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 .
Information Disclosure Statement
The Information Disclosure Statement (lDS) submitted on 03/13/2024 is in compliance with the provisions of 37 CFR 1.97 and has been considered.
Claim Objections
Claims 12-16 are objected to because of the following informalities:
Regarding claim 12, “the photon detection times” should perhaps read --the plurality of photon detection times--.
Regarding claim 13, “includes at least one of: the centroid of the photon detection times; or the maximum likelihood depth estimate, implemented as the log-matched filter of the photon detection times” should perhaps read --is determined based on at least one of: a centroid of the plurality of photon detection times; or a maximum likelihood depth estimate, implemented as a log-matched filter of the plurality of photon detection times--.
Regarding claim 15, “from photon detection times” should perhaps read --from the plurality of photon detection times--.
Regarding claim 16, “includes at least one of: the maximum likelihood estimator based on the number of photon detections; the maximum likelihood estimator based on the photon detection times; or the amplitude of a sparse vector recovered using union of subspaces optimization” should perhaps read --is determined using at least one of: a maximum likelihood estimator based on the number of photon detections; a maximum likelihood estimator based on the plurality of photon detection times; or an amplitude of a sparse vector recovered using union of subspaces optimization--.
Claim 14 is objected to by virtue of dependency.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 9-10 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 9 recites selecting an offset that “causes a match between the continuous trajectory and an observed change in radial falloff.” It is unclear what observed quantity exhibits the “radial falloff,” how that quantity is compared with the continuous trajectory, and what criterion constitutes a “match.” Consequently, the scope of the offset selection limitation is unclear.
Claim 10 recites “the prior knowledge,” but neither claim 10 nor claim 9, from which claim 10 depends, provides antecedent basis for that term. Although claim 8 recites “prior knowledge,” claim 8 is not incorporated into claim 10. Consequently, it is unclear what information is encompassed by “the prior knowledge.”
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 17 and 20 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Prenat (US 4746922 A).
Regarding claim 1, Prenat discloses a system for tracking positions of a target object (Fig. 1; Col. 4:16-28), comprising: circuitry (Fig. 1, tracking radar 2 and estimation circuit 1) configured to:
control an illumination source to periodically emit illumination pulses for illuminating the target object (Fig. 1, radar 2, as further detailed in Fig. 2; Col. 9:60-Col. 10:11, control circuit 102 controls switch 1021 to pulse transmitter 100 at repetition frequency fR(k), and antenna 101 radiates toward the tracked target);
detect illumination reflected from the target object to estimate a sequence of modulo distances to the target object wrapped by a pulse repetition period (Fig. 1, radar 2, as further detailed in Fig. 2; Col. 10:60-Col. 11:3, measurement circuits 120/121 supply received signal powers P1(k) and P2(k) to calculator 118, which computes measured ambiguous range y(k); Col. 1:30-35; Col. 3:1-15, measurements occur at Tk,ad(k) = c/[2fR(k)] and ambiguous range da(k) lies between zero and ad(k), where ad(k) is distance domain equivalent of pulse repetition period 1/fR(k)); and
unwrap the sequence of modulo distances subject to one or more continuity constraints to output a continuous trajectory of the target object (Fig. 1, estimation circuit 1; Col. 4:22-44, unwrap y(k) sequence to estimate unambiguous range d̂(k) and ambiguity number n̂(k); Col. 5:30-40, continuity is imposed by d(k+1)=d(k)-dd(k) and n(k+1)=n(k); Col. 7:47-50, d̂(k) output at each Tk).
Claim 17 is a method corresponding to the system of claim 1. Accordingly, claim 17 is rejected on the same grounds and in view of the same prior art as claim 1.
Claim 20 is a computer product corresponding to the system of claim 1. Accordingly, claim 20 is rejected on the same grounds and in view of the same prior art as claim 1.
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.
Claims 2-4 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Prenat in view of Frederick (US 20140015546 A1).
Regarding claim 2, Prenat discloses the system of claim 1, however does not disclose: wherein the sequence of modulo distances forms a discontinuous trajectory that is not differentiable at least at one instance of time, and wherein the continuous trajectory of the target object is differentiable at all instances of time. However, Frederick teaches: wherein the sequence of modulo distances forms a discontinuous trajectory that is not differentiable at least at one instance of time (Fig. 5, wrapped phase graph 500; ¶¶ 44-45, measured phase “wraps modulo 360 degrees” and the observable wrapped phase contains a “jump in phase larger than 180 degrees”; ¶ 31, reflected phase is linearly proportional to range, θ=720RFC/c, so the wrapped phase represents range modulo c/2FC), and wherein the continuous trajectory of the target object is differentiable at all instances of time (Fig. 3, continuous curve 302; ¶ 33, trajectory is R(t) = √(R32+[S(t-T3)]2) with R3 = 1 meter, and phase is proportional to R(t), and since R3>0, the derivative exists for every t; ¶ 51, unwrapping process “produces a continuous phase trajectory”). 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 the system of Prenat with the teachings of Frederick with a reasonable expectation of success in order to remove modulo induced phase jumps and preserve the target’s motion dependent phase as a continuous trajectory, thereby yielding a system with phase data that can be meaningfully interpreted and continuously tracked across wrap boundaries (Frederick, ¶¶ 45, 51).
Regarding claim 3, Prenat in view of Frederick teaches the system of claim 2, and further teaches: wherein the circuitry is further configured to recover unwrapped depth estimates at each measurement time from the sequence of modulo distances, based on the continuous trajectory of the target object (Prenat, Fig. 1, estimation circuit 1; Col. 4:28-39, circuit 1 forms a linear combination of all measured ambiguous ranges y(k) and recurrently estimates the unambiguous target range; Col. 5:30-35, propagated trajectory satisfies d(k+1)=d(k)-dd(k); Col. 7:48-50, “At time Tk , the estimated target range is d̂(k)”).
Regarding claim 4, Prenat in view of Frederick teaches the system of claim 3, and further teaches: wherein to unwrap the sequence of modulo distances, the circuitry is configured to execute a first-order difference phase unwrapping algorithm (Frederick, Fig. 4, DSP 490; ¶ 47, computes the first difference between consecutive wrapped samples ωRX(n)=θRX(n)-θRX(n-1); ¶¶ 48-50, corrects the difference by subtracting or adding 360 degrees when it exceeds ±180 degrees, and accumulates the corrected first differences according to ϕRX(n)=ϕRX(n-1)+ωRX(n); ¶ 51, resulting a “continuous phase trajectory”). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to further modify the system of Prenat in view of Frederick with the additional teachings of Frederick with a reasonable expectation of success in order to correct phase wrap discontinuities by differencing consecutive samples and adding or subtracting one phase cycle when the difference exceeds a half cycle threshold, thereby yielding a system with a straightforward recursive unwrapping routine that produces a continuous phase trajectory (Frederick, ¶¶ 47-51).
Claims 18-19 are methods corresponding to the system of claims 2-3. Accordingly, claims 18-19 are rejected on the same grounds and in view of the same prior art as claims 2-3.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Prenat in view of Frederick further in view of Lien (US 20160320853 A1).
Regarding claim 6, Prenat in view of Frederick teaches the system of claim 3, and further teach: wherein to unwrap the sequence of modulo distances, the circuitry is configured to execute an […] Kalman filter that estimates the continuous trajectory from the modulo distances (Prenat, Fig. 1, estimation circuit 1; Col. 4:28-39, “device 1 described in this embodiment is a Kalman filter,” which forms “a linear combination of all the measured values y(k) of the ambiguous range” and recurrently obtains the estimated unambiguous target range d̂(k); Col. 7:48-50, “At time Tk, the estimated target range is d̂(k)”). However, Prenat in view of Frederick does not teach: [the circuitry is configured to execute an] “extended” [Kalman filter]. Lien teaches the limitation in Fig. 3, micro-motion tracking module 308; ¶ 34, “an extended Kalman filter may be used to incorporate raw phase with the Doppler centroid … which allows for nonlinear phase unwrapping”). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to further modify the system of Prenat in view of Frederick with the teachings of Lien with a reasonable expectation of success in order to incorporate raw phase with Doppler centroid information in an extended Kalman filter so that nonlinear wrapping is resolved within the trajectory estimator, thereby yielding a system with nonlinear phase unwrapping and finer resolution displacement tracking using lower complexity ranging hardware (Lien, ¶¶ 22-23, 34).
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Prenat in view of Koelpin (“Six-Port Based Interferometry for Precise Radar and Sensing Applications,” published 2016)1.
Regarding claim 7, Prenat discloses the system of claim 1, and further discloses: wherein the continuous trajectory of the target object defines a change of distances of the target object with respect to the illumination source (Fig. 1, estimation circuit 1; Col. 5:30-35, the tracked state satisfies d(k+1)=d(k)-dd(k) and successive trajectory values represent changes in radar-to-target distance; Col. 4:48-56, radial velocity VR(k) is “the derivative of the radar-to-target range” and compensates variations of that range), and […]. However, Prenat does not disclose: “wherein the circuitry is further configured to determine an offset for shifting the continuous trajectory of the target object to produce a shifted continuous trajectory tracking absolute distances of the target object with respect to the illumination source.” Koelpin teaches the limitation in p. 8, § 3.1, Eq. 14 and Fig. 8, wherein for the Fig. 8 distance detection system, unwrapping or counting phase periods produces relative displacement measurements and adding ambiguity period multiples “as the offset.” Additionally, Koelpin in p. 19, § 5.1.1 teaches determining a coarse absolute target distance and then obtaining an “accurate absolute distance value” by “adding an offset corresponding to the period of the ambiguity” to the trajectory, thus since Eq. 14 linearly maps phase to target displacement, the added phase period offset correspondingly shifts the continuous distance trajectory to track absolute target-to-receiver distances. 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 the system of Prenat with the teachings of Koelpin with a reasonable expectation of success in order to anchor precise relative phase tracking with a coarse absolute distance measurement and add the corresponding ambiguity period offset, thereby yielding a system that retains precise relative displacement tracking while outputting an accurate absolute target distance (Koelpin, § 5.1.1, p. 19).
Regarding claim 8, Prenat in view of Koelpin teaches the system of claim 7, and further teaches: wherein the circuitry is configured to determine the offset from prior knowledge of absolute position of the target object at one or more time instances during the continuous trajectory (Koelpin, p. 19, § 5.1.1, ambiguity resolution requires “knowledge of the starting position,” which is prior knowledge of absolute target position at the starting time instance of the trajectory, and determines a coarse “absolute distance of the target” at selected time steps and calculates the ambiguity period offset from that coarse absolute estimate before continuing precise trajectory evaluation, therefore the offset is determined from an absolute target position known at one or more trajectory time instances). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Prenat in view of Koelpin with the additional teachings of Koelpin with a reasonable expectation of success in order to use a known starting position or coarse absolute distance observation to select the correct ambiguity period offset, thereby yielding a system with an absolute distance trajectory referenced to a known target position rather than an arbitrary phase constant (Koelpin, § 5.1.1, p. 19).
Claims 1, 11, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Shand (US 20190004177 A1) in view of Liu (“Velocity-based sparse photon clustering for space debris ranging by single-photon Lidar,” published January 2024)2.
Regarding claim 1, Shand discloses a system for tracking positions of a target object (Fig. 1, LIDAR device 100; ¶ 61, the LIDAR “rapidly and repeatedly scan[s] across a scene to provide continuous real-time information on distances to reflective objects” and associates “a three-dimensional position with each returning light pulse”), comprising:
circuitry (Fig. 1, electronics 104 and receiver 110; ¶¶ 74, 76-78, and 84-88; Fig. 6, method 600, which ¶ 138 states may be implemented using the Fig. 1 arrangement, and ¶ 140 states may be implemented by circuitry) configured to:
control an illumination source to periodically emit illumination pulses for illuminating the target object (Fig. 1, electronics 104 controlling light source 106; ¶ 62, emission according to “a periodic sequence”; ¶ 77, control signals control light emission; ¶¶ 80-81, light source 106 emits light pulses);
detect illumination reflected from the target object (Fig. 1, receiver 110; ¶¶ 84 and 86-88, receiver 110 focuses reflected light onto detectors that convert the detected light into an electrical signal) to estimate a sequence of modulo distances to the target object wrapped by a pulse repetition period (Fig. 6, block 606, implemented by electronics 104; ¶¶ 65 and 147-153, computing system computes a close range sequence relative to the most recently emitted pulses even when the detected returns actually correspond to earlier pulses, where the close range values are true distances wrapped into the range associated with one pulse repetition period); and
unwrap the sequence of modulo distances subject to one or more continuity constraints (Fig. 6, blocks 608-610, implemented by electronics 104; ¶¶ 151 and 154-159, the system reassociates returns with preceding emitted pulses and selects the range sequence whose ranges are “substantially similar to one another,” including ranges matching within a threshold tolerance) [...].
Shand does not disclose: [unwrap the sequence of modulo distances subject to one or more continuity constraints] “to output a continuous trajectory of the target object.” However, Liu teaches the limitation in p. 2, Methods and p. 3, Algorithm 1, steps 5-6. Specifically, Liu models target range over time using a continuous polynomial, clusters photon data according to velocity and acceleration, and performs “a polynomial fitting on the ranging data” thereby “obtaining the trajectory of the target,” where the fitted range versus time polynomial is a continuous trajectory of the target object. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Shand with the teachings of Liu with a reasonable expectation of success in order to extract a continuous target trajectory from sparse photon returns in substantial background noise, thereby yielding a system with rapid and high precision trajectory tracking under low signal-to-noise conditions (Liu, p. 1, Abstract and Introduction).
Regarding claim 11, Shand in view of Liu teaches the system of claim 1, and further teaches: wherein the circuitry comprises a single-photon detector to detect the illumination reflected from the target object (Liu, p. 2, Methods, ranging subsystem “mainly consists of a pulsed laser, a single photon detector, a time synchronization control and photon counting circuit modules” and the “TCSPC module records the time difference between the laser pulse emission and the echo photon detection”) and generate within a total acquisition time, raw data as a sequence of photon detection time stamps (Liu, p. 1, Introduction; p. 2, Methods; p. 3, Algorithm 1, “original echo photon data is acquired using SPADs and a high-resolution time-correlated single photon counting” module and represents the original photon database using indexed photon collection times and corresponding ranges over a defined detection duration, where the detection duration is the total acquisition time, the original photon database is raw data, and the indexed photon collection times are a sequence of photon detection timestamps). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Shand in view of Liu with the additional teachings of Liu with a reasonable expectation of success in order to improve weak return detection efficiency and photon timing resolution while reducing required illumination pulse energy, thereby yielding a system with sensitive, high resolution single photon timestamp acquisition for improved long range ranging (Liu, p. 1, Introduction; p. 2, Methods).
Claim 17 is a method corresponding to the system of claim 1. Accordingly, claim 17 is rejected on the same grounds and in view of the same prior art as claim 1.
Claim 20 is a computer product corresponding to the system of claim 1. Accordingly, claim 20 is rejected on the same grounds and in view of the same prior art as claim 1.
Claims 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Shand in view of Liu further in view of Hollen (US 20240302502 A1).
Regarding claim 12, Shand in view of Liu teaches the system of claim 11, and further teaches: wherein the total acquisition time (Liu, p. 2, Methods, detection duration during which the original photon data is collected) is [...] to estimate the sequence of modulo distances to the target object (Shand, Fig. 6, blocks 606-608; ¶¶ 147-159, generation and selection of close range and alternate range sequences).
Shand in view of Liu does not teach: [the total acquisition time is] “divided into a sequence of sub-acquisitions, each sub-acquisition of the sequence of sub-acquisitions defined by a plurality of photon detection times, wherein the circuitry is configured to produce a modulo depth estimate from the photon detection times within each sub-acquisition of the sequence of sub-acquisitions” [to estimate the sequence of modulo distances to the target object]. However, Hollen teaches the limitation in Fig. 1 LIDAR system 100, whose control circuit 110 and sensor array 140 are further detailed by the Fig. 2 processor circuit 210 and detector array 240, and whose pixel level histogram processing is further detailed by Figs. 6-8. Specifically, Hollen teaches the total acquisition time is divided into a sequence of sub-acquisitions (¶ 9, a frame includes N temporally spaced subframes; ¶ 59, repeated strobe intervals are aggregated into respective subframes, and the subframes define an image frame); each sub-acquisition is defined by a plurality of photon detection times (Fig. 6, pixel 600 and memory block 610; ¶¶ 67-72, SPAD detections are assigned to photon arrival time bins relative to repeated start signals and accumulated across multiple shots; ¶ 83, a first subframe histogram is generated from approximately 250 emitted pulses and the corresponding SPAD detections); circuitry configured to produce a modulo depth estimate from the photon detection times within each sub-acquisition (Fig. 7, histogram 712, peak finding 714, and windowing 716; ¶¶ 66, 71, and 83-85, the temporal position of a detected histogram peak supplies the received time or time-of-flight estimate for that subframe, where because the arrival times are measured within recurring laser cycle bins, the resulting time-of-flight depth is a depth modulo the pulse repetition period); and, the circuitry produces a sequence of such modulo depth estimates (¶¶ 83-85 and 91-92, histogram and peak-estimation process is repeated for successive subframes). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Shand in view of Liu with the teachings of Hollen with a reasonable expectation of success in order to distribute emitter operation and photon data acquisition among successive subframes, thereby yielding a system with reduced power supply stress and heating, reduced pixel memory requirements, and improved timing resolution (Hollen, ¶¶ 10-15, 40-41, and 115-117).
Regarding claim 13, Shand in view of Liu and Hollen teaches the system of claim 12, and further teaches: wherein the modulo depth estimate in a sub-acquisition of the sequence of sub-acquisitions includes at least one of: the centroid of the photon detection times; or the maximum likelihood depth estimate, implemented as the log-matched filter of the photon detection times (Hollen, Fig. 2, processor circuit 210; ¶ 58, the pixel processor calculates an “average ToF aggregated over hundreds or thousands of laser pulses and photon returns”; ¶ 59, those repeated laser and detection intervals are aggregated into respective subframes, where the average of the photon time-of-flight values is the centroid of the photon detection times). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Shand in view of Liu and Hollen with the additional teachings of Hollen with a reasonable expectation of success in order to aggregate numerous photon return times into an average time-of-flight estimate, thereby yielding a system with an increased signal-to-noise ratio and a more reliable depth estimate for each sub-acquisition (Hollen, ¶¶ 58, 72).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Shand in view of Liu further in view of Tobin (“Robust real-time 3D imaging of moving scenes through atmospheric obscurant using single-photon LiDAR,” published 2021)3.
Regarding claim 15, Shand in view of Liu teaches the system of claim 11, wherein the total acquisition time (Liu, p. 2, Methods, the defined detection duration during which original photon data is collected) is [...]. Shand in view of Liu does not teach: [the total acquisition time is] “divided into a sequence of sub-acquisitions, each sub acquisition of the sequence of sub-acquisitions defined by a plurality of photon detection times, wherein the circuitry is configured to produce a reflectivity estimate from photon detection times within each sub-acquisition of the sequence of sub-acquisitions.” However, Tobin teaches the limitation in Fig. 1 bistatic SPAD and TCSPC imaging system, as processed by the Fig. 4 M2R3D algorithm and applied to the Fig. 7 moving scene sequence. Specifically, Tobin teaches the total acquisition time is divided into a sequence of sub-acquisitions (p. 8, “Real-time processing of moving 3D scenes in obscurant” measurements extending for several minutes are reconstructed as a ten frame per second video, with each output frame formed by aggregating 15,000 successive binary frames; Fig. 7, each output frame represents 100 milliseconds of acquisition); each sub-acquisition is defined by a plurality of photon detection times (Fig. 1, raw data cube acquired during a 100 millisecond frame; p. 4, TCSPC system supplies successive data cubes, and each cube / frame contains histograms of photon counts indexed by time-of-flight bin, where time-of-flight bins represent the photon detection times accumulated during the frame); circuitry produces a reflectivity estimate from the photon detection times within each sub-acquisition (Fig. 4, measured photon counts at frame k are supplied to the “Robust Depth and Reflectivity estimation” process; p. 4, reflectivity is a target parameter for each frame; p. 5, algorithm estimates depth and reflectivity images from the successively observed photon histograms and uses previously estimated depth and reflectivity frames to restore the current frame). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Shand in view of Liu with the teachings of Tobin with a reasonable expectation of success in order to derive per-frame reflectivity information while accounting for sparse photon returns and high, nonuniform background levels, thereby yielding a system with robust real time depth and reflectivity characterization of moving targets in degraded visual environments (Tobin, p. 2; p. 5, “Reconstruction algorithm”; p. 10, “Discussion”).
Allowable Subject Matter
Claims 5, 14 and 16 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. Claims 9-10 would be allowable if rewritten to overcome the rejection under 35 U.S.C. 112(b) set forth in this Office action and to include all limitations of the base claim and any intervening claims. A statement of reasons for the indication of allowable subject matter are as follows.
With respect to claim 5, Prenat in view of Frederick does not teach the system of claim 3, wherein to unwrap the sequence of modulo distances, the circuitry is configured to execute a convex optimization Lasso-B2R2 algorithm. Neither Lien, Koelpin, Shand, Liu, Hollen nor Tobin remedy the deficiencies of Prenat in view of Frederick.
With respect to claim 9, Prenat in view of Koelpin does not teach the system of claim 7, wherein the circuitry is configured to determine the offset by selecting an offset that causes a match between the continuous trajectory and an observed change in radial falloff over the course of the continuous trajectory. Neither Lien, Frederick, Shand, Liu, Hollen nor Tobin remedy the deficiencies of Prenat in view of Frederick.
With respect to claim 14, Shand in view of Liu and Hollen does not teach the system of claim 12, wherein the modulo depth estimate in a sub-acquisition is determined by a union of subspaces optimization model. Neither Lien, Koelpin, Prenat, Frederick, nor Tobin remedy the deficiencies of Shand in view of Liu and Hollen.
With respect to claim 16, Shand in view of Liu and Tobin does not teach the system of claim 15, wherein the reflectivity estimate in each sub-acquisition of the sequence of sub-acquisitions includes at least one of: the maximum likelihood estimator based on the number of photon detections; the maximum likelihood estimator based on the photon detection times; or the amplitude of a sparse vector recovered using union of subspaces optimization. Neither Lien, Koelpin, Prenat, Frederick, nor Hollen remedy the deficiencies of Shand in view of Liu and Tobin.
The remaining prior art made of record and not relied upon is considered pertinent to applicant’s disclosure, as noted in the attached PTO 892, include:
Rieger (US 20120257186 A1) discloses addressing pulsed time-of-flight range ambiguity by varying pulse intervals, forming candidate distance measurement series for different pulse mappings and time windows, and selecting the series least affected by the modulation signal as the correct distance result. However, Rieger does not teach the specific Lasso-B2R2 convex unwrapping of claim 5, radial falloff-based offset selection of claim 9, union of subspaces modulo depth estimation of claim 14, or the claim 16 reflectivity estimators based on photon detections/timestamps or sparse vector amplitude.
Egea (US 20190346570 A1) discloses a ToF camera that emits active IR illumination, measures reflected light, evaluates phase wrapped measurements, and determines depth by selecting among candidate phase wrappings. However, Egea does not teach the specific Lasso-B2R2 convex optimization of claim 5, radial falloff offset matching of claim 9, union of subspaces modulo depth optimization of claim 14, nor the reflectivity estimators based on photon counts/timestamps or sparse vector amplitudes of claim 16.
In sum, the prior art made of record teach or suggest various aspects of the invention, but none in a way that would fully anticipate or render obvious all limitations as specifically recited in claims 5, 9, 14 and 16. Accordingly, claims 5, 14 and 16 would be allowable if rewritten in independent form, including all limitations of its base claim and any intervening claims. Claim 9 would be allowable if rewritten to overcome the rejection under 35 U.S.C. 112(b) set forth in this Office action and to include all limitations of the base claim and any intervening claims. Claim 10 would be allowable if rewritten to overcome the rejection under 35 U.S.C. 112(b) set forth in this Office action and to include all limitations of the base claim and any intervening claims by virtue of dependency to claim 9.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
Conclusion
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1 Koelpin, A.; Lurz, F.; Linz, S.; Mann, S.; Will, C.; Lindner, S. Six-Port Based Interferometry for Precise Radar and Sensing Applications. Sensors 2016, 16, 1556.
2 Xialin Liu et al., “Velocity-based sparse photon clustering for space debris ranging by single-photon Lidar” arXiv:2401.04147v1 [physics.data-an], published 8 Jan 2024.
3 Tobin, Rachael, et al. "Robust real-time 3D imaging of moving scenes through atmospheric obscurant using single-photon LiDAR." Scientific reports 11.1 (2021): 11236.
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