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 .
Claims 1-20 are currently pending and examined below.
Response to amendment
This is a Final Office action in response to applicant's remarks/arguments filed on 04/02/2026.
Status of the claims:
Claims 1-3, 8-9, 14-17, 19, and 20 have been amended.
Applicant’s arguments, see Remarks pages 7-9, filed on 04/02/2026, with respect to the rejection(s) of claim(s) 1-20 under 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 Therefore, the rejection has been withdrawn.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 Dumoulin et al. (US 20150037045 A1) and Bhaskaran et al. (US 20200249326 A1) necessitated by the claim amendment.
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.
Claims 1, 8-9, 14, 17, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Soren Juelsgaard (US 2020/0041622 A1; “Juelsgaard”) in view of Yang et al. (US 20180003799 A1, “Yang”) and Bhaskaran et al. (US 20200249326 A1, “Bhaskaran 326”).
Regarding claim 1, Juelsgaard teaches method in a light detection and ranging (LiDAR) system (Para 2), comprising:
receiving a first signal at a first channel and a second signal at a second channel at the LiDAR system (Figs. 2 and 4, para 14-15, 53 each channel receives its own signal);
determining an intensity of the crosstalk signal based on an intensity of the first signal (Para 15 “The light sensor also measures an intensity of received noise signals, which may be used by downstream processes to classify the noise source as either an external Lidar system or reflecting surface.”. See also, fig. 5 para 73, 75),
provided the intensity of the crosstalk signal is in a detectable range, excluding the crosstalk signal from the detection of the second signal (Fig. 6, para 80 block 615. See also, fig. 6 block 620 and para 25 “mask out information from other sensors that may be less reliable due to the noise”),
to produce a corrected second signal to extract the at least one of range or velocity information related to a target based on the corrected second signal (Figs. 4-7 Para 17 “The Lidar system also includes circuitry to measure the time of flight (ToF), which is used to determine the distance of the Lidar unit to the detected object”. See also, para 82-84).
Juelsgaard fails to explicitly teach determining a frequency of a crosstalk signal in a detection of the second signal based on the first signal,
wherein the crosstalk signal is based on a proximity of the first channel to the second channel in the LiDAR system.
However, Yang teaches this missing feature by explicitly operating in the frequency domain to identify and cancel interference components in received signals. Yang discloses that “The signal processing unit cancels frequency interference from a reception signal,” and that interference cancellation is performed by identifying frequency components associated with interference in the received signal and removing those components prior to detection (Figs. 11, 12 (S20), para 1, 68 and claim 1). Yang further illustrates cancellation of interference within frequency bands corresponding to interference peaks during signal processing (see, e.g., FIGS. 2–7).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to apply Yang’s frequency-domain interference determination and cancellation to Juelsgaard’s LiDAR crosstalk mitigation system in order to identify the frequency of the detected crosstalk signal based on another received signal and exclude that frequency component from the affected channel, because both references address removing interference from received sensing signals and operate on received waveforms prior to detection.
Juelsgaard, in view of Yang, still fails to explicitly teach wherein the crosstalk signal is based on a proximity of the first channel to the second channel in the LiDAR system.
However, Bhaskaran 326 discloses a multi-channel LiDAR system in which a strong reflection in a first channel causes cross-channel noise / optical leakage into a nearby or adjacent second channel, such that light from the first channel is detected at the second channel and produces a false return / false detection. Bhaskaran 326 teaches that this cross-channel noise occurs between nearby channels, including where the sensors are next to each other physically and/or within a threshold physical distance of each other, and further teaches adjacent channels separated by azimuth and activated substantially simultaneously (Figs. 1A-1B;Para 20-24; Para 34-35 and 49; see also claim 2, para 97, reciting that identifying the false positive return is based at least in part on determining that the first sensor is within a threshold physical distance of the second sensor.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to further apply Bhaskaran 326’s teaching to Juelsgaard’s LiDAR crosstalk mitigation system, in order to more reliably determine when interference observed in a second channel is attributable to leakage from a nearby first channel rather than a true target return. Doing so would have predictably improved false-return rejection, reduced ghost detections, and improved accuracy of target ranging and/or velocity extraction.
Regarding claim 8, Juelsgaard, in view of Yang and Bhaskaran 326, teaches the method of claim 1, wherein the first signal and the second signal are optical signals (Juelsgaard, Para 53 “The light emitter emits a light pulse and the receiver detects reflected light from objects in the environment.”),
the method further comprising determining the crosstalk signal includes the first signal from a first direction within a field of view of the LiDAR system (Juelsgaard, para 21, 32, 39” the noise processing system …may use the noise data to determine a direction of a noise source relative to the AV system …”),
wherein the first channel is associated with the first direction, and the second channel is associated with a second direction (Juelsgaard, Fig. 2 para 53-54. See also, para 3”an array of channels may be used to expand the field of view of the Lidar unit”. Different channels correspond to different angular directions.).
Regarding claim 9, Juelsgaard, in view of Yang and Bhaskaran 326, teaches the method of claim 8, further comprising, for the second direction, determining the first direction in which the crosstalk signal is received, wherein the determining the frequency of the crosstalk signal in the detection of the second signal based on the first signal comprises determining the frequency of the crosstalk signal in the detection of the second signal based on the first signal in a current frame or a previous frame (Juelsgaard, Para 23, 84, “The vehicle computing system associates the second noise signal with the noise source based on a predicted location of the noise source.” Association across frames implies use of current and prior frames.).
Regarding claim 14, Juelsgaard teaches a light detection and ranging (LiDAR) system, comprising: a processor; and a memory to store instructions (Para 21, 50, claim 1. “The vehicle computing system (including a memory) processes noise data received from the Lidar unit.”). The rest of the claim will be rejected the same way as claim 1.
Claim 17 is system claims corresponding to method claim 8. It is rejected for the same reasons.
Regarding claim 20, Juelsgaard teaches a light detection and ranging (LiDAR) system, comprising: an optical source to emit an optical beam; one or more optical receivers to receive a first signal at a first channel and a second signal at a second channel (at least Fig. 2, para 53 The light emitter emits a light pulse and the receiver detects reflected light and each channel receives its own signal”); a circuitry (at least Para 17, 53, “The Lidar unit includes circuitry to measure the time of flight.” ); and a memory (para 50. See also, para 92) to store instructions. The rest of the claim will be rejected the same way as claim 1.
Claims 2-6, 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Juelsgaard in view of Yang, Bhaskaran 326 and Hall et al. (US 10739444 B2, “Hall”).
Regarding claim 2, Juelsgaard, in view of Yang and Bhaskaran 326, fails to explicitly teach but Hall teaches the method of claim 1, wherein the first signal and the second signal are electronic signals (col 5: lines 16-19 and lines 49-51. Hall expressly treats the received channel outputs as analog (electronic) signals and performs ADC conversion, so the “first signal” and “second signal” correspond to electronic outputs of the respective analog receive channels.),
the method further comprising determining the crosstalk signal in the detection of the second signal includes a portion of the first signal coupled into the second channel (Col 5: lines 7-11 and lines 53-54. Because Hall electrically couples the receive-channel outputs at a shared node and sums them, the observed signal at the coupled node (and at the ADC input) necessarily includes a portion of the signal from another receive channel. That is exactly the claimed concept that the “crosstalk signal … includes a portion of the first signal coupled into the second channel.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate Hall’s known electronic receive-channel coupling behavior into Juelsgaard’s LiDAR system, because both references address multi-channel LiDAR signal acquisition and processing, and electronic channel coupling is a known mechanism by which inter-channel crosstalk arises and can be identified and mitigated in LiDAR receiver electronics.
Regarding claim 3, Juelsgaard, in view of Yang, Bhaskaran 326 and Hall, teaches the method of claim 2, further comprising determining a source of the crosstalk signal being the first signal based on a crosstalk model (As discussed with respect to Claim 2, Hall (Col 5: lines 7-11 and lines 53-54) teaches an electronic crosstalk model in which the outputs of multiple LiDAR receive channels are electrically coupled and effectively summed at a shared node prior to analog-to-digital conversion. In such an architecture, interference observed in a detected signal is inherently attributable to signal content originating from another receive channel, thereby determining that the source of the crosstalk signal is the first signal based on the electronic crosstalk model defined by the channel coupling.), and
wherein the determining the frequency of the crosstalk signal in the detection of the second signal based on the first signal comprises determining the frequency of the crosstalk signal in the detection of the second signal being a frequency of the first signal (Yang (Figs. 11, 12 (S20), para 1, 68 and claim 1) teaching frequency-domain interference processing in which interference is identified and cancelled based on its frequency characteristics. In particular, Yang teaches cancelling frequency interference from a reception signal, which necessarily involves determining the interference frequency corresponding to the signal causing the interference. Because the interference frequency corresponds to the frequency of the interfering signal, Yang teaches determining the frequency of the crosstalk signal to be the frequency of the first signal. In summary, frequency-domain interference cancellation necessarily determines the frequency of interference to be the same as the frequency of the signal causing the interference.).
Regarding claim 4, Juelsgaard, in view of Yang, Bhaskaran 326 and Hall, teaches the method of claim 2, wherein the determining the intensity of the crosstalk signal based on the intensity of the first signal comprises determining the intensity of the crosstalk signal based on the intensity of the first signal and a coupling coefficient (As discussed with respect to Claims 2 and 3, Hall teaches an electronic crosstalk model in which outputs of multiple LiDAR receive channels are electrically coupled and effectively summed at a shared node prior to analog-to-digital conversion, such that the detected electronic signal includes coupled contributions from other channels. In such electronically coupled receiver architectures, the magnitude of the coupled (crosstalk) component is determined by a coupling coefficient associated with the electrical coupling path.),
the coupling coefficient being a function of the frequency of the first signal (Yang further teaches frequency-dependent interference processing in which cancellation of interference is performed based on the frequency characteristics of the interfering signal. In particular, Yang discloses interference cancellation using frequency-domain processing elements (e.g., envelope comparison and frequency-selective cancellation (Figs. 11-12, para 68, 72)), which operate on the received signal at specific interference frequencies. Because electrical coupling behavior in receiver circuits is frequency-dependent, applying Yang’s frequency-domain interference processing to Hall’s electronically coupled multi-channel LiDAR receiver necessarily results in determining the intensity of the crosstalk signal based on the intensity of the first signal and a coupling coefficient that varies as a function of frequency, as recited in Claim 4.).
Regarding claim 5, Juelsgaard, in view of Yang, Bhaskaran 326 and Hall, teaches the method of claim 2, wherein the excluding the crosstalk signal from the detection of the second signal comprises, in a peak selection process (As discussed with respect to Claims 2–4, Hall teaches a multi-channel LiDAR receiver in which electronic signals from different receive channels are electrically coupled, such that interference components may be present in detected signals.),
discarding a portion of the detection of the second signal in a frequency band around the frequency of the crosstalk signal with a predetermined bandwidth (Yang further teaches frequency-domain processing of received signals in which interference is identified and cancelled during a peak selection process. In particular, Yang teaches identifying frequency-domain interference and cancelling the interference component prior to final detection, which necessarily involves discarding detected signal components in a frequency region associated with the interference.).
Regarding claim 6, Juelsgaard, in view of Yang, Bhaskaran 326 and Hall, teaches the method of claim 2, wherein the excluding the crosstalk signal from the detection of the second signal comprises, in a peak selection process, applying a threshold of signal to noise ratio (SNR) to a portion of the detection of the second signal in a frequency band around the frequency of the crosstalk signal higher than that to other portion of the detection of the second signal, wherein the threshold of SNR is determined based on the intensity of the crosstalk signal (As discussed above, Yang teaches frequency-domain interference handling in which detected signal values are compared against threshold values in order to classify and suppress interference components. Once an interference frequency has been identified, it is routine in frequency-domain peak selection to apply a stricter detection criterion to frequency regions associated with known interference than to other frequency regions. Yang further teaches evaluating the magnitude of the interference during detection, and Hall teaches that the magnitude of coupled interference depends on the intensity of the source signal.
Accordingly, it would have been obvious to apply a higher signal-to-noise ratio threshold to the portion of the detected signal within the frequency band around the crosstalk frequency than to other portions of the detected signal, and to determine that threshold based on the intensity of the crosstalk signal, because adaptive thresholding based on interference strength is a known and predictable technique for suppressing interference in multi-channel receiver systems.).
Claim 15 is system claims corresponding to method claim 2. It is rejected for the same reasons.
Claim 16 is a system claim corresponding to method claims 5-6. It is rejected for the same reasons.
Claims 7,16 are rejected under 35 U.S.C. 103 as being unpatentable over Juelsgaard in view of Yang, Bhaskaran 326, Hall and Bhaskaran et al. (US 20200309957 A1, “Bhaskaran”).
Regarding claim 7, Juelsgaard, in view of Yang and Hall, teaches the method of claim 2, wherein the excluding the crosstalk signal from the detection of the second signal (Juelsgaard teaches mitigating interference that affects LiDAR detections. In particular, Juelsgaard describes identifying noise/interference affecting LiDAR returns and preventing such interference from contributing to final detections (e.g., by masking or ignoring affected detections, para 25). This teaches excluding crosstalk-affected detections from further use.).
Juelsgaard, in view of Yang and Hall fails to explicitly teach but Bhaskaran teaches that the excluding the crosstalk signal from the detection of the second signal comprises, at a point cloud processing (Bhaskaran explicitly teaches post-detection processing at the point-cloud/perception stage, where individual LiDAR detections are evaluated and handled as points, at least figs. 1, 7-8 abstract, para 15, 56 ,“Particulate matter and other noise sources may cause one or more sensor types to generate false positive detections, and the system determines whether to identify a detection as a false positive.”),
discarding a portion of the detection of the second signal (Fig. 8, para 73, 126-129, “Based on the determined confidence score, the system may remove or ignore the false positive detection.” This corresponds to discarding a portion of detections.).
It would have been obvious to one of ordinary skill in the art to apply the point-cloud-level false-detection removal of Bhaskaran to Juelsgaard’s LiDAR system, thereby discarding only those point-cloud detections associated with crosstalk and having characteristics consistent with predicted interference intensity. Such a combination represents a routine and predictable application of known frequency-domain interference identification followed by post-detection point-cloud filtering to improve LiDAR perception accuracy.
Juelsgaard, in view of Yang, Hall and Bhaskaran in a frequency band around the frequency of the crosstalk signal (Yang teaches identifying and cancelling interference in the frequency domain, i.e., interference localized to particular frequency components of the received signal (Figs. 11, 12 (S20), para 1, 68 and claim 1) with an intensity similar to a predicted intensity of the crosstalk signal (Yang further teaches evaluating the magnitude (envelope) of the interference signal during frequency-domain processing, thereby characterizing the interference intensity (Figs. 11-12, para 68, 72), while Bhaskaran teaches using signal-related measures (e.g., confidence scores derived from signal characteristics such as intensity) to decide whether to remove detections).
Claim 16 is a system claim corresponding to method claim 7. It is rejected for the same reasons.
Claims 10-13, 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Juelsgaard in view of Yang, Bhaskaran 326, Crouch et al. (US 20190361122 A1, “Crouch”) and Going et al. (US 11662444 B1, “Going”).
Regarding claim 10, Juelsgaard, in view of Yang and Bhaskaran 326, fails to explicitly teach but Crouch teaches the method of claim 8, wherein the first direction is associated with a first Doppler shift, wherein the second direction is associated with a second Doppler shift (Para 7, 79 and claim 1, “Determining a Doppler frequency shift based on a peak in a cross spectrum. ”Crouch’s FMCW LiDAR processes returns per measurement channel / look direction, such that each return has an associated Doppler frequency shift corresponding to the relative velocity along that direction.),
the method further comprising determining a Doppler offset based on a difference between the first Doppler shift and the second Doppler shift (abstract, para 7 and claim 1. Crouch teaches determining Doppler frequency shifts for LiDAR returns. Once Doppler shifts associated with different returns are known, determining a Doppler offset as a difference between such Doppler shifts represents a straightforward arithmetic operation on known values and would have been obvious to one of ordinary skill in the art.).
Juelsgaard teaches identifying signals received from different directions in a LiDAR system in order to characterize and mitigate interference originating from particular directions. Crouch teaches determining Doppler frequency shifts for LiDAR returns to characterize relative motion of sources producing those returns. It would have been obvious to apply Crouch’s Doppler-shift determination to Juelsgaard’s directionally distinct signals so that differences in relative motion between signals received from different directions can be quantified, and to determine a Doppler offset as a difference between Doppler shifts in order to distinguish crosstalk or interference signals from valid target returns based on their differing motion characteristics.
Juelsgaard, in view of Yang and Bhaskaran 326 and Crouch, also fails to explicitly teach but Going teaches determining a shifted crosstalk frequency by adding the Doppler offset to the frequency of the crosstalk signal (Col 7: lines 29-35, “The received signal includes a frequency offset (Doppler shift), which is used to correct the frequency of the return signal.”).
Juelsgaard teaches identifying and characterizing crosstalk or interference signals received from particular directions in a LiDAR system in order to mitigate their impact on detection results. Going teaches that Doppler shift constitutes a frequency offset and that such offset is applied to correct or adjust the frequency of a received signal in Doppler-based LiDAR processing. It would have been obvious to apply Going’s Doppler-based frequency adjustment to Juelsgaard’s identified crosstalk signal so that the frequency at which the crosstalk appears in the Doppler-affected detection domain can be accurately determined, thereby enabling effective exclusion or suppression of the crosstalk signal under relative motion conditions.
Regarding claim 11, Juelsgaard, in view of Yang, Bhaskaran 326, Crouch and Going teaches the method of claim 10, wherein the excluding the crosstalk signal from the detection of the second signal comprises, in a peak selection process, discarding a portion of the detection of the second signal in a frequency band around the shifted crosstalk frequency with a predetermined bandwidth (Crouch, teaches detecting LiDAR returns using frequency-domain processing after Doppler correction, wherein Doppler shifts are identified as peaks in a cross spectrum. Crouch further teaches computing a cross spectrum using Fourier transforms and performing detection based on spectral components in the Doppler-corrected frequency domain (Para 80, 84).
Once a crosstalk frequency (including a Doppler-shifted crosstalk frequency as determined in Claim 10) is identified in such a frequency-domain detection framework, excluding detections within a frequency band around that frequency using a predetermined bandwidth would have been obvious to one of ordinary skill in the art. Such exclusion represents a known and appropriate interference-suppression technique applied to spectral detection, as removing spectral components in a defined frequency region prevents interference peaks from being selected as valid detections while preserving detection of other frequency components corresponding to actual targets.).
Regarding claim 12, Juelsgaard, in view of Yang, Bhaskaran 326, Crouch and Going teaches the method of claim 10, wherein the excluding the crosstalk signal from the detection of the second signal comprises, in a peak selection process, applying a threshold of SNR to a portion of the detection of the second signal in a frequency band around the shifted crosstalk frequency higher than that to other portion of the detection of the second signal (Because Crouch (Para 7, 80, 84 and claim 1) performs detection by selecting peaks in a Doppler-corrected frequency spectrum, applying different acceptance criteria to different portions of the spectrum is inherent to peak selection. Once a frequency band associated with crosstalk is identified, applying a higher SNR threshold in that band than in other portions of the spectrum would have been obvious, as it allows suppression of interference-related peaks while preserving sensitivity to valid target peaks outside the interference band.),
wherein the threshold of SNR is determined based on the intensity of the crosstalk signal (As discussed with respect to Claims 10–12, Crouch teaches detecting LiDAR returns using Doppler-corrected frequency-domain processing, wherein detections are identified as spectral peaks and detection decisions are based on the magnitude of frequency-domain components (e.g., identifying Doppler shifts as peaks in a cross spectrum). Because the intensity of spectral components corresponding to crosstalk is measurable in such a frequency-domain detection framework, it would have been obvious to one of ordinary skill in the art to determine an SNR threshold based on the intensity of the crosstalk signal, so as to suppress interference-related peaks while preserving detection of valid target signals.).
Regarding claim 13, Juelsgaard, in view of Yang, Bhaskaran 326, Crouch and Going teaches the method of claim 10, wherein the excluding the crosstalk signal from the detection of the second signal comprises, at a point cloud processing (Crouch, para 88, claim 9, “Generating a point cloud of Doppler corrected positions.”),
discarding a portion of the detection of the second signal in a frequency band around the shifted crosstalk frequency with an intensity similar to a predicted intensity of the crosstalk signal (Crouch teaches Doppler-corrected frequency-domain detection in which detections correspond to spectral peaks (para 80, 84) and detection decisions are based on signal magnitude (Para 46-47). Once crosstalk frequency and intensity characteristics are known, discarding detections originating from frequency components having intensities consistent with crosstalk represents an obvious modification to prevent interference-derived detections from propagating into the point cloud.).
Claim 18 is system claims corresponding to method claim 10. It is rejected for the same reasons.
Claim 19 is a system claim corresponding to method claims 11-13. It is rejected for the same reasons.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
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/JEMPSON NOEL/Examiner, Art Unit 3645
/YUQING XIAO/Supervisory Patent Examiner, Art Unit 3645
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