DETAILED ACTION
Status of Claims
Claims 1, 5, 8, 12, 15, 19 are amended.
Claims 1-2, 4-9, 11-16, 18-20 are pending.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 07/08/2026 has been entered.
Priority
Applicant’s claim for the benefit of a prior-filed application filed in EP 23200857.3 on 09/29/2023 under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
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, 4-9, 11-16, 18-20are rejected under 35 U.S.C. 103 as being unpatentable over Emadi (US 20240111043) in view of Liu (US 20200103523).
Regarding Claims 1, 8, 15, Emadi teaches the following limitations:
A method performed by a radar system, the method comprising: (Emadi - [0005] In another implementation, a method is provided including receiving radar returns from objects in response to radar scans of transmitted radar signals from a radar system,)
(Claim 8) A radar system comprising: a radar sensor; and circuitry configured to perform acts comprising: (Emadi - [0004] In an implementation, a system is provided including one or more processors and one or more machine-readable media storing instructions which, when executed by the one or more processors, cause the one or more processors to receive radar returns from objects in response to radar scans of transmitted radar signals from the radar system,)
(Claim 15) A radar analysis system comprising: one or more processors configured to perform acts comprising: (Emadi - [0004])
receiving radar sensor data from a radar sensor; (Emadi - [0005])
detecting static objects in the radar sensor data; (Emadi - [0005] each of the groups having predetermined minimum velocity value Vmin, a predetermined maximum velocity value Vmax, and a predetermined threshold velocity difference value between Vmin and Vmax, and determining which of the objects are static objects based on determining which group of the plurality of groups has highest number of adjusted radar returns.)
calculating cell parameters related to the static objects for a given radar cell, the cell parameters including a minimum residual velocity value for the given radar cell, (Emadi - [0003] when the radar system itself is moving, even static objects will have non-zero doppler and will appear to be moving. Therefore, it is impossible to separate static and dynamic objects by just checking if doppler velocity is 0. Emadi does not explicitly teach “radar cell”.)
wherein the cell parameters include a minimum frame time for static object detections in the given radar cell; (Emadi – [0038] This algorithm 700 is based on a solution that compares car speed change between two or more subsequent subframes and evaluates if this change is valid. Emadi does not explicitly teach “radar cell”.)
generating a two-dimensional (2D) cell map grid representing three-dimensional (3D) radar cells including the given radar cell; (Emadi does not explicitly teach “radar cell”.)
calculating an average residual velocity of the static object detections in the given radar cell; (Emadi – [0036] As described above with reference to steps 350 and 360 of FIG. 3, once it is determined which objects are static using the grouping algorithm 400, one can easily determine car speed of the car that the moving radar system 102 is mounted, and the speed of other nearby moving objects (e.g., other cars, trucks, etc., in the vicinity) by simply calculating an average for all car speeds from the static points speed group (e.g., Group 2 in the specific example of FIG. 5). Emadi does not explicitly teach “radar cell”.)
comparing the calculated cell parameters for the given radar cell to respective threshold values; (Emadi - [0005])
assigning weight scores to the cell parameters based on the threshold comparison; (Emadi – [Fig. 5], [0032] In step 410 a group array of speed groups (which can be continuous adjoining speed groups, if desired) is created, with each speed group having a minimum adjusted Doppler velocity Vmin, a maximum adjusted Doppler velocity Vmax, and a step threshold Vthreshold between Vmin and Vmax. A point counter is provided for each of the speed groups which counts a list of points that are assigned to each speed group based on the adjusted Doppler velocities for each of the detected objects in a radar scan (comprised of all of the returns received from objects for transmission of a plurality of radar signals 110 and 112 in one radar scan). If the speed groups are continuous, the Vmax for one group will be the Vmin for the adjacent higher speed group.)
summing the weight scores assigned to the cell parameters to generate a combined score; (Emadi – [Fig. 5], [0032] [0034] Group 2 has the maximum number of points with 23 points, which is many more points than any of the other groups. Since it is known that there are many more static objects 106 in the environment of a car (or robot, or any other vehicle that moves on or close to the ground), this means all points in Group 2 that have calculated speed v>9 and v<10 are static objects 106. As such, use of the grouping algorithm 400 of FIG. 4 provides a highly accurate and convenient approach to achieve segmentation between static and dynamic objects using returns from a moving radar system.)
comparing the combined score to a probability threshold; and (Emadi – [Fig. 5], [0032] [0034] Emadi does not explicitly teach “probability threshold”.)
outputting an indication that the cell is occupied or not occupied based on the comparison of the combined score to the probability threshold. (Emadi does not explicitly teach this limitation.)
Emadi does not explicitly teach the following limitations, however Liu, in the same field of endeavor, teaches:
generating a two-dimensional (2D) cell map grid representing three-dimensional (3D) radar cells including the given radar cell; (Liu – [Fig. 1], [0014] Occupied: Cells of the radar spatial grid may be designated as being occupied by mapping radar sensor data (e.g., radar returns) of the environment to corresponding cells of the radar spatial grid. In some examples, the radar spatial grid may indicate, for occupied cells, whether the cell is occupied by a static object (e.g., a building, parked vehicle, vegetation, etc.) or a dynamic object (e.g., vehicle, bicycle, pedestrian, etc.). In the case of a static radar object static radar return having zero velocity is received. A first cell of the radar spatial grid associated with the location of the radar return is designated as being occupied. Occupancy probabilities can be computed for cells adjacent to the first cell based on the static radar return and historical returns. Each adjacent cell having an occupancy probability above a threshold probability can be designated as being occupied.)
outputting an indication that the cell is occupied or not occupied based on the comparison of the combined score to the probability threshold. (Liu – [0014])
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the calculations of Emadi with the radar spatial grids and occupancy probabilities of Liu in order to determine if a cell is occupied by an object (Liu – [0014]).
Regarding Claims 2, 9, 16, Emadi further teaches:
further comprising performing egomotion compensation on the received radar sensor data prior to detecting the static objects. (Emadi – [0006] In another implementation, a system to segment static objects from dynamic moving objects using a radar system including a transmitter and a receiver mounted on a moving platform,)
Regarding Claims 4, 11, 18, Emadi further teaches:
further comprising calculating as a cell parameter a minimum residual velocity of a given static object detection in the given cell based on the average residual velocity and a detected residual velocity of the given static object. (Emadi – [0036])
Emadi does not explicitly teach the following limitations, however Liu, in the same field of endeavor, teaches:
radar cell (Liu – [Fig. 1], [0014])
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the calculations of Emadi with the radar spatial grids and occupancy probabilities of Liu in order to determine if a cell is occupied by an object (Liu – [0014]).
Regarding Claims 5, 12, 19, Emadi further teaches:
wherein the cell parameters further include one or more of: a number of static object detections in the given radar cell; (Emadi – [0005]) (Emadi does not explicitly teach this limitation.)
a maximum signal-to-noise ratio for static objects in the given radar cell; or (Emadi – [0005]) (Emadi does not explicitly teach this limitation.)
a maximum radar cross section value for static objects in the given radar cell. (Emadi – [0005]) (Emadi does not explicitly teach this limitation.)
Emadi does not explicitly teach the following limitations, however Liu, in the same field of endeavor, teaches
wherein the cell parameters include one or more of: a number of static object detections in the given radar cell; (Liu – [Fig. 1], [0014])
a maximum signal-to-noise ratio for static objects in the given radar cell; a maximum radar cross section value for static objects in the given radar cell; or (Liu – [Fig. 1], [0014] SNR is the measurement of a RCS of a radar return.)
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the calculations of Emadi with the radar spatial grids and occupancy probabilities of Liu in order to determine if a cell is occupied by an object (Liu – [0014]).
Regarding Claims 6, 13, 20, Emadi further teaches:
further comprising outputting an indication that the cell is occupied when the combined score is greater than the probability threshold. (Emadi – [Fig. 5], [0032] [0034])
Emadi does not explicitly teach the following limitations, however Liu, in the same field of endeavor, teaches:
radar cell… occupancy probability (Liu – [Fig. 1], [0014])
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the calculations of Emadi with the radar spatial grids and occupancy probabilities of Liu in order to determine if a cell is occupied by an object (Liu – [0014]).
Regarding Claims 7, 14, Emadi further teaches:
performed on a frame-by-frame basis. (Emadi – [0038])
Response to Arguments
Applicant’s arguments, see Pages 9-12, filed 06/12/2026, with respect to the rejection under 35 U.S.C. § 103 have been fully considered and are not persuasive. Applicant argues, see pages 10-11, that the combination of Emandi and Liu does not teach “wherein the cell parameters include a minimum frame time for static object detections in the given radar cell”. The examiner disagrees, Emadi – [0038] teaches an algorithm that arrives at a solution with two or more subsequent subframes and requires at least two subframes. This makes sense because a change of speed requires a change in distance over time and to validate if an object is static or not requires at least two measurements when considering the static and dynamic measurements of Emandi as a whole. The BRI of the limitation allows the time between two subsequent subframes to map to “a minimum frame of time for static object detections”. The combination of Emandi and Liu makes this limitation obvious in terms of a given radar cell as cited in the office action.
Applicant’s arguments, see Page 11-12, filed 06/12/2026, with respect to the rejection under 35 U.S.C. § 103 have been fully considered and are not persuasive. Applicant argues that the dependent claims are allowable due to the dependency on the independent claims. As noted above, the examiner maintains Emandi in view of Liu teaches the independent claims and therefore the dependent claims remain rejected.
Applicant's remaining arguments amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims is understandable and distinguishable from other inventions.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRANDON JAMES HENSON whose telephone number is (703)756-1841. The examiner can normally be reached Monday-Friday 9:00 am - 5:00 pm.
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/BRANDON JAMES HENSON/Examiner, Art Unit 3648
/BERNARR E GREGORY/Primary Examiner, Art Unit 3648
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