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 .
Examiner’s Note
According to claims 1 and 12, applicants are claiming, “presence or absence of an object”. If the object is present the steps performed in independent claims does makes sense, but if the object is absence accordingly none of the following steps are required to perform. The specification does not clarifies what happens if the object is absent.
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.
Claim 15 is rejected under 35 U.S.C. 101 because the invention is directed to non-statutory subject matter.
Claim 15 claims a computer-readable recording medium, however, the specification does not positively limit the computer-readable storage medium to be statutory subject matter (see page 13, lines 18 – 22 also page 14, lines 2 - 6a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD/CD-ROM drive, a memory card, or the like). Therefore, claim 15 is rejected under 35 U.S.C. 101, because a claim that covers both statutory and non-statutory embodiments (under the broadest reasonable interpretation of the claim when read in light of the specification and in view of one skilled in the art) embraces subject matter that is not eligible for patent protection and therefore is directed to non-statutory subject matter. See the OG Notice titled "Subject Matter Eligibility of Computer Readable Media".
An amendment to these claims adding --non-transitory-- before “computer-readable recording medium” would overcome this rejection.
Double Patenting (Statuary)
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1 -15 are provisionally rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 1 - 15 of copending Application No. 18/955,859 (reference application). This is a provisional statutory double patenting rejection since the claims directed to the same invention have not in fact been patented.
Claim 1 of application 18/954,384 is as below:
A method of tracking an object location based on beamforming, comprising:
in a first scan mode for determining presence or absence of an object, determining a first angle change vector of a beam for scanning a three-dimensional space;
scanning the three-dimensional space while changing at least one of an azimuth angle and an elevation angle at which the beam is radiated in the three-dimensional space based on the first angle change vector;
constructing a first data set for input into an object tracking model based on a first received signal generated by reflection of the beam; and
inputting the first data set into the object tracking model and obtaining object presence or absence information based on first output data of the object tracking model.
Claim 1 of application 18/955,859 is as below:
A method of tracking an object location based on beamforming, comprising:
in a first scan mode for determining presence or absence of an object, determining a first angle change vector of a beam for scanning a three-dimensional space;
scanning the three-dimensional space while changing at least one of an azimuth angle and an elevation angle at which the beam is radiated in the three-dimensional space based on the first angle change vector;
constructing a first data set for input into an object tracking model based on a first received signal generated by reflection of the beam; and
inputting the first data set into the object tracking model and obtaining object presence or absence information based on first output data of the object tracking model.
Here, claim 1 of both the applications are identical.
Dependent claims 2 – 11 and 15 do not overcome statutory double patenting rejections.
Claim 12 of application 18/954,384 is as below:
An apparatus for tracking an object location based on beamforming, comprising: at least one memory; and
at least one processor, wherein the processor is configured to:
in a first scan mode for determining presence or absence of an object,
determine a first angle change vector of a beam for scanning a three-dimensional space;
scan the three-dimensional space while fixing one of an azimuth angle and an elevation angle at which the beam is radiated in the three-dimensional space and changing the other based on the first angle change vector;
construct a first data set for input into an object tracking model based on a first received signal generated by reflection of the beam; and
input the first data set into the object tracking model and obtain object presence or absence information based on first output data of the object tracking model.
Claim 12 of application 18/955,859 is as below:
An apparatus for tracking an object location based on beamforming, comprising: at least one memory; and
at least one processor, wherein the processor is configured to:
in a first scan mode for determining presence or absence of an object,
determine a first angle change vector of a beam for scanning a three-dimensional space;
scan the three-dimensional space while fixing one of an azimuth angle and an elevation angle at which the beam is radiated in the three-dimensional space and changing the other based on the first angle change vector;
construct a first data set for input into an object tracking model based on a first received signal generated by reflection of the beam; and
input the first data set into the object tracking model and obtain object presence or absence information based on first output data of the object tracking model.
Here, claim 12 of both the applications are identical.
Dependent claims 13 and 14 do not overcome statutory double patenting rejections.
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.
Claims 1, 3, 4, 12 and 15 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable by
Choi US PGPub: US 2021/0149037 A1 May 20, 2021.
Regarding claims 1, 12, Choi discloses,
a method of tracking an object location based on beamforming and an apparatus for tracking an object location based on beamforming (Figs. 3/300, 10/1000), comprising: at least one memory (storage 1020 – Fig. 10/1020); and at least one processor (processor 1010 – Figs. 3/320, 10/1010), wherein the processor is configured to: (a method with three-dimensional 3D position measuring using a radio detection and ranging radar sensor includes: transmitting, through the radar sensor, a transmission signal of which a carrier frequency varies over time; obtaining, through the radar sensor, a reflected signal from the transmission signal being reflected by an object; obtaining a beat frequency signal indicating a frequency difference between the transmission signal and the reflected signal; and estimating 3D position information of the object based on groups of sample data of different frequency bands extracted from the beat frequency signal – ABSTRACT, Figs. 1a – 10, paragraphs 0006 - 0014. The estimating of the azimuth may include estimating the azimuth through digital beamforming for estimating a direction in which the reflected signal is received based on a difference occurring among the beat frequency signals – paragraphs 0015, 0024. The 3D position measuring apparatus 100 may estimate a distance from the 3D position measuring apparatus 100 to the object present nearby, and an azimuth corresponding to a position of the object in a horizontal direction or a horizontal angle – paragraph 0050), comprising:
in a first scan mode for determining presence or absence of an object (the radar sensor may include an antenna that has a frequency scanning characteristic – paragraph 0087),
determining a first angle change vector of a beam for scanning a three-dimensional space (estimate the 3D position information by estimating an elevation angle with respect to a position of the object based on a change of a center direction of the transmission signal for each of the respective frequency bands of the transmission signal – Fig. 2, paragraphs 0011, 0027, 0052. The processor 320 may estimate the elevation angle with respect to the position of the object using a characteristic of a change of a center direction of the transmission signal for each frequency band – paragraph 0061);
scanning the three-dimensional space while changing at least one of an azimuth angle and an elevation angle at which the beam is radiated in the three-dimensional space based on the first angle change vector (a change of a center direction of a transmission signal in a vertical direction according to a frequency band. A radar sensor 200 used by a 3D position measuring apparatus may transmit an FMCW transmission signal of which a frequency varies over time. A center direction of the transmission signal of the radar sensor 200 may vary in a vertical direction based on a frequency band. The vertical direction may correspond to a direction perpendicular to a horizontal plane - Fig. 2, paragraph 0052);
constructing a first data set for input (analyzing the radar data sensed through the radar sensor 310 – paragraph 0058) into an object tracking model (the processor 320 may estimate 3D position information and/or a velocity of the object by analyzing the radar data sensed through the radar sensor 310 – paragraph 0058) based on a first received signal generated by reflection of the beam (the processor 320 may estimate the elevation angle with respect to the position of the object using a characteristic of a change of a center direction of the transmission signal for each frequency band – Figs. 2, 8, 9, paragraphs 0061. The 3D position measuring apparatus obtains a beat frequency signal indicating a frequency difference between the transmission signal and the reflected signal. For example, the 3D position measuring apparatus may calculate a beat frequency signal for each of reception channels respectively corresponding to the receiving antennas – paragraph 0107); and
inputting the first data set into the object tracking model (the 3D position measuring apparatus obtains a beat frequency signal – i.e., inputting, indicating a frequency difference between the transmission signal and the reflected signal. For example, the 3D position measuring apparatus may calculate a beat frequency signal for each of reception channels respectively corresponding to the receiving antennas – paragraph 0107) and obtaining object presence or absence information based on first output data of the object tracking model (the 3D position measuring apparatus estimates 3D position information of the object based on the beat frequency signal. For example, the 3D position measuring apparatus may estimate the 3D position information of the object based on groups of sample data of different frequency bands that are extracted from the beat frequency signal – paragraph 0107).
Regarding claim 3, Choi discloses,
the method of claim 1, wherein the scanning of the three-dimensional space includes adjusting a phase of a signal output from each of a plurality of antennas forming the beam, and changing the azimuth angle or the elevation angle at which the beam is radiated based on the first angle change vector (a change of a center direction of a transmission signal in a vertical direction according to a frequency band. – Fig. 2, paragraphs 0052, 0053, 0061, 0087).
Regarding claim 4, Choi discloses,
the method of claim 1, wherein the constructing of the first data set includes: converting the first received signal received by a plurality of antennas forming the beam into a digital signal (the processor 320 may sample the beat frequency signal at the sample points, and obtain the groups of sample data by performing analog-to-digital conversion that converts a sampled analog signal value to a corresponding digital signal – paragraphs 0060, 0108); and
combining the digital signals corresponding to each of the plurality of antennas to form the first data set the processor 320 may sample the beat frequency signal at the sample points, and obtain the groups of sample data by performing analog-to-digital conversion that converts a sampled analog signal value to a corresponding digital signal – paragraphs 0060, 0108).
Regarding claim 5, Choi discloses,
the method of claim 1, further comprising storing the azimuth angle and the elevation angle corresponding to the beam reflected from the object as a criterion azimuth angle and a criterion elevation angle when it is determined that the object is present in the three-dimensional space.
Regarding claim 15, Choi discloses,
a computer-readable recording medium on which a program for causing the method according to claim 1 to be executed by a computer is recorded (a non-transitory computer-readable storage medium stores instructions that, when executed by a processor, cause the processor to perform the method – paragraph 0017).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 nonobviousness.
Claims 2, 3 are rejected under 35 U.S.C. 103 as being unpatentable over
Choi US PGPub: US 2021/0149037 A1 May 20, 2021 and in view of
Narayanan US PGPub: US 2024/0312188 A1 Sep. 19, 2024.
Regarding claim 2, Choi discloses,
the method of claim 1, wherein a scan range in the first scan mode is limited depending on a location in a three-dimensional world coordinate system.
Narayanan teaches, adaptive region-based object sampling for object detection, where a light detection and ranging LIDAR system scans - e.g., across azimuth and elevation, an environment using one or more lasers and calculates distances between the LIDAR system and objects in the environment based on laser light reflected by the objects - e.g., using a time-of-flight TOF or indirect time-of-flight technique. Data from a LIDAR system captured at a given time can be referred to herein as a “LIDAR capture.” A LIDAR capture can include spatial data including three-dimensional coordinates - e.g., a point cloud, representing objects in the environment. The three-dimensional coordinates can be derived from the calculated distances between the LIDAR system and the objects at a number of respective azimuth and elevation angles (paragraph 0002).
An augmenter 206 can generate ten LIDAR-based representations of an object - e.g., a car, a tree, or a person, with each LIDAR-based representation representing the object at a different location - e.g., distance, azimuth, and/or elevation relative to a LIDAR system within the environment and having a different orientation (paragraph 0040).
A neural network 600 - e.g., a deep-learning neural network, that can be used to implement the object detection and/or object classification (paragraphs 0003, 0004, 0095, 0097).
The systems and techniques can, in some instances, limit an amount of occlusion of added LIDAR-based representations by other objects - e.g., including by objects in the LIDAR captures and by objects represented by added LIDAR-based representations. For example, augmenter 206 may add a number LIDAR-based representations into a LIDAR capture, then determine whether an overlap or unwanted occlusion has occurred (paragraph 0041).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify a method with three-dimensional 3D position measuring using a radio detection and ranging radar sensor of Choi (Choi, ABSTRACT, Figs. 1a – 10, paragraphs 0006 – 0015, 0024, 0050) wherein the system of Choi, would have incorporated the object detection and/or object classification of Narayanan (Narayanan, paragraphs 0003, 0004, 0041, 0095, 0097) for an automated vehicle can include a processor and a memory that can implement a trained machine-learning model to detect objects – e.g., location and classification information, within the environment based on the LIDAR captures, that the automated vehicle can use information regarding the detected objects when controlling the vehicle (Narayana, paragraphs 0003 – 0005).
Regarding claim 3, Choi discloses all the claimed features,
but, does not disclose, the method of claim 1, wherein the object tracking model includes a model that estimates an object type based on the first data set.
Narayanan teaches, adaptive region-based object sampling for object detection, where a light detection and ranging LIDAR system scans - e.g., across azimuth and elevation, an environment using one or more lasers and calculates distances between the LIDAR system and objects in the environment based on laser light reflected by the objects - e.g., using a time-of-flight TOF or indirect time-of-flight technique. Data from a LIDAR system captured at a given time can be referred to herein as a “LIDAR capture.” A LIDAR capture can include spatial data including three-dimensional coordinates - e.g., a point cloud, representing objects in the environment. The three-dimensional coordinates can be derived from the calculated distances between the LIDAR system and the objects at a number of respective azimuth and elevation angles (paragraph 0002).
An augmenter 206 can generate ten LIDAR-based representations of an object - e.g., a car, a tree, or a person, with each LIDAR-based representation representing the object at a different location - e.g., distance, azimuth, and/or elevation relative to a LIDAR system within the environment and having a different orientation (paragraph 0040).
A neural network 600 - e.g., a deep-learning neural network, that can be used to implement the object detection and/or object classification (paragraphs 0003, 0004, 0095, 0097).
The systems and techniques can, in some instances, limit an amount of occlusion of added LIDAR-based representations by other objects - e.g., including by objects in the LIDAR captures and by objects represented by added LIDAR-based representations. For example, augmenter 206 may add a number LIDAR-based representations into a LIDAR capture, then determine whether an overlap or unwanted occlusion has occurred (paragraph 0041).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify a method with three-dimensional 3D position measuring using a radio detection and ranging radar sensor of Choi (Choi, ABSTRACT, Figs. 1a – 10, paragraphs 0006 – 0015, 0024, 0050) wherein the system of Choi, would have incorporated the object detection and/or object classification of Narayanan (Narayanan, paragraphs 0003, 0004, 0041, 0095, 0097) for an automated vehicle can include a processor and a memory that can implement a trained machine-learning model to detect objects – e.g., location and classification information, within the environment based on the LIDAR captures, that the automated vehicle can use information regarding the detected objects when controlling the vehicle (Narayana, paragraphs 0003 – 0005).
Allowable Subject Matter
Claims 5 - 11, 13 and 14 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, along with 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).
The prior arts made of record and not relied upon are considered pertinent to applicants disclosure.
Byun US PGPub: US 2026/0098954 A1 Apr. 9, 2026.
A method of tracking an object location based on beamforming according to an embodiment of the present disclosure may include, in a first scan mode for determining presence or absence of an object, determining a first angle change vector of a beam for scanning a three-dimensional space, scanning the three-dimensional space while changing at least one of an azimuth angle and an elevation angle at which the beam is radiated in the three-dimensional space based on the first angle change vector, constructing a first data set for input into an object tracking model based on a first received signal generated by reflection of the beam, and inputting the first data set into the object tracking model and obtaining object presence or absence information based on first output data of the object tracking model.
Huang US PGPub: US 2024/0310506 A1 Sep. 19, 2024.
Radar system and method for scanning objects. The radar system includes a first subarray, a second subarray, and a third subarray. Antennas in the first subarray and the second subarray are disposed along a first axis, and antennas in the third subarray are disposed along a second axis. When scanning a radar coverage of the radar system, the radar system utilizes the first subarray and the second subarray as RF signal transceivers and utilizes the third subarray as a RF signal receiver to scan a first detection distance range according to first signal parameters and scan a second detection distance range according to second signal parameters. A maximum distance measured from the radar system to each detectable location in the first detection distance range is less than or equal to a minimum distance measured from the radar system to each detectable location in the second detection distance range.
Meyer US PGPub: US 2025/0028041 A1 Jan. 23, 2025.
Systems and methods for online calibration in distributed aperture radar, where a distributed aperture radar (DAR) system that includes multiple radar sensors. A graph neural network (GNN) is employed to cause radar data output by the multiple radar sensors to correspond to a same coordinate system.
Bialer US PGPub: US 2020/0393540 A1 Dec. 17, 2020.
A vehicle, radar system of the vehicle and method of determining an elevation of an object. The radar system includes a transmitter that transmits a reference signal and a receiver that to receive at least one echo signal related to reflection of the reference signal from an object. The receiver includes an antenna array having a plurality of horizontally-spaced antenna elements. A processor determines a first uncertainty curve associated with an azimuth measurement related to the at least one echo signal, determines a second uncertainty curve associated with a Doppler measurement and a velocity measurement related to the at least one echo signal, and locates an intersection of the first uncertainty curve and the second uncertainty curve to determine the elevation of the object.
Beyer US Patent: 4,531,125 Jul. 23, 1985.
A three-dimensional air space surveillance radar in which the radar receiver is connected to a target tracking means which stores target data and does extrapolation of target data for target trace formations, including a panoramic antenna which illuminates the entire elevation range to be covered and has a reception lobe at the elevation level which can be electronically or mechanically controlled such that a line air space scanning occurs during the course of normally sequence scanning programs.
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/NIMESH PATEL/Primary Examiner, Art Unit 2642
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