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 .
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. EP 23171093, filed on May 2, 2023.
Status of Claims
Amendments to claims 1, 6, 13 and 15.
Claim 11 is cancelled.
Claims 1 – 10 and 12 – 15 are pending.
Response to Remarks
A new secondary reference Zhang has been found necessitated by amendments.
In view of Interview discussion, the 101 rejection is withdrawn.
Regarding claim 3, the primary reference Alcalde does not use the word “weight”; however, this rejection is maintained based on beamforming/steering concepts as understood in the art. Weight is also broad term and could be digital or analog and could be done via multiplication, windowing, phase rotating, etc. Beamforming/steering weights in of itself, without more, based on the Examiner’s experience, is not typically allowable subject matter.
Claim 5 does not specify the type of disambiguation process. Applicant appears to agree that the additional secondary reference Li teaches disambiguation. The secondary reference Zhang addresses the other concerns.
Applicant remarks regarding claim 9 are persuasive.
Applicants amendments and remarks regarding claim 6 are persuasive.
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 1 – 5, 7 – 8 and 10 – 15 are rejected under 35 U.S.C. as being obvious over Alcalde (US 20180120414 A1) in view of Zhang (US 20210033724 A1) and official notice.
All citations are that of the primary reference unless otherwise specified.
As to claims 1 and 13 – 15, Alcalde discloses the computer-implemented method for calibration of a radar sensor, the radar sensor having one or more antennas (Fig. 4) the method comprising:
obtaining measurement data from the radar sensor by one or more radar signals, wherein the measurement data is indicative of a radial velocity of an object and includes a range dimension (Fig. 1 items 58, 60);
includes a radar data cube having a range, radial velocity and antenna dimensions (Official Notice.)
determining, based on the obtained measurement data, one or more data sets indicative of a variation of the one or more radar signals (Para. 24 “the controller 40 determines a calibration-matrix 54 of the system 10 based on a difference between the plurality of detections 48 and the ideal-response 52 when the object 20 is stationary, where the difference is based on an angle difference between an indicated-angle 66 at an indicated-range-rate 60 and an ideal-angle at an ideal-range-rate indicated by the ideal-response 52 for the condition that the ideal-range-rate is equal to the indicated-range-rate 60.”);
determining, based on the one or more data sets and/or based on the obtained measurement data, angle data relating to the object (Fig. 1 item 54 adjusted angle); and
calibrating, based on the one or more data sets and the angle data, the radar sensor by determining a calibration matrix for calibrating the one or more antennas (Para. 24 calibration matrix and Fig. 1 adjusted-angle item 54).
Alcalde also discloses a vehicle. See Alcalde Fig. 1.
The Examiner takes official notice of taking a Fourier transform (usually a fast Fourier transform FFT) across fast-time for range samples, Fourier transform across slow-time (pulse-repetition intervals) for Doppler/Velocity samples and Fourier transform across antennae for spatial samples. The more dimensions, the better the resolution for target separation (motivation) at the cost of computation (trade-off). The Examiner included several references that discloses the 3-D FFT cube in the updated PTO-892. Said cube is used in many disciplines other than radar, thus not considered esoteric.
Alcalde does not discloses the feature of wherein determining the one or more data sets includes, for each of a plurality of radial velocity bins of the radar data cube, accumulating the measurement values over the range dimension using range samples as artificial snapshots, thereby reducing or removing the range dimension.
In the same field of endeavor, Zhang teaches “L denotes a width of a window of the distance accumulation along the fast time dimension, and the symbol “└ ┘” denotes rounding down. A large number of experimental studies have shown that when the number of sampling points of fast time signals is set to 2,048 and the width L of the window of the distance accumulation is equal to 10, after the distance accumulation, the distance sampling points of the original echo signal may be reduced from 2,048 in R(m, n) to about 200 in R.sub.1(k, n), namely, dimensions of the matrix is reduced from 2,048 to 200. In addition, after subsequent signal processing and target identification, the distance-accumulated signal has the same detection effect as the original echo signal before the distance accumulation. In this manner, the signal processing speed may be effectively increased and the operating efficiency of search and rescue of the radar may be improved. At the same time, the distance accumulation on the signal in the fast time dimension may also suppress high frequency interference from the fast time signal to a certain extent (Para. 45).”
In view of the teachings of Zhang, it would have been obvious to a person before filing to reduce the range dimension via accumulation as taught by Zhang in order to reduce data set size thus reducing memory size constraints and increasing processing speed.
As to claim 2, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 1 further comprising: obtaining information of one or more antennas of the radar sensor and of expected ideal measurements (Paras. 24 and 32 describe ideal response related to antennae.); and
calculating, based on the one or more data sets, the angle data, and the information, one or more processed data sets, wherein the calibrating is based on the one or more processed data sets (Fig. 1 Controller having calibration-matrix 54 and all other relevant item numbers).
As to claim 3, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 2 wherein the calculating includes weighting of one or more values of the one or more data sets (Para. 24 The ordinarily skilled understand steering vectors to be weights that reshape and/or steer the antennae lobes.).
As to claim 4, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 3 wherein: the weighting of the one or more values of the one or more data sets is performed by scaling ideal beamvectors (Para. 24 Steering vectors); and the ideal beamvectors are based on a structural arrangement of the radar sensor and/or on an additional angle data of the object (Fig. 4 – the steering vectors have to take into account time delays related to structure.).
As to claim 5, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 1 wherein: the angle data of the object includes ambiguous angle data; and the method further includes a disambiguation process (Para. 30 wherein Alcalde discloses a face-linearity to select suitable objects while discarding non-suitable objects in order to avoid angular ambiguities.).
As to claim 7, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 3 wherein calculating the one or more processed data sets includes accumulation over the radial velocity dimension of the measurement data (Para. 18 “collecting/averaging range-rates”).
As to claim 8, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 1 wherein determining the angle data of the object includes determining the angle data from the radial velocity of the measurement data (Fig. 3).
As to claim 10, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 1 wherein the measurement data is further indicative of at least one of:
a range of the object (Fig. 1 item 58 indicated distance),
an ego-motion of the radar sensor, an ego-motion of a vehicle including the radar sensor (Fig. 1 stationary object such as a road sign provides ego-motion), or
information of a radar sensor arrangement including a structural arrangement of the radar sensor in a vehicle (Fig. 4, Para. 2 “At each angle, a response in the form of complex voltages is collected for each element of the antenna, and these responses can be used to fully determine a default or initial calibration of the system. That is, where the responses deviate from an expected or ideal-response is noted and a correction factor or calibration-matrix is established to correct or compensate the complex-voltages from each element of the antenna for each of the angles tested.”).
As to claim 11, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 1 wherein the calibrating the radar sensor includes determining, based on one or more accumulated data sets and the angle data, a calibration matrix for the radar sensor (Fig. 1 item 54 Calibration-matrix and Para. 18 “collecting/averaging range-rates associated with stationary-objects located near the bore-site 46 (FIGS. 2A and 2B) of the system 10.”)
As to claim 12, Alcalde in view of Zhang and official notice teaches the computer-implemented method of claim 1 further comprising: determining, based on the calibration of the radar sensor, an operating instruction for a vehicle affecting a task of a vehicle assistance system, wherein the task includes at least one of: displaying a detected object on a display of the vehicle, conducting a vehicle path planning, triggering a warning, affecting control of the vehicle during a parking process, affecting control of the vehicle during driving, mapping, based on the calibration of the radar sensor, reference maps for further applications, or creating, based on the calibration of the radar sensor, reference maps for further applications (Fig. 1 Vehicle Controls: steering, accelerator and brakes.).
Claim 5 is rejected under 35 U.S.C. 103 as being obvious over Alcalde in view of Zhang, official notice and in further view of Li (US 20230131090 A1).
If Applicant successively argues for a stricter interpretation of disambiguation, the Examiner introduces a secondary reference.
In the same field of endeavor, Li teaches “subsampling on the Doppler dimension may be used to disambiguate Doppler ambiguity introduced as a result of low computational overhead Doppler transformations such as Doppler FFT operations, and subsampling on elevation and/or azimuth angles may be used to disambiguate angle or aperture ambiguity introduced as a result of low computational overhead beamforming transformations such as beamforming FFT operations (Para. 89).”
In view of the teachings of Li, it would have been obvious to the ordinarily skilled before filing to include subsampling in order to mitigate ambiguities thereby improving accuracy.
Allowable Subject Matter
Claims 6 and 9 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.
Regarding claim 6, the specification relates snap shouts to accumulation over the range dimension. See Spec. Para. 32. A secondary reference was used to teach accumulation over the range dimension to reduce range dimension. Given the nexus between snapshots and covariance matrix, it would be hindsight to find another, different secondary reference that separately teaches covariance matrices but not accumulation over the range dimension to reduce range dimension.
Regarding claim 9, the Examiner finds Applicants remarks persuasive.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL W JUSTICE whose telephone number is (571)270-7029. The examiner can normally be reached 7:30 - 5:30 M-F.
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/MICHAEL W JUSTICE/Examiner, Art Unit 3648
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