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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/07/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claim 1 is objected to because of the following informalities:
In Claim 1, the phrase “reflected at an object” should be “reflected by an object”
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.
Claims 5 and 11 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 5, the claim recites the limitation “ the calibrated measured beam vector.” There is insufficient antecedent basis for this limitation in the claim. For examination purposes, the limitation is interpreted as “the measured beam vector.”
Regarding Claim 11, the claim recites the limitation “a fascia mounted close to a bumper.” The term “close” is a relative term which renders the claim indefinite. The term “close” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The distance between the fascia and the bumper has been rendered indefinite by the use of the term “close.”
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.
Claim 1, 8-10, and 12-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kitamura (US 2018/0156909).
Regarding Claim 1, Kitamura discloses: 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 at 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]: “radar apparatus”; [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 ([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”).
Regarding Claim 8, Kitamura discloses: wherein the result of the estimating step is stored in a memory of the radar sensor ([0024]: “The in-vehicle radar apparatus 1 ... includes ... a signal processing section 4”).
Regarding Claim 9, Kitamura discloses: wherein the result of the estimating step is represented by at least one look-up table ([0027]: “direction correction table”).
Regarding Claim 10, Kitamura discloses: 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 12, Kitamura discloses: 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 discloses: 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 discloses: 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 discloses: 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 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 2-3 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Kitamura (US 2018/0156909) as applied to Claim 1 above, and further in view of Chipengo (Chipengo et al., “From Antenna Design to High Fidelity, Full Physics Automotive Radar Sensor Corner Case Simulation,” 2018).
Regarding Claim 2, Kitamura 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 ([0041]: “In S230, a theoretical curve C is calculated in accordance with the speed Vself of the own vehicle … θinst is the installation angle of the in-vehicle radar apparatus 1”),
…
simulating the impact of the vehicle component based on the positioning data … ([0043]: “direction errors are calculated”).
Kitamura does not explicitly teach:
receiving characteristic data of the vehicle component, and
simulating the impact of the vehicle component … based on the characteristic data.
Chipengo teaches:
receiving positioning data for the radar sensor and for the vehicle component with respect to a reference position at the vehicle (Chipengo [p. 2]: “the performance of these antennas when mounted on a car bumper and fascia will be investigated”; [p. 5]: “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”; [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+”), 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 to modify Kitamura and receive characteristic data of the vehicle component and simulate the impact of the vehicle component based on the characteristic data, as taught by Chipengo. Simulating the impact of the vehicle component based on the characteristic data is beneficial for improving detection and reliability of the system (Chipengo [p. 2]). Modifying Kitamura with the teachings of Chipengo comprises combining prior art elements according to known methods to yield predictable results.
Regarding Claim 3, Kitamura 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+”).
It would have been obvious to one of ordinary skill in the art to modify Kitamura and include material composition in the characteristic data, as taught by Chipengo. Simulating impact of the vehicle component based on the material composition is beneficial for improving detection and reliability of the system (Chipengo [p. 2]). Modifying Kitamura with the teachings of Chipengo comprises combining prior art elements according to known methods to yield predictable results.
Regarding Claim 11, Kitamura does not explicitly teach – but Chipengo teaches: wherein the vehicle component is a fascia mounted close to a bumper of the vehicle in front of the radar sensor (Chipengo [p. 2]: “bumper and fascia”).
It would have been obvious to one of ordinary skill in the art to modify Kitamura and let the vehicle component be a fascia, as taught by Chipengo. Fascia are commonly mounted on or close to bumpers, and considering the impact of the fascia is beneficial for improving detection and reliability of the system (Chipengo [p. 2]). Modifying Kitamura with the teachings of Chipengo comprises combining prior art elements according to known methods to yield predictable results.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Kitamura (US 2018/0156909) 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 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 ([0041]: “In S230, a theoretical curve C is calculated in accordance with the speed Vself of the own vehicle … θinst is the installation angle of the in-vehicle radar apparatus 1”),
…
receiving simulation data which is generated by radar waves transmitted by the radar sensor … ([0040]: “radar waves”; [0043]: “frequency bins of the data”), and
estimating the impact of the vehicle component based on the simulation data ([0043]: “direction errors are calculated”).
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, and
receiving simulation data which is … reflected by the simulation component.
Harter 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 to modify Kitamura and dispose a radar sensor and a simulation component outside the vehicle, and receive simulation data from the simulation component, as taught by Harter. Performing a simulation outside of the vehicle is beneficial for better characterizing the bumper influence, which improves angle measurement (Hart [p. 2997-2998]). Modifying Kitamura with the teachings of Harter comprises combining prior art elements according to known methods to yield predictable results.
Claims 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Kitamura (US 2018/0156909) 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 5, Kitamura does not explicitly teach – but Vasanelli teaches: wherein
the result of the estimating step is represented as a reference beam vector (Vasanelli [p. 37]: “The results of the reference measurement can be saved into the calibration matrix”),
a measured beam vector is generated based on the primary data (Vasanelli [p. 37]: “the measurement result for an unknown direction can be saved in the vector”), and
modifying the primary data includes correlating the calibrated measured beam vector and the reference beam vector (Vasanelli [p. 37]: “The basic idea of the DML approach is to compare the actual measurement results with a reference calibration matrix.”; “the cross correlation between the measurement and calibration results”).
It would have been obvious to one of ordinary skill in the art to modify Kitamura and use a reference beam vector, a measured beam vector, and correlate the reference and measured beam vectors to modify the primary data, as taught by Vasanelli. Using beam vectors to correct sensor error is considered ordinary and well-known in the art. Modifying Kitamura with the teaching of Vasanelli comprises combining prior art elements according to known methods to yield predictable results.
Regarding Claim 6, Kitamura does not explicitly teach – but Vasanelli 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 (Vasanelli [p. 37]: “the direction that maximizes the cross correlation, i.e., that returns the highest similarity, gives the estimated DoA”).
It would have been obvious to one of ordinary skill in the art to modify Kitamura and determine the direction-of-arrival by determining a maximum of the correlation, as taught by Vasanelli. Determining the direction-of-arrival by determining a maximum of the correlation is considered ordinary and well-known in the art. Modifying Kitamura with the teaching of Vasanelli comprises combining prior art elements according to known methods to yield predictable results.
Regarding Claim 7, Kitamura does not explicitly teach – but Vasanelli 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 to modify Kitamura and apply fractional bin estimation to the correlation, as taught by Vasanelli. Fractional bin estimation is considered ordinary and well-known in the art. Modifying Kitamura with the teaching of Vasanelli comprises combining prior art elements according to known methods to yield predictable results.
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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/NOAH YI MIN ZHU/Examiner, Art Unit 3648
/William Kelleher/ Supervisory Patent Examiner, Art Unit 3648