Prosecution Insights
Last updated: April 19, 2026
Application No. 17/591,393

TECHNIQUES FOR SUBBAND PROCESSING FOR A LIDAR SYSTEM

Non-Final OA §103
Filed
Feb 02, 2022
Examiner
QUIGLEY, KYLE ROBERT
Art Unit
2857
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Aeva, Inc.
OA Round
3 (Non-Final)
54%
Grant Probability
Moderate
3-4
OA Rounds
3y 10m
To Grant
87%
With Interview

Examiner Intelligence

Grants 54% of resolved cases
54%
Career Allow Rate
254 granted / 466 resolved
-13.5% vs TC avg
Strong +33% interview lift
Without
With
+32.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 10m
Avg Prosecution
72 currently pending
Career history
538
Total Applications
across all art units

Statute-Specific Performance

§101
20.7%
-19.3% vs TC avg
§103
43.7%
+3.7% vs TC avg
§102
13.8%
-26.2% vs TC avg
§112
19.9%
-20.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 466 resolved cases

Office Action

§103
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 . The rejections from the Office Action of 9/20/2024 are hereby withdrawn. New grounds for rejection are presented below. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 1/21/2026 has been entered. 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. Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Roos et al. (US 20200241139 A1)[hereinafter “Roos”], Lin (US 20080240282 A1), and Vis et al. (US 5806025 A)[hereinafter “Vis”]. Regarding Claims 1, 8, and 15, Roos discloses a frequency modulated continuous wave (FMCW) LIDAR system (and corresponding method)[See Fig. 1 and Paragraph [0002] – “Examples described herein relate to the field of optical distance measurement, including light detection and ranging (LiDAR) systems and methods, such as frequency-modulated continuous-wave (FMCW) LiDAR systems and methods, or and length metrology.”], comprising: a memory; and a processor, operatively coupled to the memory [Paragraph [0031] – “The digital signal may be processed by processor 118 to determine one or more properties of the object 110 (e.g., distance to the target).”], to: generate a plurality of frequency subbands in a time domain [See Fig. 4A and Paragraph [0056], particularly – “This interference signal may be segmented into smaller-duration interference signal segments with durations T.sub.0 (e.g., each having a smaller bandwidth B.sub.0, which bandwidth may correspond to the desired range resolution, and is maintained for this example, compared to FIG. 3). These smaller temporal chirp segments may each be processed (e.g., by processor 118 of FIG. 1) to determine a range to an object.”] based on an electrical signal from one or more optical detectors [Paragraph [0031] – “The transceiver 108 may direct the transmit beam toward object 110. The transmit beam may be reflected from object 110. Reflection as used herein may refer to laser beams that are reflected and/or scattered from an object. The reflected laser beam (Rx), which may be referred to as a range return, may be received by transceiver 108. The transceiver 108 may provide the reflected laser beam to the circulator 106. The circulator 106 may provide the reflected laser beam to the combiner 112. The combiner 112 may combine the local oscillator beam and the reflected laser beam to provide a combined beam, which may be directed onto a detector 114.”]; filter the plurality of frequency subbands in the time domain to obtain a subset of the plurality of frequency subbands [Paragraph [0058] – “The processing of temporal segments may occur in a variety of ways. In some examples, a processor may not process all segments.”]; convert the subset of the plurality of frequency subbands in the time domain to one or more subband signals in a frequency domain [Paragraph [0057] – “The processing of each segment of temporal duration T.sub.0 may include a transform (e.g., a fast Fourier Transform, Hilbert Transform) and/or any other processing of the interference signal or segment thereof.”]; and detect signal peaks in the one or more subband signals in the frequency domain [Paragraph [0048] – “A Fourier transform of the interference signal (which may be performed, e.g., by processor 118 of FIG. 1 and/or other circuitry), may provide a frequency of the beat note, which may be referred to as a beat frequency. FIG. 2B illustrates an example plot of signal strength vs. frequency for a Fourier transform of an interference signal. The peak shown in FIG. 2B may be at the beat frequency.”Paragraph [0055] – “One or more processors, such as the processor 118 of FIG. 1, may determine a distance to an object for one or more temporal segment of the interference signal. A distance to an object may be determined by any of a variety of methods including those involving determining a beat note frequency corresponding to a certain temporal segment of an interference signal, in which a distance to an object may be determined with knowledge of the chirp rate. A frequency may be determined by any method including, but not limited to curve fitting, peak finding, fringe counting, and/or slope determination (e.g. for Hilbert transforms).”Paragraph [0058] – “In some examples, the processing of segments may result in more than one determination of a range to an object. For example, one or more processors (e.g., processor 118 of FIG. 1) may determine a range to an object based on each segment.”]; and determine range and velocity of one or more targets [Paragraph [0048] – “The peak shown in FIG. 2B may be at the beat frequency. The beat frequency may be given by f.sub.heat=κτ, where κ is the chirp rate and τ may be linearly proportional to the distance of the object (e.g. τ=2R/c, where R is the distance to the object and c is the speed of light). In certain examples, the processor 118 may determine a distance to an object by solving for R and using known or measured values of a chirp rate, the speed of light, and a beat frequency of an interference signal described herein.”] based on the signal peaks in the one or more subband signals in the frequency domain [Paragraph [0044] – “Examples of systems described herein may accordingly be used to determine one or more properties of an object. … Any of a variety of properties may be determined (e.g., measured) using systems described herein, including distance (e.g., range), velocity and or acceleration.”Paragraph [0063] – “The average beat note f.sub.beat may, with a known chirp rate, be used to determine a corrected distance as previously described or using other methods. Processing of multiple temporal segments to determine an object velocity may be performed by differencing the beat note frequency from an interference signal segment from an up chirp with the beat note frequency from an interference signal segment from a down chirp.”See Paragraph [0070].]. Roos fails to disclose filtering the plurality of frequency subbands in the time domain based on one or more characteristics of each of the plurality of frequency subbands to obtain a subset of the plurality of frequency subbands based on at least two separate signal thresholds, wherein at least one of the signal thresholds is an energy threshold. However, Lin discloses evaluating frequency subbands based on signal characteristics [Paragraph [0029] – “At step 210, a subband energy can be estimated to produce an estimated channel energy over a pre-specified time window. A subband energy is an energy of the input signal within a frequency band.”] and through the use of multiple signal thresholds to evaluate the subbands for the presence of an actual signal relative to background noise [See Figs. 8-10 and Paragraph [0051].], wherein at least one of the signal thresholds is an energy threshold [Paragraph [0051] – “The noise update decision unit 130 declares a presence of noise and requests a noise channel estimate update if … c) the peak-to-peak energy difference is less than a predetermined peak-to-peak threshold (446).”]. It would have been obvious to choose which frequency segments to use through use of such thresholds in order to choose subbands that have a relatively low amount of noise. This would have made the range-finding process more accurate. Roos and Lin fail to disclose that at least one of the signal thresholds is a signal-to-noise ratio (SNR) threshold. However, Vis discloses the use of such a threshold for filtering subbands [Column 6 lines 15-19 – “Thus, using quality indicators (e.g., SNR), subband filters for subband speech processing are adaptively chosen. If the quality indicator is below a threshold for a subband channel, the channel's contribution to the reconstruction is thrown out in a bias-variance trade-off for reducing overall MSE.”]. It would have been obvious to choose which frequency segments to use through use of such a threshold in order to choose subbands that have a relatively low amount of noise. This would have made the range-finding process more accurate. Regarding Claim 15, Roos discloses an optical source to transmit an optical beam toward a target [Paragraph [0031] – “The beam splitter 104 may split the laser beam into a transmit (Tx) beam and a local oscillator (LO) beam. The circulator 106 may receive the transmit beam and provide to transceiver 108. The transceiver 108 may direct the transmit beam toward object 110.”]; and an optical receiver to receive a return beam from the target comprising a reflection of the optical beam from the target, the optical receiver to produce an electrical signal in a time domain by combining the return beam with a local oscillator [Paragraph [0031] – “The transmit beam may be reflected from object 110. Reflection as used herein may refer to laser beams that are reflected and/or scattered from an object. The reflected laser beam (Rx), which may be referred to as a range return, may be received by transceiver 108. The transceiver 108 may provide the reflected laser beam to the circulator 106. The circulator 106 may provide the reflected laser beam to the combiner 112. The combiner 112 may combine the local oscillator beam and the reflected laser beam to provide a combined beam, which may be directed onto a detector 114.” Fig. 2A is in the time domain.]. Regarding Claims 2, 9, and 16, Roos discloses that the processor is further to: resample and combine the plurality of frequency subbands in the time domain into a combined time domain signal [Paragraph [0058] – “In some examples, multiple processed or unprocessed segments may be combined (e.g., averaged, summed, or differenced) by one or more processors (e.g., by processor 118 of FIG. 1). … Coherent combining may, for some examples, include summing interference signals at any stage of processing, in the time domain or frequency domain[.]”See also the combination shown in Fig. 4B.]. Regarding Claims 3, 10, and 17, the combination would disclose that to filter the plurality of frequency subbands, the processor is to: select the subset of frequency subbands in the time domain based on a set of subband selection criteria [Selection of the subbands of Roos using the thresholds of Lin]. Regarding Claims 4, 11, and 18, the combination would disclose selecting a subset of the one or more subband signals in the frequency domain [Selection of the subbands of Roos using the frequency domain thresholds of Lin], wherein the signal peaks are detected from the subset of the one or more subband signals in the frequency domain [Paragraph [0055] – “One or more processors, such as the processor 118 of FIG. 1, may determine a distance to an object for one or more temporal segment of the interference signal. A distance to an object may be determined by any of a variety of methods including those involving determining a beat note frequency corresponding to a certain temporal segment of an interference signal, in which a distance to an object may be determined with knowledge of the chirp rate. A frequency may be determined by any method including, but not limited to curve fitting, peak finding, fringe counting, and/or slope determination (e.g. for Hilbert transforms).”Paragraph [0057] – “The processing of each segment of temporal duration T.sub.0 may include a transform (e.g., a fast Fourier Transform, Hilbert Transform) and/or any other processing of the interference signal or segment thereof.”]. Regarding Claims 5, 12, and 19, the combination would disclose that the subset of the one or more subband signals in the frequency domain is selected based on at least one of characteristics of the electrical signal, characteristics of the plurality of frequency subbands in the time domain, characteristics of the one or more subband signals in the frequency domain, and characteristics of a scene in a field of view of the LIDAR system [Selection of the subbands of Roos using the thresholds of Lin. The recited characteristics all define the measurement data of Roos; performing subband selection using the thresholds of Lin would thus read on the evaluation being based on the recited characteristics.]. Regarding Claims 6, 13, and 20, the combination would disclose that the one or more characteristics used to filter the plurality of frequency subbands in the time domain comprise at least one of: a total energy in a subband [Paragraph [0051] of Lin – “a total estimated channel energy is greater than a predetermined noise floor (442)”], a signal to noise ratio in the subband [Paragraph [0051] of Lin – “b) the spectrum deviation is less than a predetermined variance threshold (444), and c) the peak-to-peak energy difference is less than a predetermined peak-to-peak threshold (446).”], a number of zero crossings, a number of clipped samples, energy variation over time [Paragraph [0029] of Lin – “At step 210, a subband energy can be estimated to produce an estimated channel energy over a pre-specified time window.”], an azimuth angle of a scan associated with the subband, an elevation angle of the scan associated with the subband, a relative velocity of a detected target, scene characteristics, detection of objects in a previous LIDAR time segment, and a maximum number of allowed subbands [Paragraph [0055] of Roos – “Any number of temporal segments may be used including 2, 3, 4, 5, 6, 7, 8, 9, 10, or another number of temporal segments.”]. Regarding Claims 7 and 14, the combination would disclose that the signal peaks comprise at least one of a peak energy [Paragraph [0048] of Roos – “A Fourier transform of the interference signal (which may be performed, e.g., by processor 118 of FIG. 1 and/or other circuitry), may provide a frequency of the beat note, which may be referred to as a beat frequency. FIG. 2B illustrates an example plot of signal strength vs. frequency for a Fourier transform of an interference signal. The peak shown in FIG. 2B may be at the beat frequency.”Paragraph [0055] of Roos – “One or more processors, such as the processor 118 of FIG. 1, may determine a distance to an object for one or more temporal segment of the interference signal. A distance to an object may be determined by any of a variety of methods including those involving determining a beat note frequency corresponding to a certain temporal segment of an interference signal, in which a distance to an object may be determined with knowledge of the chirp rate. A frequency may be determined by any method including, but not limited to curve fitting, peak finding, fringe counting, and/or slope determination (e.g. for Hilbert transforms).”] or a peak signal to noise ratio within the frequency domain [Paragraph [0051] of Lin – “c) the peak-to-peak energy difference is less than a predetermined peak-to-peak threshold (446).”]. Response to Arguments Applicant argues: PNG media_image1.png 212 787 media_image1.png Greyscale Examiner’s Response: The corresponding rejections are hereby withdrawn. Applicant argues: PNG media_image2.png 259 787 media_image2.png Greyscale Examiner’s Response: The Examiner agrees. New grounds for rejection are presented above. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: US 20150177367 A1 – SINGLE LASER LIDAR SYSTEM US 20160123718 A1 – ACCURATE CHIRPED SYNTHETIC WAVELENGTH INTERFEROMETER US 20200278432 A1 – DIGITIZATION SYSTEMS AND TECHNIQUES AND EXAMPLES OF USE IN FMCW LIDAR METHODS AND APPARATUSES US 20150378187 A1 – SOLID STATE LIDAR CIRCUIT US 20140334830 A1 – System And Method For Generating A Frequency Modulated Linear Laser Waveform US 20160352543 A1 – CONFIGURABLE ARCHITECTURE FOR GENERATING A WAVEFORM US 20190310372 A1 – Method And System For Doppler Detection And Doppler Correction Of Optical Chirped Range Detection US 20200166617 A1 – LIDAR SYSTEM FOR AUTONOMOUS VEHICLE US 20080238757 A1 – System And Methods For Remote Sensing Using Double-Sideband Signals US 20200182978 A1 – LIDAR SYSTEM US 20110010400 A1 – LIDAR POINT CLOUD COMPRESSION US 20200011994 A1 – FMCW LIDAR METHODS AND APPARATUSES INCLUDING EXAMPLES HAVING FEEDBACK LOOPS US 20200363515 A1 – WAVELENGTH SELECTION IN LIDAR SYSTEMS US 20190293768 A1 – SELECTING LIDAR PULSE DETECTOR DEPENDING ON PULSE TYPE US 4086536 A – Single Sideband Transmitter Apparatus Alland et al., Interference in Automotive Radar Systems, IEEE, September 2019 Chen et al., Micro Doppler Effect in Radar, IEEE, 2006 Hwang et al., Study on the FMCW LiDAR, IEEE, October 2019 Hyun et al., Moving and Stationary Target Detection Scheme, IEEE, 2017 Ma et al., Short Range Detection Scheme based on FMCW, IEEE, August 2019 Poulton et al., Frequency-modulated Continuous-wave LIDAR, OSA, 2016 Yang et al., Distance and Velocity Measurement of Coherent Lidar, MDPI, May 2019 US 20170356944 A1 – FILTRATION THRESHOLDING US 20150142425 A1 – NOISE ADAPTIVE POST FILTERING US 20210057900 A1 – APPARATUS AND METHOD FOR ARC FAULT DETECTION BASED ON SIGNAL-TO-NOISE RATIO Any inquiry concerning this communication or earlier communications from the examiner should be directed to KYLE ROBERT QUIGLEY whose telephone number is (313)446-4879. The examiner can normally be reached 9AM-5PM EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Arleen Vazquez can be reached at (571) 272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /KYLE R QUIGLEY/Primary Examiner, Art Unit 2857
Read full office action

Prosecution Timeline

Feb 02, 2022
Application Filed
Jun 10, 2024
Non-Final Rejection — §103
Sep 13, 2024
Response Filed
Sep 19, 2024
Final Rejection — §103
Dec 18, 2024
Notice of Allowance
Feb 12, 2025
Response after Non-Final Action
Feb 15, 2025
Response after Non-Final Action
Feb 27, 2025
Response after Non-Final Action
Apr 17, 2025
Response after Non-Final Action
Apr 18, 2025
Response after Non-Final Action
Apr 21, 2025
Response after Non-Final Action
Apr 21, 2025
Response after Non-Final Action
Nov 19, 2025
Response after Non-Final Action
Jan 21, 2026
Request for Continued Examination
Jan 28, 2026
Response after Non-Final Action
Jan 29, 2026
Applicant Interview (Telephonic)
Jan 29, 2026
Examiner Interview Summary
Feb 16, 2026
Non-Final Rejection — §103
Apr 14, 2026
Examiner Interview Summary
Apr 14, 2026
Applicant Interview (Telephonic)

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Prosecution Projections

3-4
Expected OA Rounds
54%
Grant Probability
87%
With Interview (+32.7%)
3y 10m
Median Time to Grant
High
PTA Risk
Based on 466 resolved cases by this examiner. Grant probability derived from career allow rate.

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