 10) of the interference signal component y.sub.I*[n] have been determined, the interference signal component can be eliminated from the complex radar signal y*[n], which after all includes radar echoes and interference signals, by means of subtraction (cancelling out)."; Claim 18, "The method as recited in claim 17, wherein closing each gap in the first spectrum comprises interpolating the first spectrum that has the spectral lines removed therefrom").
Melzer and Meissner are analogous art as they both concern radar interference mitigation. Melzer discloses recognizing targets in radar data but not recovering or interpolating incomplete target data. In the scenario of an over-subtraction, it is possible to have gaps in target data, but it is also possible to have gaps in target data due to environmental obstacles. Regardless, it would be advantageous for the device to recover these gaps with interpolation to mitigate the negative effects of the missing data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Meissner to include the method of recovering missing data to completely understand the environment and potential hazards of a vehicle.
Regarding claim 10 the combination of Melzer, Bonta and Meissner discloses
The method of claim 9 including a radar processor. The combination of Melzer and Bonta does not disclose wherein the recovering of samples in the plurality of modified frequency data sets comprises utilizing an interpolation algorithm to identify gaps in the plurality of frequency data sets associated with the plurality of radar chirp reflections based on the transmitted radar signal reflecting from the one or more targets.
Meissner discloses
Wherein the recovering of samples in the plurality of modified frequency data sets comprises utilizing an interpolation algorithm to identify gaps in the plurality of frequency data sets associated with the plurality of radar chirp reflections based on the transmitted radar signal reflecting from the one or more targets (Column 13 lines 11-17, "Since both the absolute value spectrum |Y*.sub.1[k]| (cf. equation 9) and the phase spectrum arg{Y.sub.I*[k]} (cf. equation 10) of the interference signal component y.sub.I*[n] have been determined, the interference signal component can be eliminated from the complex radar signal y*[n], which after all includes radar echoes and interference signals, by means of subtraction (cancelling out)."; Claim 18, "The method as recited in claim 17, wherein closing each gap in the first spectrum comprises interpolating the first spectrum that has the spectral lines removed therefrom").
Melzer and Meissner are analogous art as they both concern radar interference mitigation. Melzer discloses recognizing targets in radar data but not recovering or interpolating incomplete target data. In the scenario of an over-subtraction, it is possible to have gaps in target data, but it is also possible to have gaps in target data due to environmental obstacles. Regardless, it would be advantageous for the device to recover these gaps with interpolation to mitigate the negative effects of the missing data. An interpolation method is particularly advantageous in that it depends on nearby data so that the interpolated data points stay reasonable. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Meissner to include the method of recovering missing data with interpolation to understand the environment and potential hazards of a vehicle with reasonable estimations for the missing data.
Regarding claim 18 the combination of Melzer and Bonta discloses
The apparatus of claim 14 including the processor. Melzer discloses the plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets (Paragraph 0069, "Finally, the Range/Doppler Map X[n, m] may be calculated from the Range Map or the smoothed Range Map (step S 3 ), and the target detection (e.g. detection of distance, speed, angle) may be performed based on the Range/Doppler Map (step S 4 ). The results of the interference detection (Step S 2 ′) may be used for the target detection, e.g. to assess the reliability of the target detection and the related position (distance and angle) and speed measurements). Melzer does not disclose recovering samples in the plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets based on the threshold by utilizing an interpolation algorithm to identify gaps in the plurality of frequency data sets associated with the plurality of radar chirp reflections reflecting from the one or more targets.
Bonta discloses
The plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets based on the threshold (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A ").
Melzer discloses suppressing interference to produce a modified dataset but not with a threshold based on magnitude. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Additionally, with the removal and fill process of Bonta, Melzer can retain local variations that a smoothing function may erase. Leading to higher quality data where there is data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold instead of a smoothing function to ease the computational load on the radar device and have higher quality data.
Meissner discloses
Recovering samples in the plurality of modified frequency data sets that were suppressed by utilizing an interpolation algorithm to identify gaps in the plurality of frequency data sets associated with the plurality of radar chirp reflections reflecting from the one or more targets (Column 13 lines 11-17, "Since both the absolute value spectrum |Y*.sub.1[k]| (cf. equation 9) and the phase spectrum arg{Y.sub.I*[k]} (cf. equation 10) of the interference signal component y.sub.I*[n] have been determined, the interference signal component can be eliminated from the complex radar signal y*[n], which after all includes radar echoes and interference signals, by means of subtraction (cancelling out)."; Claim 18, "The method as recited in claim 17, wherein closing each gap in the first spectrum comprises interpolating the first spectrum that has the spectral lines removed therefrom").
Melzer and Meissner are analogous art as they both concern radar interference mitigation. Melzer discloses recognizing targets in radar data but not recovering or interpolating incomplete target data. In the scenario of an over-subtraction, it is possible to have gaps in target data, but it is also possible to have gaps in target data due to environmental obstacles. Regardless, it would be advantageous for the device to recover these gaps with interpolation to mitigate the negative effects of the missing data. An interpolation method is particularly advantageous in that it depends on nearby data so that the interpolated data points stay reasonable. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Meissner to include the method of recovering missing data with interpolation to understand the environment and potential hazards of a vehicle with reasonable estimations for the missing data.
Regarding claim 20 the combination of Melzer and Bonta discloses
The radar processor of claim 19 including the radar processor. Melzer discloses the plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets (Paragraph 0069, "Finally, the Range/Doppler Map X[n, m] may be calculated from the Range Map or the smoothed Range Map (step S 3 ), and the target detection (e.g. detection of distance, speed, angle) may be performed based on the Range/Doppler Map (step S 4 ). The results of the interference detection (Step S 2 ′) may be used for the target detection, e.g. to assess the reliability of the target detection and the related position (distance and angle) and speed measurements). Melzer does not disclose wherein the radar processor is configured to recover samples in the plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets based on the threshold by utilizing an interpolation algorithm to identify gaps in the plurality of frequency data sets associated with the plurality of radar chirp reflections.
Bonta discloses
The plurality of modified frequency data sets that were suppressed during the suppression of samples in the plurality of frequency data sets based on the threshold (Column 56 lines 57-60, "The first of the editing processes is a so-called "SKIRT EDITOR" designed to identify and remove those false targets introduced into the radar system 10 (FIG. 1) by repeater type jammers"; Column 57 lines 12-15, "In the contemplated skirt editing process an arbitrary threshold is established based on the magnitude of the return signals as seen by the single antenna quadrant A ").
Melzer discloses suppressing interference to produce a modified dataset but not with a threshold based on magnitude. It would be advantageous to use a magnitude based threshold instead of a smoothing function as a magnitude based threshold can be computationally easier to perform. Additionally, with the removal and fill process of Bonta, Melzer can retain local variations that a smoothing function may erase. Leading to higher quality data where there is data. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Bonta to use a magnitude based threshold instead of a smoothing function to ease the computational load on the radar device and have higher quality data.
Meissner discloses
Recovering samples in the plurality of modified frequency data sets that were suppressed by utilizing an interpolation algorithm to identify gaps in the plurality of frequency data sets associated with the plurality of radar chirp reflections (Column 13 lines 11-17, "Since both the absolute value spectrum |Y*.sub.1[k]| (cf. equation 9) and the phase spectrum arg{Y.sub.I*[k]} (cf. equation 10) of the interference signal component y.sub.I*[n] have been determined, the interference signal component can be eliminated from the complex radar signal y*[n], which after all includes radar echoes and interference signals, by means of subtraction (cancelling out)."; Claim 18, "The method as recited in claim 17, wherein closing each gap in the first spectrum comprises interpolating the first spectrum that has the spectral lines removed therefrom").
Melzer and Meissner are analogous art as they both concern radar interference mitigation. Melzer discloses recognizing targets in radar data but not recovering or interpolating incomplete target data. In the scenario of an over-subtraction, it is possible to have gaps in target data, but it is also possible to have gaps in target data due to environmental obstacles. Regardless, it would be advantageous for the device to recover these gaps with interpolation to mitigate the negative effects of the missing data. An interpolation method is particularly advantageous in that it depends on nearby data so that the interpolated data points stay reasonable. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Meissner to include the method of recovering missing data with interpolation to understand the environment and potential hazards of a vehicle with reasonable estimations for the missing data.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Melzer (US20190113600A1) in view of Bonta (US 5245347 A) further in view of Meissner (US 11693085 B2) further in view of Jiang (July 2023) [Jiang N, Du H, Ge S, Zhu J, Feng D, Wang J, Huang X. High-Resolution Azimuth Missing Data SAR Imaging Based on Sparse Representation Autofocusing. Remote Sensing. 2023; 15(13):3425. https://doi.org/10.3390/rs15133425] .
Regarding claim 11 the combination of Melzer, Bonta and Meissner discloses
The method of claim 10. The combination of Melzer, Bonta, and Meissner does not disclose wherein the interpolation algorithm comprises one of a group consisting of a Fourier Transform (FT) interpolation, an autoregressive (AR) Burg algorithm, a compressed sensing algorithm, an amplitude correction algorithm, and a phase retrieval algorithm.
Jiang discloses
Wherein the interpolation algorithm is a one of the group consisting of a Fourier Transform (FT) interpolation, an autoregressive (AR) Burg algorithm, a compressed sensing algorithm, an amplitude correction algorithm, and a phase retrieval algorithm Abstract, "Due to significant electromagnetic interference, radar interruptions, and other factors, Azimuth Missing Data (AMD) may occur in Synthetic Aperture Radar (SAR) echo, resulting in severe defocusing and even false targets. An important approach to solving this problem is to utilize Compressed Sensing (CS) methods on AMD echo to reconstruct complete echo").
Melzer and Jiang are analogous art as they both concern radar interference mitigation. Melzer discloses recognizing targets in radar data but not recovering or interpolating incomplete target data. In the scenario of an over-subtraction, it is possible to have gaps in target data, but it is also possible to have gaps in target data due to environmental obstacles. Regardless, it would be advantageous for the device to recover these gaps with interpolation to mitigate the negative effects of missing data. A compressed sensing interpolation is designed for interpolating data with few data points making it preferable for interpolating gaps. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Meissner to include the method of recovering missing data with compressed sensing interpolation to recover data when there are few data points facilitating recognizing road hazards and making reasonable estimations for the missing data.
Claims 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Melzer (US20190113600A1) in view of Bonta (US 5245347 A) further in view of Meissner (US 11693085 B2) further in view of Jiang (July 2023) [Jiang N, Du H, Ge S, Zhu J, Feng D, Wang J, Huang X. High-Resolution Azimuth Missing Data SAR Imaging Based on Sparse Representation Autofocusing. Remote Sensing. 2023; 15(13):3425. https://doi.org/10.3390/rs15133425] further in view of Regani (US 20210232235 A1).
Regarding claim 12 the combination of Melzer, Bonta, Meissner and Jiang discloses
The method of claim 11. Melzer discloses calculating a first and second set of vectors after modifying the data (Figure 11 elements S1, S2, and S3). The combination of Melzer, Bonta, Meissner, and Jiang does not disclose wherein the FT interpolation comprises identifying a first set of vectors at each sample position across the plurality of frequency data sets and identifying a second set of vectors at each sample position across the plurality of modified frequency data sets.
Regani discloses
Wherein the FT interpolation comprises identifying a first set of vectors at each sample position across the plurality of frequency data sets and identifying a second set of vectors at each sample position across the plurality of modified frequency data sets (Paragraph 0323, “At step s5: determine the approximate direction (i.e., the location using the azimuth, elevation, and range coordinates) for multiple objects (N) of interest using the N highest spatially separated power values from the two dominant power matrices saved in step s4, which includes steps s5a to s5c. At step s5a: threshold the dominant non-zero power matrix in each direction. The threshold may be computed using a three-dimensional CFAR or an adaptive threshold. At step s5b: threshold the zero-power matrix using the same approach as in s5a. At step s5c: find the location of the top N objects”; Paragraph 0324, “At step s6: estimate the locations of all the N targets in step s5 with a finer resolution, maybe using an interpolation technique. Parabolic/linear/sinc interpolation may be used in each dimension (i.e., azimuth, elevation, and range) independently or combined in multiple dimensions” where the vectors such as range are estimated before and after a threshold step).
Melzer and Regani are analogous art as they both concern radar interference mitigation. Melzer discloses recognizing targets in radar data and their vectors (such as range) before and after a suppression algorithm is applied, but does not disclose that the vectors are determined before and after applying a threshold. Melzer has a range-Doppler map before and after they apply their interference suppressing smoothing algorithm, as mentioned above using a threshold method can be easier to execute than a complex smoothing convolution. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Regani so that Melzer could clean its radar data with a computationally easier method.
Regarding claim 13 the combination of Melzer, Bonta, Meissner, Jiang and Regani discloses
The method of claim 12. The combination of Melzer, Bonta, Meissner, and Jiang does not disclose wherein the FT interpolation comprises computing a Doppler spectrum with nulling by applying a FT to the second set of vectors.
Regani discloses
Wherein the FT interpolation (Paragraph 0234, “Parabolic/linear/sinc interpolation may be used in each dimension (i.e., azimuth, elevation, and range) independently or combined in multiple dimensions”) comprises computing a Doppler spectrum with nulling by applying a FT to the second set of vectors (Paragraph 0285, “As shown, two distinct target traces can be observed, and the highest Doppler power keeps switching between the two. The Doppler power at a particular spatial bin and time depends on many factors such as the instantaneous radial velocity of the dynamic target if present, the radar cross-section, material, and location of the target. To avoid misdetection of the target of interest, N targets may be detected at each instance instead of one. These N targets are identified iteratively in the decreasing order of Doppler power by comparing the Doppler power with the CFAR threshold and by nulling the region around the previously detected targets to avoid overlap of detections” where you need a FT to get Doppler power).
Melzer and Regani are analogous art as they both concern radar interference mitigation. Melzer discloses recognizing targets in radar data, but does not disclose nulling with their Fourier transform. In a driving situation if one wanted to prioritize moving targets over stationary ones, nulling is a good technique to remove strong signals from stationary objects. Additionally, as Regani states nulling can also be used to differentiate between multiple targets. As such, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Melzer with Regani to include nulling to remove unwanted strong signals from stationary targets and/or differentiate between multiple targets.
Allowable Subject Matter
Claims 3-4 are 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.
Claim 16 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is an examiner’s statement of reasons for allowance: Claims 3 and 16 recite a limitation of setting the minimum or lowest local maxima as the threshold. The closest pertinent analogous art is Hameed 2022 which recites finding the local maxima but does not set the lowest one to the threshold. As this limitation was not found claims 3 and 16 would be allowable if not dependent on a rejected claim. As claim 4 is dependent on claim 3 claim 4 is also considered allowable if not dependent on a rejected claim.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
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/PETER DAVON DOZE/Examiner, Art Unit 3648
/RESHA DESAI/Supervisory Patent Examiner, Art Unit 3648
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