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 .
This is the first office action on the merits and is responsive to the papers filed 08/30/2022. Claims 1-20 are currently pending and examined below.
Information Disclosure Statement
The information disclosure statement submitted by Applicant is in compliance with the provision of 37 CFR 1.97, 1.98 and MPEP § 609. It has been placed in the application file and the information referred to therein has been considered as to the merits.
Claim Objections
Claims1-3, 5, 7-8, 10, 13-14, 17 are objected to because of the following informalities:
“spacio” should be –spatio—
Appropriate correction is required.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Meissner et al. (US 20200158825 A1, “Meissner”) in view of Allen et al. (US 11150348 B2, “Allen”).
Regarding claim 1, Meissner teaches a method of interference mitigation in a LiDAR system (Para 1),
the method comprising identifying a presence or absence of interference from a non-co-located light source in a sample of incident light received by a detector in the LiDAR system (Para 24, 76, 80 and claim 15 “processor configured to: measure a variation between the first detector signal sample and the at least one second detector signal sample, and detect a presence of an interferer if the variation exceeds a predefined threshold”).
Meissner fails to explicitly teach but Allen teaches in the absence of interference, using a nominal set of reference values for one or more spacio-temporal scanning profile trajectory parameters (Fig. 5, col 9: lines 24-26, “the dashed lines represent the nominal temporal positions of a uniformly spaced train of light pulses” (uniform, nominal operation absent interference)); and
controlling one or more scanner components of the LiDAR system using the nominal set of reference values (Col 7: lines 8-13 the light pulses 210 may be substantially uniformly spaced from each other by a delay time t between adjacent pulses” (control of emission timing); and
in the presence of interference, augmenting the nominal set of reference values, resulting in an augmented set of reference values, to modify the spacio-temporal scanning profile trajectory parameters (Col 9: lines 27-29 each light pulse….is temporally shifted with respect to a corresponding nominal temporal position by an amount δt); and
controlling the one or more scanner components of the LiDAR system using the augmented set of reference values to avoid detection of and interference by the non-co-located light source (Col 9: lines 43-46, “As a result of the random shifting of the light pulses… the apparent times of flight for the train of interfering light pulses may differ from each other in a random fashion” (interference avoidance)).
It would have been obvious to one of ordinary skill in the art to combine the interference detection of Meissner with the spatio-temporal trajectory modification techniques of Allen in order to improve interference mitigation, as both references address the same problem of LiDAR-to-LiDAR interference and apply compatible timing and control techniques, yielding predictable results.
Regarding claim 2, Meissner, as modified in view of Allen teaches the method of claim 1, wherein the augmenting step further comprises dithering one or more of the spacio-temporal scanning profile trajectory parameters (Allen, fig. 5 col 9: lines 26-27, “the solid lines represent a temporally dithered train of light pulses...”).
Regarding claim 3, Meissner, as modified in view of Allen teaches the method of claim 2, wherein the dithering of the one or more of the spacio- temporal scanning profile trajectory parameters further comprises offsetting an angular sample trajectory from a nominal sampling trajectory (Allen, col 10: lines 18-2 “The three dimensions can include the angle A… range D… and time T” (angular component included in interference mitigation) 2).
Regarding claim 4, Meissner, as modified in view of Allen teaches the method of claim 3 further comprising determining the offset of the angular sample trajectory as a random value (Allen, fig. 5 col 9: lines 29-31 “The magnitude of the temporal shift δt, as well as its direction (plus or minus sign), are randomized.”).
Regarding claim 5, Meissner, as modified in view of Allen teaches the method of claim 2, wherein the dithering of the one or more of the spacio- temporal scanning profile trajectory parameters further comprises offsetting a sample timing window for detecting reflected light signals at the detector from a nominal sample timing window (Allen, fig. 5 col 9: lines 33-34 “the temporal spacings between adjacent light pulses are also random” (timing window offset)).
Regarding claim 6, Meissner, as modified in view of Allen teaches the method of claim 5 further comprising determining a timing of the offsetting as a random value (Allen, fig. 5 col 9: lines 33-34, col 13: lines 22-26 and claim 1 “randomized temporal spacings between adjacent light pulses”).
Regarding claim 7, Meissner, as modified in view of Allen teaches the method of claim 1, wherein the augmenting step further comprises one or more of stretching or compressing one or more of the spacio-temporal scanning profile trajectory parameters (Allen, fig. 5, col 9: lines 33-34 “the temporal spacings between adjacent light pulses are random” (non-uniform spacing inherently stretches/compresses timing)).
Regarding claim 8, Meissner, as modified in view of Allen teaches the method of claim 7, wherein the stretching or compressing the one or more of the spacio-temporal scanning profile trajectory parameters further comprises one or more of stretching or compressing an angular sample trajectory from a nominal sampling trajectory (Allen, col 13: lines 40-44 and claim 1 “analyzing spatial and temporal relationships between the respective point and neighboring points” (angular trajectory variation)).
Regarding claim 9, Meissner, as modified in view of Allen teaches the method of claim 8 further comprising randomly generating a profile of the one or more of the stretching or compressing of the angular sample trajectory (Allen, col 9: lines 12-21 “random or pseudorandom or any irregular pattern”).
Regarding claim 10, Meissner, as modified in view of Allen teaches the method of claim 7, wherein the stretching or compressing the one or more of the spacio-temporal scanning profile trajectory parameters further comprises one or more of stretching or compressing a sample timing window for detecting reflected light signals at the detector from a nominal sample timing window (Meissner, para 71 “Δtmax… corresponds to a time between consecutive emissions of light pulses” (variable window length)).
Regarding claim 11, Meissner, as modified in view of Allen teaches the method of claim 10 further comprising randomly generating a length for the one or more of the stretching or compressing of the sample timing window (Allen, fig. 5, col 9: lines 32-33, “δt may range from about −200 nanoseconds to about +200 nanoseconds”).
Regarding claim 12, Meissner, as modified in view of Allen teaches the method of claim 1, wherein the augmenting step further comprises modeling sensor sampling trajectories for known LiDAR sensors which can interfere with the LiDAR system (Allen teaches representing interfering LiDAR pulse trajectories (modeling) in col 9: lines 40-41 “the dotted lines represent the interference light pulses 540 from another LiDAR sensor” and lines 44-46 “the apparent times of flight for the train of interfering light pulses may differ from each other in a random fashion.” You cannot randomize relative to another LiDAR unless you have a representation (model) of that LiDAR’s timing trajectory.); and
adjusting the nominal set of reference values based, at least in part, on the modeled sensor sampling trajectories to mitigate interference by avoiding the modeled sensor sampling trajectories based on the known scan behavior of other LiDAR sensors in order to reduce overlap (Allen teaches “avoiding” modeled trajectories in fig. 5, col 9: lines 27-29 “each light pulse 520 is temporally shifted with respect to a corresponding nominal temporal position by an amount δt” and lines 43-46 “random shifting of the light pulses 520 emitted by the LiDAR sensor itself, the apparent times of flight for the train of interfering light pulses may differ from each other in a random fashion”).
Claims 13- 20 are system claims corresponding to method claims 2-3, 5, 7-8, 10, 12. They are rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Clinton T. Meneely (US 20100045965 A1), teaches lidar system using a pseudo-random pulse sequence
Kobi J. Scheim (US 20160327646 A1), teaches pseudo random sequences in array lidar systems
Jerry C. Chen (US 20190285749 A1), teaches lidar resistant to interference and hacking
Campbell et al. (US 20180275249 A1), teaches scan patterns for lidar systems
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/JEMPSON NOEL/Examiner, Art Unit 3645
/YUQING XIAO/Supervisory Patent Examiner, Art Unit 3645