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 .
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 1-20 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.
Claims 1, 8, and 15 recite the limitation "the frequency spectrum" in “determine (determining) a spread function for the frequency spectrum” and “perform (performing) a correction of the frequency spectrum”. There is insufficient antecedent basis for this limitation in the claim.
Applicant could amend the claim to refer to “the first frequency spectrum” or “a frequency spectrum”.
Claims 2-7, 9-14, and 16-20 are rejected because they depend from claims 1, 8, and 15 respectively.
Claims 4, and 11 recite the limitation "the scanning mirror" in “an angular velocity of the scanning mirror”. There is insufficient antecedent basis for this limitation in the claim.
Applicant could amend the claim to refer to “a scanning mirror”.
Claims 5 and 12 are rejected because they depend from claims 4, and 11 respectively.
Claims 5, 12, and 18 recite the limitation " the expected frequency waveform" in “for the plurality of scanning parameters based on the expected frequency waveform”. There is insufficient antecedent basis for this limitation in the claim.
Applicant could amend the claim to refer to “an expected frequency waveform”.
Claims 5, 12, and 18 recite the limitation " the doppler shifted frequency spectrum" in “based on the expected frequency waveform and the doppler shifted frequency spectrum”. There is insufficient antecedent basis for this limitation in the claim.
Applicant could amend the claim to refer to “a doppler shifted frequency spectrum”.
Claims 6, and 14 recite the limitation " the first frequency waveform " in “apply the matched filter to the first frequency waveform” and “performing the correction of the first frequency waveform”. There is insufficient antecedent basis for this limitation in the claim.
Applicant could amend the claim to refer to “a first frequency waveform”.
Claim 11 recites the limitation " the LIDAR system" in a chirp rate of an optical source of the LIDAR system. There is insufficient antecedent basis for this limitation in the claim.
Applicant could amend the claim to refer to “a LIDAR system”.
Claims 16-20 recite the limitation " the processing device ". There is insufficient antecedent basis for this limitation in the claim.
Applicant could amend the claim to refer to “a processing device”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Step 1 - Statutory Category: Step 1 of the 2019 Guidance requires the examiner to determine if the claims are to one of the statutory categories of invention. Applied to the present application, claims 1-7 and 15-20 are directed to a machine (device/system) and claims 8-14 a process (method). Accordingly, claims 1-20 fall within at least one of the four statutory categories of invention (process, machine, manufacture, or composition of matter) under 35 U.S.C. 101.
Claim 1 is reproduced below with the abstract idea underlined.
Claim 1: A light detection and ranging (LIDAR) system, comprising: an optical scanner to transmit an optical beam towards, and receive a return signal from, a target; an optical processing system coupled to the optical scanner to generate an electrical signal comprising a plurality of frequencies in a first frequency spectrum; and a signal processing system coupled to the optical processing system, comprising: a processing device; and a memory operatively coupled to the processing device, the memory to store instructions that, when executed by the processing device, cause the LIDAR system to: determine a value for each of a plurality of scanning parameters associated with the optical scanner; determine a spread function for the frequency spectrum based on the values for each of the plurality of scanning parameters; and perform a correction of the frequency spectrum based on the spread function.
Under Step 2A, Prong 1, Claim 1’s underlined limitations recite a spread function which is a mathematical transfer function and determining this function as a function of multiple input variables (scanning parameters) represents mathematical equation or algorithm. Furthermore, correcting frequency spectrums using spread function requires mathematical equations. Determining a value for each of a plurality of scanning parameters can be characterized as merely reading or observing numerical data points which can be considered mental process.
Accordingly, claim 1 recites a judicial exception in the form of mathematical concepts and mental process.
Step 2A, Prong 2: examiner needs to determine if the claim(s) recite additional elements
that integrate the exception into a practical application of the exception. The additional elements in the claim have been left in normal font. Claim 1 integrates the judicial exception into a practical application because of the following reasons:
Claim 1 additional elements recite measuring and data processing hardware. The mathematical calculations are tied to physical sensors that improve measuring hardware. Because the mathematical algorithm is integrated into a practical application that improves LIDAR hardware performance, claim 1 is patent eligible under 35 U.S.C. 101 step 2A prong 2.
Claims 8 and 15 have analogous limitations to claim 1 so they are patent eligible under 35 U.S.C. 101 step 2A prong 2 for the same reasons as set forth with respect to analysis of claim 1 above.
Claim Rejections - 35 USC § 102
(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 1-3, 6, 8-10, 13, 15-17, and 19 are rejected under 35 U.S.C. 102 (a)(1) as anticipated by Krause Perin et al. (US 20220120860 A1) hereinafter Krause Perin.
Regarding claim 1, Krause Perin teaches a light detection and ranging (LIDAR) system (a LiDAR system 100, fig. 1A and ¶ [22]), comprising: an optical scanner to transmit an optical beam towards, and receive a return signal from, a target (optical scanner 102, fig. 1A and ¶ [24]); an optical processing system (optical receivers 104, optical circuits 101, free space optics 115, and signal conversion unit 106, fig. 1A) coupled to the optical scanner (free space optics 115 and optical receivers 104 are optically and electronically coupled to receive reflected return light collected by optical scanner 102, ¶ [23 & 28]) to generate an electrical signal comprising a plurality of frequencies in a first frequency spectrum (optical receivers 104 mixes the return signals with a local oscillator to output a beat frequency signal ¶ [28]. The system converts the beat signal into frequency domain to produce an input spectrum where the received signal comprises a first frequency waveform, ¶ [35 & 53]); and a signal processing system coupled to the optical processing system (LiDAR control system 110 and signal processing unit 112, fig. 1A), comprising: a processing device (processing device, ¶ [25]); and a memory operatively coupled to the processing device, the memory to store instructions (a memory and a processing device or processor operatively coupled with the memory, ¶ [7]) that, when executed by the processing device, cause the LIDAR system to (the non-transitory machine-readable medium has instructions stored therein, which when executed by a processing device or processor of a LiDAR system, cause the processing device or processor to …, ¶ [8]): determine a value (receiving/measuring real-time metrics and returning operational information via motion control system 105 or Lidar control system 110, ¶ [27]) for each of a plurality of scanning parameters (the set of metrics may include the angular speed of the scanning mirror, the position of the scanning mirror, the optical scanner geometry, the scanning mirror size, the beam diameter, or a target, etc, ¶ [8 & 44]) associated with the optical scanner (attributes these parameters to the physical components and geometry of the optical scanner (e.g., scanning mirror and optical deflector geometry) ¶ [24 & 44]); determine a spread function (a frequency domain filter waveform M(f) whose bandwidth B is dynamically calculated/adjusted based on mirror angular speed, ¶ [45 & 50]. Adjusting filter bandwidth based on mirror angular speed is analogous to determining a parameter index spread function) for the frequency spectrum based on the values for each of the plurality of scanning parameters (a frequency domain filter waveform M(f) whose bandwidth B is dynamically calculated based on a plurality of scanner metrics (mirror angular speed, mirror position, scanner geometry) to compensate for mirror Doppler spreading, ¶ [45 & 50]); and perform a correction of the frequency spectrum based on the spread function (dynamically updates the filter coefficients and widens the filter bandwidth B in direct proportion to the mirrors angular rotation speed and scanner geometry ¶ [44-47]. By filtering the input spectrum using mirror speed adapted filter waveform (e.g., Gaussian, sinc, or rectangular PSD shape, ¶ [50]), the system eliminates mirror frequency smearing and restores sharp target peaks).
Claims 8 and 15 recite the analogous limitations as claim 1 and therefore are rejected for the same reasons as set forth with respect to rejection of claim 1.
Regarding claim 2, Krause Perin teaches the LIDAR system of claim 1, wherein to determine the spread function for the frequency spectrum, the processing device is to: select the spread function from a plurality of spread functions (selects a filter waveform/shape from a plurality of candidate waveforms (e.g., rectangular, sinc, sinc-squared, or Gaussian waveforms), fig. 5 and ¶ [50]) based on the value for each of the plurality of scanning parameters (selects and updates filter waveform and its coefficients based on scanner metrics comprising the angular speed of the scanning mirror, the scanning mirror size, and the beam diameter ¶ [44]).
Claims 9 and 16 recite the analogous limitations as claim 2 and therefore are rejected for the same reasons as set forth with respect to rejection of claim 2.
Regarding claim 3, Krause Perin teaches the LIDAR system of claim 2, wherein the processing device is further to: calibrate (updates filter coefficients and bandwidth parameter B for candidate waveforms, fig. 6) each of the plurality of spread functions (different matched filter waveforms may be selected based on theoretical simulation or modeling, or may be selected empirically, fig 5 and ¶ [50]) using selected values for the plurality of scanning parameters (the filter coefficients 403 for the matched filter 402 may be updated according to a set of metrics including an angular speed of a scanning mirror, a position of the scanning mirror, an optical scanner geometry, a scanning mirror size, a beam diameter, or a target, etc ¶ [44]) and an expected frequency spectrum (the matched filter 402 may include a second frequency waveform, which may be the expected received signal frequency waveform ¶ [41]).
Claims 10 and 17 recite the analogous limitations as claim 3 and therefore are rejected for the same reasons as set forth with respect to rejection of claim 3.
Regarding claim 6, Krause Perin teaches the LIDAR system of claim 1, wherein to perform the correction of the first frequency spectrum based on the spread function (dynamically updates the filter coefficients and widens the filter bandwidth B in direct proportion to the mirrors angular rotation speed and scanner geometry ¶ [44-47]. By filtering the input spectrum using mirror speed adapted filter waveform (e.g., Gaussian, sinc, or rectangular PSD shape, ¶ [50]), the system eliminates mirror frequency smearing and restores sharp target peaks), the processing device is to: determine a matched filter associated with the spread function (selecting a matched filter comprising a secondary waveform (e.g., Gaussian, sinc, or rectangular PSD shape, ¶ [50]) whose bandwidth B is scaled according to the mirror Doppler spreading, Abstract); and apply the matched filter to the first frequency waveform to obtain a compensated frequency spectrum (inputting the received signal spectrum 401 into matched filter 402 to filter the received signal and produce a filtered output spectrum for peak detection, fig.4 and ¶ [6]).
Claims 13 and 19 recite the analogous limitations as claim 6 and therefore are rejected for the same reasons as set forth with respect to rejection of claim 6.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 4 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Krause Perin et al. (US 20220120860 A1) hereinafter Krause Perin in view of Mickel et al. (US 12153136 B1) hereinafter Mickel and further in view of Fisher et al. (US 2020/0072946 A1) hereinafter Fisher.
Regarding claim 4, Krause Perin teaches the LIDAR system of claim 3, wherein the plurality of scanning parameters comprises an angular velocity of the scanning mirror (the filter coefficients may be updated depending on key factors such as a mirror angular speed, ¶ [5]) of an optical source of the LIDAR system (active optical components on optical circuits 101 driving optical sources such as lasers and amplifies via optical driver 103, fig. 1A ¶ [26]).
Krause Perin further defines Chirp rate (
k
=
Δ
f
c
T
c
) as an adjustable system parameter, ¶ [36].
Krause Perin teaches the filter coefficients may be constant (e.g., derived from theoretical simulation or modeling), or updated depending on key factors such as a mirror angular speed, a mirror position, a scanner geometry, a target, a scene, etc, ¶ [5]. However, Krause doesn’t explicitly disclose the plurality of scanning parameters comprises a range of a target, an azimuth of the target, an elevation of the target, and a chirp rate of an optical source of the LIDAR system.
Mickel teaches a range of a target (obtaining a library of candidate point spread functions (PSF) that each correspond to a different possible object range/distance for deconvolution, Abstract). Mickel discloses that its technology is directly applicable to 2D and 3D LiDAR systems as well as laser range finding systems, col. 2 ll. 53-66.
Fisher teaches an azimuth of the target, [and] an elevation of the target (evaluates optical distortion using a 2D spread function g (x,y) indexed across 2D spatial detector coordinates, ¶ [70] and fig. 9. g(x,y) is defined as the Glare spread function measured from a single point source of light in space. Because a point light source in space originates at a single (Ө,
ϕ
) coordinate, g(x,y) records how optical scattering smears that single direction’s energy across neighboring azimuth (x) and elevation (y) pixel locations on the sensor plane.).
It would have been obvious to one ordinary skill in art before the effective filling date of the claimed invention to combine teachings of Mickel and Fisher with Krause Perin system to aggregate a 5-parameter input lookup vector (range, azimuth, elevation, mirror velocity, and chirp rate). Because each of these five operational parameters directly dictates the physical width and frequency scaling of the mirror Doppler spectrum, combining these teachings represents optimization of result-effective variables to ensure matched filter calibration across varying target distances, scan angles, mirror speed, and chirp rate without producing any unexpected results.
Claim 11 recites the analogous limitations as claim 4 and therefore is rejected for the same reasons as set forth with respect to rejection of claim 4.
Claims 5, 12, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Krause Perin et al. (US 20220120860 A1) hereinafter Krause Perin in view of Hall et al. (US 11561305 B2) hereinafter Hall.
Regarding claim 5, Krause Perin teaches the LIDAR system of claim 3, wherein to calibrate each of the plurality of spread functions (updates filter coefficients and bandwidth parameter B for candidate waveforms, fig. 6. Different matched filter waveforms may be selected based on theoretical simulation or modeling, or may be selected empirically, fig 5 and ¶ [50])).
Krause Perin teaches when the scanning mirror is moving at a low mirror speeds (e.g., <5 kdeg/s), the mirror-induced Doppler has little impact on the signal quality. The peak value 302 a may be detected in the PSD 301 a of the received signal, fig. 3A and ¶ [38]). However, Krause Perin does not teach sample a first signal at a mirror speed of zero.
Hall teaches a scanning LiDAR system wherein the mirror is stationary, (Col. 15, claim 8).
It would have been obvious to one ordinary skill in art before the effective filling date of the claimed invention to modify baseline sampling of Krause Perin by employing a stationary mirror as taught by Hall to eliminate any residual mirror Doppler broadening artifacts prior to active scanning.
Krause Perin in view of Hall further teaches the processing device is to: sample a first signal at a mirror speed of zero (The peak value 302 a may be detected in the PSD 301 a of the received signal, (Krause Perin, fig. 3A and ¶ [38]), and (Hall, col. 15, claim 8 )) using the selected values for the plurality of scanning parameters (Krause Perin, selects and updates filter waveform and its coefficients based on scanner metrics comprising the angular speed of the scanning mirror, the scanning mirror size, and the beam diameter ¶ [44])) to determine the expected frequency spectrum (Krause Perin, the expected received signal frequency waveform/PSD 301 a used by matched filter 402, fig. 3A and ¶ [41 & 42]); sample a second signal at a non-zero scanning mirror speed (Krause Perin, As depicted in FIG. 3B, when the scanning mirror is moving at a high mirror speeds (>5 kdeg/s), there may be a significant broadening of the signal power spectrum density (PSD) 301 b , fig. 3B and ¶ [39]) using the selected values for the plurality of scanning parameters (Krause Perin, selects and updates filter waveform and its coefficients based on scanner metrics comprising the angular speed of the scanning mirror, the scanning mirror size, and the beam diameter ¶ [44])) to determine a doppler spread frequency spectrum (Krause Perin, first frequency waveform or input spectrum 401 (when sampled while the scanning mirror is actively rotating at non-zero scanning speeds )/ PSD 301b (fig.3B), ¶ [41 & 42]); and calculate the spread function associated with the selected values (Krause Perin, receiving/measuring real-time metrics and returning operational information via motion control system 105 or Lidar control system 110, ¶ [27]. The set of metrics may include the angular speed of the scanning mirror, the position of the scanning mirror, the optical scanner geometry, the scanning mirror size, the beam diameter, or a target, etc, ¶ [8 & 44]) for the plurality of scanning parameters (Krause Perin, a frequency domain filter waveform M(f) whose bandwidth B is dynamically calculated/adjusted based on mirror angular speed, mirror position, scanner geometry, ¶ [45 & 50]. Adjusting filter bandwidth based on mirror angular speed is analogous to determining a parameter index spread function) based on the expected frequency waveform (Krause Perin, M(f) is chosen to match the baseline expected PSD of the optical subsystem, ¶ [42& 50]) and the doppler shifted frequency spectrum (Krause Perin, B is scaled proportionally to mirror speed to expand the filter width across the Doppler-broadened spectrum, ¶ [50]).
Claims 12 and 18 recite the analogous limitations as claim 5 and therefore are rejected for the same reasons as set forth with respect to rejection of claim 5.
Claims 7, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Krause Perin et al. (US 20220120860 A1) hereinafter Krause Perin and further in view of Fisher et al. (US 2020/0072946 A1) hereinafter Fisher.
Regarding claim 7, Krause Perin teaches the LIDAR system of claim 1, and Krause Perin further teaches how to perform the correction of the first frequency spectrum based on the spread function (dynamically updates the filter coefficients and widens the filter bandwidth B in direct proportion to the mirrors angular rotation speed and scanner geometry ¶ [44-47]. By filtering the input spectrum using mirror speed adapted filter waveform (e.g., Gaussian, sinc, or rectangular PSD shape, ¶ [50]), the system eliminates mirror frequency smearing and restores sharp target peaks).
However, Krause Perin teaches using a matched filter to generate a filtered spectrum. Krause Perin doesn’t disclose any deconvolution technique.
Krause Perin doesn’t teach the LIDAR system of claim 1, wherein to perform the correction of the first frequency spectrum based on the spread function, the processing device is to: perform a deconvolution of the first frequency spectrum using the spread function to obtain a compensated frequency spectrum.
Fisher teaches generating corrected Lidar image data by performing 2D deconvolution of received signals p(x,y) using a Glare Spread Function (GSF) g(x,y), ¶[71]. Fisher further teaches recovering the corrected, unblurred signal i(x,y) by deconvolution of the measured image data p(x,y) represented by the detection signals and the GSF g(x,y) (e.g., by computing and dividing respective fast Fourier transforms (FFTs) of the measured data p(x,y) and the GSF g(x,y) and performing an inverse transform of the result), ¶ [71]
It would have been obvious to one ordinary skill in art before the effective filling date of the claimed invention to use deconvolution filter taught by Fisher to correct the frequency waveform taught by Krause Perin to recover the clean, unbroadened return spectrum.
Claims 14 and 20 recite the analogous limitations as claim 7 and therefore are rejected for the same reasons as set forth with respect to rejection of claim 7.
Conclusion
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/SAEEDE NAFOOSHE/ Examiner, Art Unit 2857
/ANDREW SCHECHTER/ Supervisory Patent Examiner, Art Unit 2857
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