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
Examiner acknowledges Applicant’s claim to priority benefits of EP23169046.2 filed 4/20/2023.
Information Disclosure Statement
Examiner acknowledges no information disclosure statement(s) (IDS) is submitted.
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 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.
For applicant’s benefit portions of the cited reference(s) have been cited to aid in the review of the rejection(s). While every attempt has been made to be thorough and consistent within the rejection it is noted that the PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS. See MPEP 2141.02 VI.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-6, 8-9 and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Loomis (US 2012/005,3834 A1), and further in view of Feller et al. (US 2008/0269988 A1).
Regarding claim 1, Loomis (‘834) discloses “a computer-implemented method for determination of the altitude of a moving vehicle based on GNSS data and vehicle sensor data (paragraph 28: Figure 4: GPS+IMU system; paragraph 30: the navigation unit executes a Kalman filter to combine IMU and GPS measurements; paragraphs 36: Figure 5: flow diagram for operation modes of a cordless GPS+IMU system),
the method comprising, obtaining: a sensor vehicle pitch rate stemming from at least one vehicle sensor (Figure 4, ref 405; (paragraph 28: Figure 4: GPS+IMU system; paragraph 30: the navigation unit executes a Kalman filter to combine IMU and GPS measurements; paragraphs 36: Figure 5: flow diagram for operation modes of a cordless GPS+IMU system); paragraph 40); and
while the GNSS signal is available, a GNSS vehicle pitch rate that stems from GNSS data of an altitude of the vehicle (paragraph 38: the navigation unit uses GPS to estimate position, heading and speed, and also to calibrate pitch, yaw, altitude and acceleration sensor biases); and
calibrating the sensor vehicle pitch rate based on the GNSS vehicle pitch rate paragraph 38: the navigation unit uses GPS to estimate position, heading and speed, and also to calibrate pitch, yaw, altitude and acceleration sensor biases).”
Loomis (‘834) does not explicitly disclose “in real-time”, “the calibration being is based on formulating the GNSS vehicle pitch rate as an affine function of the sensor vehicle pitch rate.”
Feller et al. (‘988) relates to a global navigation satellite system (GNSS) based sensor for vehicle steering control. Feller et al. (‘988) teaches “in real-time (paragraph 7: sensor system for vehicle steering control comprising: a plurality of global navigator satellite systems (GNSS) including receivers and antennas at a fixed spacing to determine a vehicle position, velocity and at least one of a heading angle, a pitch angle and a roll angle based on carrier phase corrected real time kinematic (RTK) position differences. The roll angle facilitates correction of the lateral motion induced position errors resultant from motion of the antennae as the vehicle moves based on an offset to ground and the roll angle; paragraph 25: Heading information, combined with position, either differentially corrected (DGPS or DGNSS) or carrier phase corrected real time kinematic (RTK) provides the feedback information desired for a proper control of the vehicle direction”,
“the calibration being is based on formulating the GNSS vehicle pitch rate as an affine function of the sensor vehicle pitch rate (paragraph 24: the GNSS attitude system may optionally combined with one or more rate gyro(s) used to measure turn, roll or pitch rates and to further calibrate bias and scale factor errors with these gyros)”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the computer-implemented method of Loomis (‘834) with the teaching of Feller et al. (‘988) for achieving navigation with high accuracy (Feller et al. (‘988)– paragraph 6). In addition, both of the prior art references, (Loomis (‘834) and Feller et al. (‘988)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, using combined global navigation satellite sensor system and Gyroscope control method for vehicle steering.
Regarding claim 2, which is dependent on independent claim 1, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 1. Loomis (‘834)/Feller et al. (‘988) does not explicitly disclose “the calibration is based on the equation:
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36
378
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where
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34
134
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is the GNSS vehicle pitch rate,
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32
124
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is the sensor vehicle pitch rate, a is a scaling correction, and b is an offset correction.”
Feller et al. (‘988) relates to a global navigation satellite system (GNSS) based sensor for vehicle steering control. Feller et al. (‘988) teaches “the calibration is based on the equation:
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36
378
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, where
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34
134
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is the GNSS vehicle pitch rate,
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32
124
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is the sensor vehicle pitch rate, a is a scaling correction, and b is an offset correction (paragraph 24: the GNSS attitude system may optionally combined with one or more rate gyro(s) used to measure turn, roll or pitch rates and to further calibrate bias and scale factor errors with these gyros; paragraph 58-62: For the purpose of calibrating the gyroscopes 430, 440, the angles measured by the GNSS attitude system 402 are used as truth in a Kalman filter estimator of gyro bias and scale factor errors…over a small interval of time, T, the following equation holds:
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24
112
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where
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30
38
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=average gyro reading over, A=gyro scale factor error, B=gyro rate bias error).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the computer-implemented method of Loomis (‘834) with the teaching of Feller et al. (‘988) for achieving navigation with high accuracy (Feller et al. (‘988)– paragraph 6). In addition, both of the prior art references, (Loomis (‘834) and Feller et al. (‘988)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, using combined global navigation satellite sensor system and Gyroscope control method for vehicle steering.
Regarding claim 3, which is dependent on claim 2, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 2. Loomis (‘834)/Feller et al. (‘988) does not explicitly disclose “calibrating the sensor vehicle pitch rate comprises computing the scaling correction a and the offset correction b.”
Feller et al. (‘988) relates to a global navigation satellite system (GNSS) based sensor for vehicle steering control. Feller et al. (‘988) teaches “calibrating the sensor vehicle pitch rate comprises computing the scaling correction a and the offset correction b (paragraph 24: the GNSS attitude system may optionally combined with one or more rate gyro(s) used to measure turn, roll or pitch rates and to further calibrate bias and scale factor errors with these gyros; paragraph 58-62: For the purpose of calibrating the gyroscopes 430, 440, the angles measured by the GNSS attitude system 402 are used as truth in a Kalman filter estimator of gyro bias and scale factor errors…over a small interval of time, T, the following equation holds:
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24
112
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where
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30
38
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=average gyro reading over, A=gyro scale factor error, B=gyro rate bias error).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the computer-implemented method of Loomis (‘834) with the teaching of Feller et al. (‘988) for achieving navigation with high accuracy (Feller et al. (‘988)– paragraph 6). In addition, both of the prior art references, (Loomis (‘834) and Feller et al. (‘988)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, using combined global navigation satellite sensor system and Gyroscope control method for vehicle steering.
Regarding claim 4, which is dependent on claim 3, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 3. Loomis (‘834)/Feller et al. (‘988) does not explicitly disclose “the computation of the scaling correction a and the offset correction b is based on the following equations:
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62
428
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,
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64
802
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, where t is a current time step and t -1 a previous time step.”
Feller et al. (‘988) relates to a global navigation satellite system (GNSS) based sensor for vehicle steering control. Feller et al. (‘988) teaches “the computation of the scaling correction a and the offset correction b is based on the following equations:
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62
428
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,
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64
802
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, where t is a current time step and t -1 a previous time step (paragraph 24: the GNSS attitude system may optionally combined with one or more rate gyro(s) used to measure turn, roll or pitch rates and to further calibrate bias and scale factor errors with these gyros; paragraph 58-62: For the purpose of calibrating the gyroscopes 430, 440, the angles measured by the GNSS attitude system 402 are used as truth in a Kalman filter estimator of gyro bias and scale factor errors…over a small interval of time, T, the following equation holds:
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24
112
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where
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30
38
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=average gyro reading over, A=gyro scale factor error, B=gyro rate bias error).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the computer-implemented method of Loomis (‘834) with the teaching of Feller et al. (‘988) for achieving navigation with high accuracy (Feller et al. (‘988)– paragraph 6). In addition, both of the prior art references, (Loomis (‘834) and Feller et al. (‘988)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, using combined global navigation satellite sensor system and Gyroscope control method for vehicle steering.
Regarding claim 5, which is dependent on independent claim 1, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 1. Loomis (‘834) further discloses “the at least one vehicle sensor comprises an Inertial Measurement Unit (IMU) (paragraph 28: Figure 4: GPS+IMU system; paragraph 30: the navigation unit executes a Kalman filter to combine IMU and GPS measurements; paragraphs 36: Figure 5: flow diagram for operation modes of a cordless GPS+IMU system).”
Regarding claim 6, which is dependent on independent claim 1, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 1. Loomis (‘834) further discloses “the method further comprises: when the GNSS signal is lost, determining an altitude of the vehicle using the last vehicle altitude obtained from the GNSS data and the calibrated sensor pitch rate (paragraph 39: if external position information is not available, as is the case when driving in a tunnel, for example, the navigation unit uses stored sensor bias information and pitch, yaw, altitude and acceleration sensor measurements to update estimated position, heading and speed).”
Regarding claim 8, which is dependent on independent claim 1, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 1. Loomis (‘834) further discloses “the vehicle is a motorbike, a car, a bus or a truck. (paragraph 12: Figure 1: a wheeled vehicle 105, e.g. a car or truck).”
Regarding claim 9, which is dependent on independent claim 1, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 1. Loomis (‘834) further discloses “a non-transitory computer readable medium comprising instructions which, when executed by a computer system, cause the system to perform the method of claim 1. (paragraph 42: the appended claims are intended to include within their scope such processes, machines, manufacture, means, methods, or steps).”
Regarding claim 12, which is dependent on claim 9, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 9. Loomis (‘834) further discloses “the system is coupled with or further comprises the GNSS and the at least one vehicle sensor (paragraph 17: cordless GPS+IMU system).”
Regarding claim 13, which is dependent on claim 9, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 9. Loomis (‘834) further discloses “the at least one vehicle sensor includes an Inertial Measurement Unit (IMU)) (paragraph 28: Figure 4: GPS+IMU system; paragraph 30: the navigation unit executes a Kalman filter to combine IMU and GPS measurements; paragraphs 36: Figure 5: flow diagram for operation modes of a cordless GPS+IMU system).”
Regarding claim 14, which is dependent on claim 9, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 9. Loomis (‘834) further discloses “a vehicle equipped with the system (paragraph 12: Figure 1: a wheeled vehicle 105, e.g. a car or truck; Figure 4).”
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Loomis (US 2012/005,3834 A1)/Feller et al. (US 2008/0269988 A1), and further in view of Jones et al. (US 2014/0324291 A1).
Regarding claim 7, which is dependent on independent claim 1, Loomis (‘834)/Feller et al. (‘988) discloses the method of claim 1. Loomis (‘834) describes If external position information from GPS is available (e.g. from GPS 420), as is the case when several GPS satellites are in view, the navigation unit uses GPS to estimate position, heading and speed, and also to calibrate pitch, yaw, altitude and acceleration sensor biases (paragraph 38). Loomis (‘834)/Feller et al. (‘988) does not explicitly disclose “the GNSS data stems from a GNSS device that comprises only one antenna.”
Jones et al. (‘291) relates to vehicle control using global navigation satellite system (GNSS) based sensor. Jones et al. (‘291) teaches “the GNSS data stems from a GNSS device that comprises only one antenna (paragraph 144:Figure 15: the implement antenna 756, to the single GNSS receiver 734).”
It would have been obvious to one of ordinary skill-in-the-art before the effective filing date of the claimed invention to modify the computer-implemented method of Loomis (‘834)/Feller et al. (‘988) with the teaching of Jones et al. (‘291) for achieving navigation with high accuracy (Jones et al. (‘291) – paragraph 29). In addition, all of the prior art references, (Loomis (‘834) and Feller et al. (‘988)) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, using combined global navigation satellite sensor system and Gyroscope control method for vehicle steering.
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
KR 102388126 B1 [English Translation] describes GPS information is used in the process that the IMU performs self-calibration, and for this purpose, GPS information is first collected…GPS information may be information obtained from GPS included in the IMU system itself, information may be information obtained from GPS included in the vehicle itself but not included in the IMU system, and may be information obtained from an external device not included in the vehicle itself, such as external navigation…it may be information obtained from GPS…in order to collect information obtained from GPS included in the vehicle itself or information obtained from an external GPS, data may be transmitted through wired or wireless communication (page 2 last paragraph – page 3 first paragraph); corrects the posture information of the IMU through the posture information obtained through GPS, and it is possible to self-calibrate the IMU without using a separate device for calibration. This process may be performed by receiving GPS information in real time while driving the vehicle and comparing it with the IMU at that time, or may compare the stored GPS information with the IMU information after the operation ends (page 3 third paragraph).
Faragher et al. (US 2021/0254979 A1) describes a computer-implemented method performed in a tracking system for tracking the motion of a body, as a function of time, the method comprising: (a) during a first time period, obtaining first data related to the motion of a body from at least one primary positioning unit, wherein said at least one primary positioning unit is mounted on a first platform carried on the body, or wherein said at least one primary positioning unit is separate to the body, said primary positioning unit being operational during the first time period; (b) during the first time period, obtaining second data from one or more secondary sensors configured to make measurements from which position or movement may be determined, said one or more secondary sensors being mounted on one or more second platforms carried on the body; (c) generating first training data comprising the first data and second data; (d) during a second time period, obtaining third data from the one or more secondary sensors, and; (e) analysing the third data to estimate at least one first metric related to the motion of the body during the second time period using a first algorithm trained using the first training data (paragraph 7).
Stahlin et al. (US 10,353,076 B2) describes One of the two sensor signals may, for example, represent the aforementioned reference position data derived from vehicle dynamics data from an inertial sensor, whereas the other sensor signal may, for example, represent the position data derived from a GNSS signal, wherein both sensor signals and the measuring signal indicate a position of the vehicle comprising an absolute position, a speed, an acceleration and a heading of the vehicle…the two sensor signals can be filtered using a filter (column 4 lines 6-15).
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/NUZHAT PERVIN/Primary Examiner, Art Unit 3648