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 .
Response to Amendments
The amendment filed 05/08/2026 is entered.
Claims 1, 3-4, 6, and 11 are amended.
Claims 2 and 5 are canceled.
Claims 1, 3-4, and 6-15 are pending.
Claim Objections
Claim 1 is objected to because of the following informalities:
In Claim 1, the phrase “a memory being available during operation” should be “a memory that is available during operation”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims
particularly pointing out and distinctly claiming the subject matter which the
inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out
and distinctly claiming the subject matter which the applicant regards as his
invention.
Claim(s) 1 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claim 1, the Claim recites the limitation “a result of the estimating step is represented as a reference beam vector.” It is unclear whether “a result of the estimating step” refers to “the result of the estimating step” recited earlier in the claim, or to a different result. For examination purposes, the limitation is interpreted as referring to the same “result of the estimating step” recited earlier in the claim.
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.
Claim(s) 1, 3, 6, and 8-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kitamura (US 2018/0156909) in view of Chipengo (Chipengo et al., “From Antenna Design to High Fidelity, Full Physics Automotive Radar Sensor Corner Case Simulation,” 2018) and Loesch (US 2017/0045609).
Regarding Claim 1, Kitamura teaches:
A computer implemented method for determining a direction-of-arrival for radar waves which are transmitted by a radar sensor mounted at a vehicle, wherein the radar waves are reflected by an object in the external environment of the vehicle and received by the radar sensor, wherein a vehicle component is mounted in a field of view of the radar sensor ([0004]: “multiple reflections of the electromagnetic waves are caused by the bumper”; [0006]: “in-vehicle radar apparatus which is installed in the bumper of a vehicle and detects at least the direction of an object”; [0007]: “reflecting object”),
the method comprising the following steps performed by a processing unit ([0027]: “signal processing section 4”):
estimating an impact of the vehicle component on the radar waves received by the radar sensor ([0005]: “detecting direction errors”; [0036]: “direction error learning processing”),
storing the result of the estimating step in a memory being available during operation of the vehicle ([0027]: “The nonvolatile memory stores … a direction correction table”; [0036]: “updating the direction correction table”),
receiving, during operation of the vehicle, primary data generated by radar waves which are received by the radar sensor ([0030]: “the signal processing section 4 acquires sampling data of the beat signals of one measurement cycle, obtained through transmitting and receiving radar waves”),
modifying the primary data by the stored result of the estimating step ([0034]: “the directions which have been estimated in S140 (hereinafter referred to as “estimated directions”) are corrected using the direction correction table”), and
determining the direction-of-arrival by using the modified data ([0034]: “correction is performed”; [0035]: “object information is generated which includes ... the direction in which the object is located”),
Kitamura does not explicitly teach:
wherein:
estimating the impact of the vehicle component includes:
receiving positioning data for the radar sensor and for the vehicle component with respect to a reference position at the vehicle,
receiving characteristic data of the vehicle component, and
simulating the impact of the vehicle component based on the positioning data and based on the characteristic data;
a result of the estimating step is represented as a reference beam vector;
a measured beam vector is generated based on the primary data; or
modifying the primary data includes correlating the measured beam vector and the reference beam vector.
However, Chipengo is in the field of automotive radar simulation (Chipengo [Title]; [Abstract]: “Antenna interaction with vehicle bumper and fascia is also investigated”) and teaches:
wherein estimating the impact of the vehicle component includes:
receiving positioning data for the radar sensor and for the vehicle component with respect to a reference position at the vehicle (Chipengo [p. 5]: “ the engineer simply acquires bumper and facia computer aided designs (CAD) from the vehicle original equipment manufacturer (OEM). Using these CAD files, the antenna can be simulated in the exact place where it would be located in normal vehicle operation”),
receiving characteristic data of the vehicle component (Chipengo [p. 4]: “the properties of the metallic bumper and dielectric facia can significantly alter the antenna properties”), and
simulating the impact of the vehicle component based on the positioning data and based on the characteristic data (Chipengo [p. 5]: “Effects of a dielectric cover, bumper, and facia on the radiation characteristics of the antenna from Section 2 were investigated using HFSS FEM and HFSS SBR+”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kitamura and estimate the impact of the vehicle component by receiving positioning data for the radar sensor and for the vehicle component, receiving characteristic data of the vehicle component, and simulating the impact of the vehicle component based on the positioning data and the characteristic data, as taught by Chipengo, with a reasonable expectation of success. Applying Chipengo’s known simulation technique to Kitamura’s direction error correction system yields the predictable result of efficiently estimating the impact of the vehicle component, which improves detection and reliability of the system (Chipengo [p. 2]; [p. 5]).
Furthermore, Loesch is in the field of automotive radar angle estimation (Loesch [0005]: “When the radar sensor is installed in a motor vehicle, for example behind a bumper”; “errors in the angle estimate.”; [0006]: “enable more accurate angle estimation”) and teaches:
a result of the estimating step is represented as a reference beam vector (Loesch [0037]: “control vector a(θ)”; [0075]: “the (relative) transmitting control vector a′tx(θ) is then corrected (recalibrated)”);
a measured beam vector is generated based on the primary data (Loesch [0037]: “received signals x”; [0043]: “x is the vector of the signals obtained with the various combinations of transmitting and receiving antenna elements”); and
modifying the primary data includes correlating the measured beam vector and the reference beam vector (Loesch [0037]: “A knowledge of the control vector a(θ) makes it possible to create an (under suitable conditions, unequivocal) correlation between the angle θ of the object and the received signals x, and to infer the azimuth angle θ of the object from the amplitude relationships and phase relationships of the received signals.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kitamura and represent the result of the estimating step as a reference beam vector, generate a measured beam vector based on the primary data, and modify the primary data by correlating the measured beam vector and the reference beam vector, as taught by Loesch, with a reasonable expectation of success. Applying Loesch’s known control vector correlation technique to Kitamura’s direction error correction system yields the predictable result of a more accurate angle estimate for a radar sensor mounted behind a vehicle component (Loesch [0005-0006]).
Regarding Claim 3, Kitamura as modified does not explicitly teach – but Chipengo teaches: wherein the characteristic data includes data related to a material composition of the vehicle component (Chipengo [p. 4]: “the properties of the metallic bumper and dielectric facia can significantly alter the antenna properties”; [p. 5]: “Effects of a dielectric cover, bumper, and facia on the radiation characteristics of the antenna from Section 2 were investigated using HFSS FEM and HFSS SBR+”).
Because the characteristic data including data related to a material composition of the vehicle component is an element of Chipengo’s simulation technique, the rationale to modify Kitamura with the teachings of Chipengo persists from Claim 1.
Regarding Claim 6, Kitamura as modified does not explicitly teach – but Loesch teaches: wherein determining the direction-of-arrival by using the modified data includes determining a maximum of the correlation of the measured beam vector and the reference beam vector (Loesch [0004]: “the estimated angle is obtained as the position of the best agreement between the received signal and the antenna diagram”; [0037]: “the azimuth angle cannot be exactly calculated but can only be estimated, for example using a maximum likelihood estimate”).
Because determining the direction-of-arrival by determining a maximum of the correlation is an element of Loesch’s correlation technique, the rationale to modify Kitamura with the teachings of Chipengo persists from Claim 1.
Regarding Claim 8, Kitamura as modified teaches: wherein the result of the estimating step is stored in a memory of the radar sensor ([0027]: “The nonvolatile memory stores … a direction correction table”).
Regarding Claim 9, Kitamura as modified teaches: wherein the result of the estimating step is represented by at least one look-up table ([0027]: “direction correction table”).
Regarding Claim 10, Kitamura as modified teaches: wherein during operation of the vehicle, an online calibration of the radar sensor is performed ([0036]: “direction error learning processing is executed for learning the direction error”), and
the stored result of the estimating step is updated based on the online calibration ([0036]: “updating the direction correction table”; [0055]: “the direction correction table is updated anytime by means of learning”).
Regarding Claim 11, Kitamura as modified does not explicitly teach – but Chipengo teaches: wherein the vehicle component is a fascia of the vehicle and the radar sensor is mounted behind the fascia (Chipengo [p. 2]: “bumper and fascia”; [Fig. 6]: “Packaged antenna mounted on bumper behind car facia”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kitamura and let the vehicle component be a fascia and mount the radar sensor behind the fascia, as taught by Chipengo, with a reasonable expectation of success. Radar sensors can be mounted behind fascia to seamlessly integrate radar into a vehicle (Chipengo [p. 3]), and considering the impact of the fascia is beneficial for improving detection and reliability of the system (Chipengo [p. 2]).
Regarding Claim 12, Kitamura as modified teaches: A computer system being configured to carry out the computer implemented method of claim 1 ([0027]: “The signal processing section 4 consists of a known type of microcomputer, mainly composed of a CPU 41, a ROM 42, and a RAM 43”).
Regarding Claim 13, Kitamura as modified teaches: A vehicle including a radar sensor and the computer system according to claim 12 ([0024]: “The in-vehicle radar apparatus 1 shown in FIG. 1 includes an antenna section 2, a transmit/receive section 3, and a signal processing section 4”).
Regarding Claim 14, Kitamura as modified teaches: The vehicle according to claim 13, wherein the radar sensor includes a memory in which the result of the estimating step is stored ([0027]: “RAM 43”; “The nonvolatile memory stores ... a direction correction table”).
Regarding Claim 15, Kitamura as modified teaches: A non-transitory computer readable medium comprising instructions for carrying out the computer implemented method of claim 1 ([0027]: “The signal processing section 4 consists of a known type of microcomputer, mainly composed of a CPU 41, a ROM 42, and a RAM 43”).
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kitamura (US 2018/0156909), Chipengo (Chipengo et al., “From Antenna Design to High Fidelity, Full Physics Automotive Radar Sensor Corner Case Simulation,” 2018), and Loesch (US 2017/0045609), as applied to Claim 1 above, and further in view of Harter (Harter et al., “Self-Calibration of a 3-D-Digital Beamforming Radar System for Automotive Applications With Installation Behind Automotive Covers,” 2016).
Regarding Claim 4, Kitamura as modified teaches: wherein estimating the impact of the vehicle component includes:
receiving positioning data for the radar sensor and for the vehicle component with respect to a reference position at the vehicle (Chipengo [pg. 5]).
Kitamura does not explicitly teach:
outside the vehicle, disposing the radar sensor relative to a simulation component having the same dimensions and similar material properties as the vehicle component,
receiving simulation data which is generated by radar waves transmitted by the radar sensor and reflected by the simulation component, or
estimating the impact of the vehicle component based on the simulation data.
However, Harter is in the field of automotive radar calibration (Harter [Title]) teaches:
receiving positioning data for the radar sensor and for the vehicle component with respect to a reference position at the vehicle (Harter [p. 2996]: “the measurement setup shown in Fig. 4 with three trihedrals at different positions is chosen”; [p. 2998]: “Fig. 9. Sketch of the measurement scenario with a trihedral and the bumper in front of the 3-D-DBF radar system.”),
outside the vehicle, disposing the radar sensor relative to a simulation component having the same dimensions and similar material properties as the vehicle component (Harter [p. 2998]: Fig. 9),
receiving simulation data which is generated by radar waves transmitted by the radar sensor and reflected by the simulation component (Harter [p. 2996]: “After the reception of the signals, the measurement data of each transmitter and receiver combination are range processed”), and
estimating the impact of the vehicle component based on the simulation data ([p. 2996]: “phase errors can be determined...”; [p. 2998]: “the combined amplitude errors of the 3-D-DBF radar sensor and silver-painted bumper in front are estimated by means of the self-calibration procedure from Section IV.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kitamura, as modified by Chipengo and Loesch, and dispose a radar sensor and a simulation component outside the vehicle, and receive simulation data from the simulation component, and estimate the impact of the vehicle component based on the simulation data, as taught by Harter, with a reasonable expectation of success. Performing a simulation outside of the vehicle is beneficial for better characterizing the bumper influence, which improves angle measurement (Hart [p. 2997-2998]).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kitamura (US 2018/0156909), Chipengo (Chipengo et al., “From Antenna Design to High Fidelity, Full Physics Automotive Radar Sensor Corner Case Simulation,” 2018), and Loesch (US 2017/0045609), as applied to Claim 1 above, and further in view of Vasanelli (Vasanelli et al., “Calibration and Direction-of-Arrival Estimation of Millimeter-Wave Radars: A Practical Introduction,” 2020).
Regarding Claim 7, Kitamura as modified does not explicitly teach: wherein a fractional bin estimation is applied to the correlation of the measured beam vector and the reference beam vector.
However, Vasanelli is in the field of direction-of-arrival estimation (Vasanelli [Title]) and teaches: wherein a fractional bin estimation is applied to the correlation of the measured beam vector and the reference beam vector (Vasanelli [p. 38]: “the input vector has 32 entries, for a smoother spectrum use a zero padding to 256 values”; [p. 42]: “the created ideal steering matrix Y does not contain any noise and, therefore, leads to a smoother DoA result. In addition, the angular step-size can be chosen as small as desired without increasing the measurement effort.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kitamura, as modified by Chipengo and Loesch, and apply fractional bin estimation to the correlation, as taught by Vasanelli, with a reasonable expectation of success. Applying Vasanelli’s known fractional bin estimation technique to the correlation yields the predictable result of a smoother and finer-resolution direction-of-arrival estimate (Vasanelli [p. 38]).
Response to Arguments
Applicant’s amendments and arguments, filed 05/08/2026, regarding Claim Objections and Claim Rejections under 35 USC 112(b) have been fully considered and are persuasive. The previous objections and 112 (b) rejections have been overcome.
Applicant’s arguments, filed 05/08/2026, regarding Claim Rejections under 35 USC 102 and 103 have been fully considered but are moot because they do not apply to the specific combination of references being used in the current rejection. However, for clarity of record, Examiner addresses specific arguments below.
Applicant argues that paragraphs [0041] and [0043] of Kitamura do not describe receiving positioning data for a radar sensor and a vehicle component, or simulating the impact of the vehicle component based on the positioning data. Examiner asserts that the arguments are moot because the rejection set forth above does not rely on Kitamura for these limitations and instead relies on Chipengo.
Applicant argues that Chipengo fails to teach or suggest an in-vehicle simulation of the impact of a vehicle component. In response to Applicant’s argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “in-vehicle simulation”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
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 NOAH Y. ZHU whose telephone number is (571) 270-0170. The examiner can normally be reached Monday-Friday, 8AM-4PM.
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).
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire, can be reached on (571) 270-5144. 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
/BRADY W FRAZIER/ Primary Examiner, Art Unit 3648
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