DETAILED ACTION
Notice of Pre-AIA or AIA Status
This is in response to application no.18/794,372 filed on 08/05/2024. 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 § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 6, 7, 8, 13 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Massoud et al. (US 20210011125 A1) in view of Damon et al. (US 20190367104 A1).
Regarding claim 1, Massoud teaches the claim limitation as follows:
A LiDAR system for object detection comprising: a receiver configured to receive a light signal reflected from an object (FIGS. 1 and 2, ¶0041: receiver 106 is configured to receive an echo signal y(t), reflected from an object 104); a digital converter configured to convert the received light signal into a digital signal (¶0043: Received signal y(t) is forwarded to the digital converter 106a. The digital converter 106a is configured to convert y(t) into a digital signal y(n)); a pre-processor configured to pre-process the digital signal based on (¶0043: The digital signal y(n) is then supplied to the pre-processor 106b for filtering and noise removal. To this end, the pre-processor 106b filters the digital signal y(n)…generates a pre-processed signal y′(n)); and a processor configured to analyze the pre-processed signal based on a threshold technique to detect a presence of the object ( ¶0044-0045: Pre-processed signal y′(n) is then provided to the CFAR processor 106c. The CFAR processor 106c is configured to process the pre-processed signal y′(n) to detect the presence of objects in the vicinity of conventional object-detection system 100….the CFAR processor 106c …calculate a threshold for object detection).
Massoud does not explicitly teach a median filter.
However, Damon teaches a median filter (¶0032).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Massoud’s object detection system by incorporating the teaching of Damon as noted above, in order to reduce nose or to remove spurious data in the received signal, as taught by Damon (¶0032).
Regarding claim 6, Massoud teaches the LiDAR system of claim 1, wherein the threshold technique is constant false alarm rate (CFAR) threshold technique (¶0044: the CFAR processor 106c…calculate a threshold for object detection).
Regarding claim 7, Massoud teaches the LiDAR system of claim 6 wherein the processor is further configured to analyze a cell-under-test (CUT) and M reference cells in accordance with the number of reference cells M and the multiplication factor K0 to detect the presence of the object (¶0044: The CFAR processor 106c operates on a cell-under-test (CUT) and M reference cells around CUT, present in the pre-processed signal y′(n). In so doing, the CFAR processor 106c computes an average power of M reference cells and multiplies the average power of M reference cells with a multiplication factor K0 to calculate a threshold for object detection).
Regarding claim 8, the claim is drawn to a method claim and recites the limitation analogous to claim 1, and is rejected due to the same reason set forth above with respect to claim 1.
Regarding claim 13, the claim is drawn to a method claim and recites the limitation analogous to claim 6, and is rejected due to the same reason set forth above with respect to claim 6.
Regarding claim 14, the claim is drawn to a method claim and recites the limitation analogous to claim 7, and is rejected due to the same reason set forth above with respect to claim 7.
Claim(s) 2 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Massoud et al. (US 20210011125 A1) in view of Damon et al. (US 20190367104 A1) as applied to claim 1, and further in view of Tenze et al. (US 20010019633 A1).
Regarding clam 2, Massoud in view of Damon does not teach wherein the pre-processor comprises: a median filter configured to perform median filtering of the digital signal and generate a filtered digital signal; and a subtractor configured to subtract the filtered digital signal from the digital signal and generate the pre-processed signal.
However, Tenze teaches wherein the pre-processor comprises: a median filter configured to perform median filtering of the digital signal and generate a filtered digital signal; and a subtractor configured to subtract the filtered digital signal from the digital signal and generate the pre-processed signal (¶0012, 0022: The noise discriminator 30 comprises a median filter 301, a subtractor 302 and a noise type estimator 303. The median filter 301 filters the input signal x to obtain a filtered version of x, being median(x). The filtered signal median(x) is subtracted from the input signal x…).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Massoud’s object detection system by incorporating the teaching of Tenze as noted above, in order to reduce a noise level in the received signal as taught by Tenze (¶0002).
Regarding claim 9, the claim is drawn to a method claim and recites the limitation analogous to claim 2, and is rejected due to the same reason set forth above with respect to claim 2.
Claim(s) 3, 4, 10 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Massoud et al. (US 20210011125 A1) in view of Damon et al. (US 20190367104 A1) and Tenze et al. (US 20010019633 A1) as applied to claim 2, and further in view of Pacala et al. (US 20190056497 A1).
Regarding claim 3, Massoud in view of Damon and Tenze do not teach wherein the pre-processor is further configured to select a length of a moving window for the median filter in accordance with a pulse width of a transmitted light pulse.
However, Pacala teaches wherein the pre-processor is further configured to select a length of a moving window for the median filter in accordance with a pulse width of a transmitted light pulse (FIG. 22, ¶0253, 0262, 0311: different coarse matched filters 2224, 2234, and 2244 can be used to determine a best match to crossing. The various widths of such filters can be selected based on the widths of the transmitted pulses…).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Massoud’s object detection system by incorporating the teaching of Pacala as noted above, in order to increase the accuracy of the detection system and reduce noise, as taught by Pacala (¶0055).
Regarding claim 4, Massoud in view of Damon, Tenze and Pacala teaches the LiDAR system of claim 3. Pacala further teaches wherein the length of the moving window is longer than the pulse width of the transmitted light pulse (FIG. 22, ¶0253, 0262, 0311: different coarse matched filters 2224, 2234, and 2244 can be used to determine a best match to crossing. The various widths of such filters can be selected based on the widths of the transmitted pulses…). The motivation statement set forth above with respect to claim 3 applies here.
Regarding claim 10, the claim is drawn to a method claim and recites the limitation analogous to claim 3, and is rejected due to the same reason set forth above with respect to claim 3.
Regarding claim 11, the claim is drawn to a method claim and recites the limitation analogous to claim 4, and is rejected due to the same reason set forth above with respect to claim 4.
Claim(s) 5 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Massoud et al. (US 20210011125 A1) in view of Damon et al. (US 20190367104 A1) as applied to claim 1, and further in view of Hofele (US 6040797 A).
Regarding claim 5, Massoud in view of Damon and Pacala does not explicitly teach wherein the threshold technique is an analog threshold technique.
However, Hofele teaches wherein the threshold technique is an analog threshold technique (col. 3, lines 48-57: a radar system receives from a predeterminable measurement window are down-converted into the video range in a manner known per se, resulting in an amplitude-modulated, analog video signal…this signal can subsequently be filtered in analog fashion, for example by means of a threshold circuit…).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Massoud’s object detection system by incorporating the teaching of Hofele as noted above, in order to remove nose components from the analog signal, as taught by Hofele (col. 3, lines 48-57).
Regarding claim 12, the claim is drawn to a method claim and recites the limitation analogous to claim 5, and is rejected due to the same reason set forth above with respect to claim 5.
The following is the prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wintermantel (US 7463181 B2) describes “Method Of Suppressing Interferences In Systems For Detecting Objects” Tile
Conclusion
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/NATHNAEL AYNALEM/Primary Examiner, Art Unit 2488
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