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 .
Claim Objections
Claims 11-12 and 16 are objected to for the following informalities:
In Claim 11, line 2, the word “determining” should be “determine.”
In Claim 12, line 3, the word “and” should be “an.”
In Claim 16, line 1, remove the additional comma.
Appropriate correction is required.
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.
(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 1-5 and 8-12 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Long (Long et al., “Full-Velocity Radar Returns by Radar-Camera Fusion,” 2021).
Regarding Claim 1, Long discloses: A method of operating a host vehicle, comprising:
receiving a first detection of a first reflection point from an object during a first time frame of a radar ([pg. 2]: “radar points”; “object detection”);
determining a first position and a first Doppler frequency of the first detection ([pg. 1]: “3D positions”; “Doppler effect”; [pg. 4]: “Radar provides an estimate of the target position, q … Radar also provides the signed radial speed, ṙ”);
updating the first position to a first predicted position in a second time frame using the first Doppler frequency ([pg. 7]: “The point-wise velocity estimate makes it possible to compensate the motion of dynamic objects”; Eq. 19; “Then p0 is transformed to current radar coordinates by known egomotion”), wherein updating includes:
determining an object-based component of the first Doppler frequency for the first detection from the first Doppler frequency by removing an effect of a velocity of the host vehicle from the first Doppler frequency ([pg. 4]: “Now Eq.(7) is actually the egomotion-corrected Doppler speed.”; “The raw Doppler speed, ṙraw, is the radial component of the relative velocity between target and sensor, ṁ – ċ”; “ċ is the known ego-velocity”);
shifting the first detection from the first position to an intermediate position in the second time frame using the object-based component of the first Doppler frequency ([pg. 7]: “compensate the motion of dynamic objects”; Eq. 19; Examiner note: The detection point is shifted from first position pi to intermediate position p0 in Eq. 19.);
shifting the first detection from the intermediate position to the first predicted position in the second time frame using a vehicle-based component of the first Doppler frequency ([pg. 7]: “Then p0 is transformed to current radar coordinates by known egomotion”; Examiner note: Then the detection point is shifted by a vehicle-based component.);
receiving a second detection of a second reflection point from the object ([pg. 2]: “To align radar frames, in addition to compensating egomotion, we shall consider the motion of moving points in consecutive frames”); and
detecting the object from the first predicted position in the second time frame and the second detection ([pg. 2]: “it is often essential to accumulate multiple prior radar frames to acquire sufficiently dense point clouds for downstream tasks, e.g., object detection.”; Fig. 6).
Regarding Claim 8, Long discloses: A system for operating a host vehicle, comprising:
a processor ([pg. 5]: “compute”; [pg. 7]: “processing”) configured to:
receive a first detection of a first reflection point from an object during a first time frame of a radar ([pg. 2]);
determine a first position and a first Doppler frequency of the first detection ([pg. 1]; [pg. 4]);
update the first position to a first predicted position in a second time frame using the first Doppler frequency ([pg. 7]), wherein updating includes:
determining an object-based component of the first Doppler frequency for the first detection from the first Doppler frequency by removing an effect of a velocity of the host vehicle from the first Doppler frequency ([pg. 4]);
shifting the first detection from the first position to an intermediate position in the second time frame using the object-based component of the first Doppler frequency ([pg. 7]);
shifting the first detection from the intermediate position to the first predicted position in the second time frame using a vehicle-based component of the first Doppler frequency ([pg. 7]);
receive a second detection of a second reflection point from the object ([pg. 2]); and
detect the object from the first predicted position in the second time frame and the second detection ([pg. 2]; Fig. 6).
Regarding Claims 2 and 9, Long discloses: the method further comprising:
receiving the second detection of the second reflection point from the object during the first time frame ([pg. 2]: “single frame”; “at least two radar hits”; [pg. 7]: “radar hits acquired in a single sweep”; “point-wise”);
determining a second position of the second detection and a second Doppler frequency for the second detection ([pg. 1]: “3D positions”; “Doppler effect”; [pg. 2]: “point-wise”);
updating the second position to a second predicted position in the second time frame based on calculations using the second Doppler frequency ([pg. 7]: Eq. 19; “transformed to current radar coordinates by known egomotion”); and
detecting the object from the first predicted position in the second time frame and the second predicted position in the second time frame ([pg. 2]: “accumulate multiple prior radar frames”; “object detection.”; Fig. 6).
Regarding Claims 3 and 10, Long discloses: the method further comprising updating the first predicted position in the second time frame to a second predicted position in a third time frame based on a first calculation using the first Doppler frequency and the velocity of the host vehicle obtained in the second time frame ([pg. 2]: “multiple prior radar frames”; [pg. 7]: Eq. 19; “known egomotion”; “up to 25 frames”).
Regarding Claims 4 and 11, Long discloses: the method further comprising receiving the second detection within the second time frame, determining a second position of the second detection and a second Doppler frequency for the second detection in the second time frame ([pg. 2]: “consecutive frames”; “point-wise”), and updating the second position to a third predicted position in the third time frame using a second calculation based on the second Doppler frequency ([pg. 7]: Eq. 19; “known egomotion”; “up to 25 frames”).
Regarding Claims 5 and 12, Long discloses: wherein detecting the object further comprises determining at least one of: (i) a position of the object; (ii) a shape of the object; (iii) an orientation of the object; and (iv) a class of the object ([pg. 7]: “we apply a pose estimation method”).
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.
Claims 6-7 and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Long (Long et al., “Full-Velocity Radar Returns by Radar-Camera Fusion,” 2021) in view of Abbott (US 2024/0280372).
Regarding Claims 6, 13, and 20, Long teaches: wherein the first time frame is one of a plurality of temporally-spaced time frames ([pg. 2]: “multiple prior radar frames”; “consecutive frames”; [pg. 7]: “25 frames”).
Long generally teaches the idea of selecting a subset of frames and accumulating prior and consecutive frames ([pg. 2]: “multiple prior radar frames”; “consecutive frames”; “carefully decide the number of frames”; [pg. 7]: “error increases with the number of frames”), but does not explicitly teach: selecting a subset of the plurality of temporally-spaced time frames using a moving time window.
Abbott teaches: selecting a subset of the plurality of temporally-spaced time frames using a moving time window (Abbott [0040]: “sliding window of multiple frames may be used to build a dense 3D point cloud”).
It would have been obvious to one of ordinary skill in the art to modify Long and select a subset of frames using a moving time window, as taught by Abbott. Moving time windows are considered ordinary and well-known in the art, and they are beneficial for reducing error and improving detection.
Regarding Claims 7 and 14, Long does not explicitly teach – but Abbott teaches: the method further comprising controlling the host vehicle to navigate the host vehicle with respect to the object based on the first predicted position and the second detection (Abbott [0075]: “”).
It would have been obvious to one of ordinary skill in the art to modify Long and navigate the host vehicle with respect to the object, as taught by Abbott. The disclosure of Long is directed to autonomous driving, and navigating a vehicle based on detections is considered ordinary and well-known in the art. Navigating the host vehicle with respect to the object is beneficial for enabling safer vehicle operation.
Regarding Claim 15, Long teaches: A host vehicle, comprising:
…
a processor ([pg. 5]: “compute”; [pg. 7]: “processing”) configured to:
receive a first detection of a first reflection point from an object during a first time frame of a radar ([pg. 2]);
determine a first position and a first Doppler frequency of the first detection ([pg. 1]; [pg. 4]);
update the first position to a first predicted position in a second time frame using the first Doppler frequency ([pg. 7]), wherein updating includes:
determining an object-based component of the first Doppler frequency for the first detection from the first Doppler frequency by removing an effect of a velocity of the host vehicle from the first Doppler frequency ([pg. 4]);
shifting the first detection from the first position to an intermediate position in the second time frame using the object-based component of the first Doppler frequency ([pg. 7]);
shifting the first detection from the intermediate position to the first predicted position in the second time frame using a vehicle-based component of the first Doppler frequency ([pg. 7]);
receive a second detection from a second reflection point from the object ([pg. 2]);
detect the object from the first predicted position in the second time frame and the second detection ([pg. 2]; Fig. 6); and …
Long does not explicitly teach – but Abbott teaches: a system for controlling navigation of the host vehicle and control the system to navigate the host vehicle with respect to the object (Abbott [0075]: “control component(s) of the vehicle”; “the vehicle 1200 may use this information (e.g., instances of obstacles) to localize its position in a map, to navigate”).
It would have been obvious to one of ordinary skill in the art to modify Long to include a system for controlling navigation of the host vehicle and to navigate the host vehicle with respect to the object, as taught by Abbott. The disclosure of Long is directed to autonomous driving, and controlling and navigating a vehicle based on detections is considered ordinary and well-known in the art. Navigating the host vehicle with respect to the object is beneficial for enabling safer vehicle operation.
Regarding Claim 16, Long teaches: wherein the processor is further configured to:
receive the second detection at the first time frame ([pg. 2]; [pg. 7]);
determine a second position of the second detection and a second Doppler frequency for the second detection ([pg. 1]; [pg. 2]);
update the second position to a second predicted position in the second time frame based on calculations using the second Doppler frequency ([pg. 7]); and
detect the object from the first predicted position in the second time frame and the second predicted position in the second time frame ([pg. 2]; Fig. 6).
Regarding Claim 17, Long teaches: wherein the processor is further configured to update the first predicted position in the second time frame to a second predicted position in a third time frame based on a first calculation using the first Doppler frequency and the velocity of the host vehicle obtained in the second time frame ([pg. 2]; [pg. 7]).
Regarding Claim 18, Long teaches: wherein the processor is further configured to receive the second detection within the second time frame, determining a second position of the second detection and a second Doppler frequency for the second detection in the second time frame, and update the second position to a third predicted position in the third time frame using a second calculation based on the second Doppler frequency ([pg. 2]; [pg. 7]).
Regarding Claim 19, Long teaches: wherein the processor is further configured to detect the object by determining at least one of: (i) a position of the object; (ii) a shape of the object; (iii) an orientation of the object; and (iv) a class of the object ([pg. 7]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NOAH Y. ZHU whose telephone number is (571)270-0170. The examiner can normally be reached Monday-Friday, 8AM-4PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William J. Kelleher can be reached on (571) 272-7753. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NOAH YI MIN ZHU/Examiner, Art Unit 3648
/William Kelleher/Supervisory Patent Examiner, Art Unit 3648