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. Priority Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. JP2022-100232, filed on 6/22/2022. Information Disclosure Statement The information disclosure statement (IDS) submitted on 7/30/2025 and 6/20/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Drawings The drawings on 6/20/2023 are in compliance with the provisions of 37 CFR 1.81. Accordingly, the drawings are being considered by the examiner. Specification The specification submitted on 6/20/2023 are in compliance with the provisions of 37 CFR 1.71. Accordingly, the specification is being considered by the examiner. 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 1-2, and 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Maleki et al. (US 20190154832 A1, "Maleki") Regarding claim 1, a first embodiment of Maleki teaches a LIDAR device comprising: a transmission unit configured to transmit a transmission wave modulated by a modulation in which a sampling interval is to be set (Maleki, Para [0035], Fig 1, where laser 104 serves as the transmission unit with a particular range resolution as disclosed in Para [0096]) ; a scanning unit configured to scan the transmission wave within a predetermined range of a scanning angle (Maleki, Para [0102], Fig 1, where MEMS Mirror 116 serves as the scanning unit scanning in accordance with a designated scan pattern) ; a reception unit configured to receive a reflected wave that is the transmission wave reflected by an object (Maleki, Para [0035], Fig 1, where detector 120 is a photodetector to receive the laser) ; a data conversion unit configured to convert the reflected wave received within the predetermined range of the scanning angle into sampling data ( Maleki, Para [0139], Fig 1, where analog to digital converter (ADC) 124 converts the electrical data into digital data) ; a data holding unit configured to hold the sampling data (Maleki, Para [0141], Fig 1, where the field programmable gate array (FPGA) 126 analyzes the received data and therefore holds it) ; a frequency analysis unit configured to perform frequency analysis on at least one first analysis target data set and a plurality of second analysis target data sets so as to acquire ranging point data including information at least on a distance and a direction of a ranging point with respect to the LIDAR device by using a result of the frequency analysis, the at least one first analysis target data set being obtained by reading the sampling data from the data holding unit for each range of first angle that is equal to or less than the scanning angle (Maleki, Para [0141], Fig 1 where the FPGA 126 is responsible for analyzing the data from a scanning pattern like in Fig 17A-17C by applying a fast Fourier transform algorithm and then further processes the data for position and velocity data as disclosed in Para [0145]) , a point group generator configured to generate a group of a plurality of ranging points indicated by the ranging point data acquired by using the result of the frequency analysis on the first analysis target data set and a group of a plurality of ranging points indicated by the ranging point data acquired by using the result of the frequency analysis on the second analysis target data set (Maleki, Para [0147], Fig 1, where computer 128 receives each pixel of position and velocity data from the FPGA 125 and outputs it in the form of a point cloud) . . However, the first embodiment of Maleki does not teach the plurality of second analysis target data sets being obtained by reading the sampling data for each range of second angle smaller than the first angle. On the other hand, another embodiment of Maleki teaches an adaptive scanning pattern with a smaller amplitude that overlaps with a full scanning pattern (Maleki, Para [0158], Fig 18a-18C where a second scanning pattern with both a full and smaller adaptive scan is performed in a different embodiment, being analyzed resultingly by a different embodiment of FPGA 126). Accordingly, it would have been obvious of one of ordinary skill in the art, before the effective filing date of the invention to have modified the Lidar device of the first embodiment of Maleki in view of a second embodiment of Maleki , by using both scanning patterns such the frequency analysis unit can more sensitively analyze ranging point data . See MPEP 2141.III KSR Rationale D . Regarding claim 2, Maleki teaches the LIDAR device according to claim 1, wherein the plurality of second analysis target data sets includes at least two second analysis target data sets obtained by reading the sampling data for two ranges of the second angle that partially overlap with each other (Maleki, Para [0158], Fig 18a-18C where a second scanning pattern with both a full and smaller adaptive scan is taught, where the smaller scan has a smaller amplitude but is within the full scan pattern) . Regarding claim 7, Maleki teaches the LIDAR device according to claim 1, wherein the frequency analysis unit is configured to set a thinning interval according to a peak frequency of the reflected wave in a result of the frequency analysis on the first analysis target data set (Maleki, Para [0157], where a thinning interval is taught through the fine scan) , and the frequency analysis unit executes the frequency analysis on a plurality of second analysis target thinned data sets obtained by reading the sampling data for each range of the second angle at the thinning interval, instead of the second analysis target data set, to acquire the ranging point data (Maleki, Para [0158], Fig 18a-18C where a second scanning pattern with both a full and smaller adaptive scan is taught. By applying the fine scan repeatedly to the scanning pattern, thinned data sets are apparent) . Regarding claim 8, Maleki teaches the LIDAR device according to claim 7, wherein the plurality of second analysis target thinned data sets includes at least two second analysis target thinned data sets obtained by reading the sampling data for two ranges of the second angle that partially overlap with each other (Maleki, Para [0158], Fig 18a-18C where the smaller scan has a smaller amplitude but is within the full scan pattern) . Claims 3, and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Maleki in view of Russo et al. ( US 20190339389 A1 , " Russo ”). Regarding claim 3, Maleki teaches the LIDAR device according to claim 1 . However, Maleki does not teach the frequency analysis unit is one of a plurality of frequency analysis units, and the plurality of frequency analysis units executes the frequency analysis respectively on the second analysis target data sets different from each other in parallel. On the other hand, Russo teaches a multitude of frequency analyzing units that simultaneously processed received data (Russo, Para [0052], Fig 7a, where there are multiple processing modules 706. Russo, Para [0052], Fig 7a, where there are multiple processing modules 706 that all simultaneously process the received data and send the information to control modules 708). Accordingly, it would have been obvious of one of ordinary skill in the art, before the effective filing date of the invention to have modified the Lidar device of Maleki in view of Russo, by applying the use of multiple processing units to make frequency analysis more efficient. See MPEP 2141.III KSR Rationale D . Regarding claim 9, Maleki teaches the LIDAR device according to claim 7 . However, Maleki does not teach the frequency analysis unit is one of a plurality of frequency analysis units, and the plurality of frequency analysis units executes the frequency analysis respectively on the second analysis target thinned data sets different from each other in parallel. On the other hand, Russo teaches a multitude of frequency analyzing units that simultaneously processed received data (Russo, Para [0052], Fig 7a, where there are multiple processing modules 706. Russo, Para [0052], Fig 7a, where there are multiple processing modules 706 that all simultaneously process the received data and send the information to control modules 708). Accordingly, it would have been obvious of one of ordinary skill in the art, before the effective filing date of the invention to have modified the Lidar device of Maleki in view of Russo, by applying the use of multiple processing units to make frequency analysis more efficient. See MPEP 2141.III KSR Rationale D. Claims 4- 6 are rejected under 35 U.S.C. 103 as being unpatentable over Maleki in view of Russo, and Sakamoto (US 20090096661 A1 "Sakamoto”). Regarding claim 4, Maleki teaches the LIDAR device according to claim 1 . However, Maleki does not teach when a peak intensity of the reflected wave in the result of the frequency analysis on the first analysis target data set is equal to or greater than a preset threshold value, On the other hand, Sakamoto teaches the adjustment of using data if an intensity threshold is met (Sakamoto, Para [0159], Fig 6, where if a peak matching a threshold intensity is found, then an adjusted smaller value is used) . However, Maleki in view of Sakamoto still does not teach the frequency analysis unit executes the frequency analysis on a plurality of third analysis target data sets obtained by reading the sampling data for each range of third angle smaller than the second angle, instead of the second analysis target data set, to acquire the ranging point data On the other hand, Russo teaches a smaller scanning pattern that can be used when an intensity threshold is met (Russo Para [0043], Fig 4B, where by using the scan pattern disclosed, in which a smaller scanning pattern (as compared to Russo 4A) is taught, the frequency analysis from Sakamoto, Para [0159] can be enacted on a third angle range smaller than the second angle). Accordingly, it would have been obvious of one of ordinary skill in the art, before the effective filing date of the invention to have modified the Lidar device of Maleki in view of Sakamoto and Russo , by applying the technique of adjusting the use of data when a threshold is met by going through alternative data scanned at a smaller angle that meets the threshold requirement. See MPEP 2141.III KSR Rationale D . Regarding claim 5, Maleki in view of Sakamoto and Russo teaches the LIDAR device according to claim 4, wherein the plurality of third analysis target data sets includes at least two third analysis target data sets obtained by reading the sampling data for two ranges of the third angle that partially overlap with each other (Maleki, Para [0158], Fig 18a-18C where a scanning pattern with both a full and smaller adaptive scan is taught, where the smaller scan has a smaller amplitude but is within the full scan pattern. This could be applied to the smaller scan pattern disclosed in Russo, Para [0043]). Regarding claim 6, Maleki in view of Sakamoto and Russo teaches the LIDAR device according to claim 4, wherein the frequency analysis unit is one of a plurality of frequency analysis units (Russo, Para [0052], Fig 7a, where there are multiple processing modules 706) , and the plurality of frequency analysis units executes the frequency analysis respectively on the third analysis target data sets different from each other in parallel (Russo, Para [0052], Fig 7a, where there are multiple processing modules 706 that all simultaneously process the received data and send the information to control modules 708) . Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT ZAKI HAWKINS whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)272-6595 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT Monday-Friday 7:30am-5pm . Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, FILLIN "SPE Name?" \* MERGEFORMAT YUQING XIAO can be reached at FILLIN "SPE Phone?" \* MERGEFORMAT (571) 270-3603 . The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ZAKI KEHINDE HAWKINS/ Examiner, Art Unit 3645 /YUQING XIAO/ Supervisory Patent Examiner, Art Unit 3645