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 .
Status of Application
Claims 1-20 are pending. Claims 1, 12, and 19 are the independent claims. Claims 1, 6, 10, 12, 15, 18, 19, and 20 have been amended. This office action is in response to the Amendments received on 10/30/2025.
Response to Arguments
With respect to Applicant’s remarks filed on 10/30/2025; “Applicant Arguments/Remarks Made in an Amendment” have been fully considered. Applicant’s remarks will be addressed in sequential order as they were presented.
Applicant's arguments according to the Applicant’s Remarks filed on 10/30/2025, see pages 11-12 “Response to Rejection Under 35 U.S.C § 112(A)”, with respect to claims 1-11, 12-18, and 19-20, has been considered and are persuasive. The rejection of claims 1-11, 12-18, and 19-20 under 35 U.S.C § 112(a) has been withdrawn.
In response to the amended claims files on 10/30/2025, the rejection of claims 6 and 15 as being indefinite under 35 U.S.C § 112(b), has been withdrawn. However, the currently amended claims have changed the examiner’s broadest reasonable interpretation for the previously indefinite claims, therefore new ground of rejections have been applied in the final office action below.
Applicant's arguments, see pages 12-15 “Response To Rejection Under 35 U.S.C § 103”, with respect to claims 1, 12, 19, 3-6, 10-11, 14-15, 18, and 20, have been fully considered but they are not persuasive. With respect to claims 1, 12, and 19, applicant argues that the claimed navigation information processing method is non-obvious over Chen in view of Cui, further in view of ‘Titterton and Weston’ (or as alternative in view of Steinhardt) as the combination of references fails to teach or suggest the core inventive concept of the present application. Particularly, applicant argues that the technical objective of Chen is different from the claimed invention in the present application. In response, it is respectfully submitted the reason or motivation to modify the reference may often suggest what the inventor has done, but for a different purpose or to solve a different problem. It is not necessary that the prior art suggest the combination to achieve the same advantage or result discovered by applicant. See, e.g., In re Kahn, 441 F.3d 977, 987, 78 USPQ2d 1329, 1336 (Fed. Cir. 2006) (motivation question arises in the context of the general problem confronting the inventor rather than the specific problem solved by the invention); Cross Med. Prods., Inc. v. Medtronic Sofamor Danek, Inc., 424 F.3d 1293, 1323, 76 USPQ2d 1662, 1685 (Fed. Cir. 2005) ("One of ordinary skill in the art need not see the identical problem addressed in a prior art reference to be motivated to apply its teachings."); In re Lintner, 458 F.2d 1013, 173 USPQ 560 (CCPA 1972) (discussed below); In re Dillon, 919 F.2d 688, 16 USPQ2d 1897 (Fed. Cir. 1990), cert. denied, 500 U.S. 904 (1991). Further, applicant argues that Cui does not teach or suggest the claimed two-dimensional vector (now being amended to two-dimensional observation vector). Applicant argues that the input to the Kalman as taught by Cui, is likely multi-dimensional because U (position) itself is likely multi-dimensional. The argument is not persuasive, because U (or L) and V are two components indicating position and its corresponding velocity, See paragraph [0025] of Cui. It has not been disclosed in Cui that position is multi-dimensional. However, for the purpose of compact prosecution, and in the event Cui doesn’t explicitly teach the input of Kalman filter being two-dimensional vector, the newly added reference, Riewe et al., US 20030216865 also teaches the claimed feature. See final Office Action Below.
Dependent claims continue to stand rejected as no separate arguments were presented other than the arguments made for the independent claims. Thus, the rejections of these claims are maintained.
Office Note: Due to applicant’s amendments, further claim rejections appear on the record as stated in the below Office Action.
It is the Office’ stance that all of applicant arguments have been considered.
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.
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, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et a., US 20210310809 A1, hereinafter “Chen”, in view of Cui et al, CN 104076382 A, hereinafter “Cui”, or in alternative rejection in view of Riewe et al., US20030216865, hereinafter “Riewe”, further in view of Titterton and Weston (Strapdown Inertial Navigation Technology, 2nd Edition, 2004), hereinafter “” Titterton and Weston” or Steinhardt et al., US 20150142390, hereinafter “Steinhardt” A1, in alternative rejection.
Regarding claims 1, 12, and 19, Chen discloses A navigation information processing method (Abstract, “a dead reckoning method for a vehicle”, [0033], “Dead reckoning may be applied to scenes such as vehicle navigation and the like. For example, the dead reckoning method for a vehicle in an embodiment of the present application is executed by a vehicle controller, to obtain accurate information such as a position and attitude and a speed and assist navigation.”), and an electronic device comprising a memory and a processor ([0225]), wherein the memory is configured to store a computer program ([0226]), and the processor runs the computer program to cause the electronic device to perform a navigation information processing method ([0225], claim 18), and a non-transitory computer-readable storage medium on which a computer program is stored ([0226]), wherein when the computer program is executed by a processor, a navigation information processing method is implemented ([0225], claim 18) comprising: acquiring motion state information of a vehicle based on an inertial device ([0027], “an inertial measurement unit (IMU)”, [0103], “The three-axis angular speed and acceleration can be obtained according to the IMU, and be used for an a priori estimation of the position and attitude.”, and Fig. 6), and acquiring vehicle information of the vehicle based on a controller area network ([0103], “a wheel speed controller area network (CAN)”, and Fig. 6); fusing the navigation information and the vehicle information by using a preset Kalman filter to obtain target navigation information (e.g., Figs. 1-4 and Fig. 6, and [0003], [0027], “adopting a Kalman filtering model, to obtain a posteriori position and attitude estimation.”, [0036]-[0037], [0118-[0121]), and navigating the vehicle based on the target navigation information ([0172]).
Although Chen discloses a dead reckoning system for a vehicle includes an inertial measurement unit (IMU), however, Chen doesn’t explicitly disclose performing a strapdown solution on the motion state information to obtain navigation information. However, a strapdown solution/algorithm is a well-known method in the art as being taught, for example, by Titterton and Weston (Strapdown Inertial Navigation Technology, 2nd Edition, 2004) or as an another example as being taught as one of the vehicle positioning technology by Cui ([0006], [0013], “Strapdown Inertial Navigation System” and at least [0018]- [0025], [0038]- [0043]),). Furthermore, for the purpose of compact prosecution, Steinhardt teaches the limitation of performing a strapdown solution on the motion state information to obtain navigation information (e.g., [0011], “a strapdown algorithm is carried out, by means of which at least the sensor signals of the inertial sensor arrangement are processed to form, in particular corrected, navigation data and/or driving dynamics data, relative to the vehicle in which the sensor system is arranged.”)
Chen doesn’t disclose that wherein the vehicle information as an input vector of the Kalman filter is a two-dimensional vector.
Although, Cui teaches the vehicle information as an input vector of the Kalman filter is a two-dimensional observation vector ([0020], “Kalman filter for position information and speed (U, V1), (L2, V2), (L3, V3)”, __Kalman filter for position and speed reads on input vector of Kalman filter being a two-dimensional vector__), however, for the purpose of compact prosecution and in the event Cui doesn’t explicitly teaches the claimed feature, Riewe also teaches the vehicle information as an input vector of the Kalman filter is a two-dimensional observation vector (at least [0016], [0046], “speed data”, [0054], [0062], “a two-dimensional observation, which is provided to the Kalman filter”, [0063])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and apparatus for a vehicle as taught by Chen with performing strapdown inertial navigation algorithm/solution as taught by Steinhardt in sensor system arranged in a vehicle, or as taught by Cui or Titterton and Weston, as alternative, with a reasonable expectation of success, with the motivation of enabling continuous and reliable position and orientation estimation especially in GPS-denied environments. This approach eliminates the need for mechanical gimbals, reduces system complexity and cost, and provides navigation performance in time durations where positioning signals may be unavailable or unreliable.
Regarding claims 2 and 13, Chen discloses wherein the acquiring motion state information of a vehicle based on an inertial device comprises: acquiring a three-axis acceleration and a three-axis angular velocity of the vehicle based on the inertial device ([0027], and Fig. 6, “three-axis gyroscope and three-axis acceleration information of the IMU (Inertial Measurement Unit)”); calculating position coordinates (e.g., [0006], “obtaining a position and attitude increment of the vehicle”, [0035], “position and attitude information of the vehicle may include position coordinates and a body attitude angle of the vehicle.”), a three-dimensional motion velocity ([0100]), and an attitude quaternion of the vehicle based on the three-axis acceleration and the three-axis angular velocity ([0027], “three-axis gyroscope and three-axis acceleration information of the IMU are integrated to obtain apriori predictions of the attitude, speed and position of a vehicle.”, [0081], “a vehicle attitude quaternion”); and constructing a state vector of the vehicle based on the position coordinates, the three-dimensional motion velocity, and the attitude quaternion (e.g., [0081]-[0086], “prediction of the position and attitude state”, [0109]-[0114], __predication state as is disclosed in the reference, reads on constructing a state vector __), and using the state vector as the motion state information ([0114]).
Claims 3-6, 10-11, 14-15, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, in view of Cui (or Riewe, in alternative rejection), further in view of Titterton and Weston or Steinhardt, in alternative rejection and further in view of Adams et al., US11254323, hereinafter “Adams”.
Regarding claims 3 and 14, Chen in view of prior arts relied upon discloses the navigation information processing method according to claim 1, and Although Chen, according to Fig. 1, and paragraph [0103], discloses a wheel speed controller area network (CAN) which implicitly meets the limitation of acquiring vehicle information of the vehicle based on a controller area network comprises: acquiring, based on the controller area network, however, Chen doesn’t explicitly teach wherein the acquiring vehicle information of the vehicle based on a controller area network comprises: acquiring, based on the controller area network, a target steering angle and a target movement velocity of the vehicle in a target time period;
Nevertheless, Cui teaches wherein the acquiring vehicle information of the vehicle based on a controller area network comprises: acquiring, based on the controller area network, a target steering angle and a target movement velocity of the vehicle in a target time period (e.g., “The invention extracted from CAN bus vehicle speed, steering wheel angle and other information, so as to perform fusion with the SINS”);
Furthermore, although Chen implicitly teaches calculating a velocity residual value of the target movement velocity (e,g., (e.g., [0044], “position increment [] on the basis of [] and a heading angle”, [0055], [0066], [0077],__heading difference reads on velocity residual__, also claim 16, ); however Chen, doesn’t explicitly teach calculating an angle residual value of the target steering angle and a velocity residual value of the target movement velocity and using the target steering angle and the target movement velocity as the vehicle information when the angle residual value is less than a first preset threshold and the velocity residual value is less than a second preset threshold.
Nevertheless, Adams teaches calculating an angle residual value of the target steering angle and a velocity residual value of the target movement velocity (Abstract, “residual associated with a measurement corresponding to the state”, and at least, Col 2, Lines 25-34, Col 7, Lines 50-54), “determine the state of the vehicle 102 based on one or more odometry sensors 110. The odometry sensors may include wheel speed sensors, motor speed sensors, steering angle sensors, and the like., Fig. 6, __the states of the vehicle as disclosed in the reference are steering angle and speed and determining residual associated with the state reads on the limitation”, and using the target steering angle and the target movement velocity as the vehicle information when the angle residual value is less than a first preset threshold and the velocity residual value is less than a second preset threshold (at least Fig. 2, Block 216 and 218, Col 10 last paragraph and Col 11, Lines 1-12, Col 11, second paragraph).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and apparatus for a vehicle as taught by Chen with performing strapdown inertial navigation algorithm/solution as taught by Steinhardt and further using CAN to acquire vehicle information as taught by Cui and determining the state of the vehicle based on the obtained residual value of the state data in a time period being less than a preset error threshold, with a reasonable expectation of success, because using CAN in navigation enable efficient and reliable communication between various electronic components as and also determining the state of the vehicle over time based on determining the residual and monitoring the error based by comparing the residual value to a predetermined threshold, increase the accuracy of the navigation information by using the input veicle state value smaller that a predetermined threshold(error) or correcting the value if they are greater than the predetermined threshold.
Regarding claims 4 and 5, Chen in view of prior arts relied upon discloses the navigation information processing method according to claim 3, however, Chen doesn’t explicitly disclose calculating a difference between adjacent target movement velocities [steering angles] in the target time period to obtain a plurality of velocity/angle difference values; determining a first [second] quantity of velocity [angle] difference values greater than a preset velocity [angle] value in the plurality of velocity [angle] difference values; and summing the first [second] quantity of velocity [angle] difference values greater than the preset velocity value to obtain a velocity [angle] difference value sum, wherein the calculating a velocity/angle residual value of the target movement velocity [steering angle] comprises: calculating the velocity [angle] residual value of the target movement velocity [steering angle] by using a velocity [angle] residual value calculation formula, wherein the velocity [angle] residual value calculation formula is as follow:
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[
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], wherein
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[
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] is the velocity [angle] residual value,
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[
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] is the velocity [angle] difference value sum, and m [n] is the first [second] quantity. (Note: limitations of claim 5 are added in brackets, [ ], and superseded the previous word/term)
However, the claims recite calculation formulas, respectively, for velocity residual value and angle residual value. Under the broadest reasonable interpretation of the examiner and as the best of the examiner’s knowledge, these formulas are not a standard measure of residual values. Therefore, they are interpreted as a custom bias measure (a custom indicator of the bias for measuring bias). For example, in claim 4, the numerator (i.e.,
V
s
u
m
), in the recited formula, shows the absolute values of the summation of the velocity difference (residuals) which is interpreted as the total bias in the residuals where then divided by the square of the number of the values (or first quantity as recited in the claim), in order to penalize for the data quantity. The higher number in denominator by using the square of the number of values, makes the value shrinks quickly with more data. There for under the examiner’s BRI, this formula is a custom indicator of normalized bias, in order to use in Kalman filtering for improving the accuracy of the navigation information estimation. For the purpose of compact prosecution, for example, Adams, at least in Col 3, Last two paragraphs, teaches in a similar method using the normalized residual for monitoring the localization error and controlling the vehicle based on the comparison of the residual value to a threshold.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and use velocity/angle residual value as a custom formulation as, for example, taught by Adams, in order to detect the discrepancies between the measures values in adjacent time and indicate the bias in the system and use in Kalman filtering for improving the accuracy of the navigation information estimation.
Regarding claims 6 and 15, Modified Chen teaches the navigation information processing method according to claim 3, wherein the acquiring, based on the controller area network, a target steering angle and a target movement velocity of the vehicle in a target time period comprises: acquiring, based on the controller area network, a steering angle and a movement velocity of the vehicle in the target time period (See rejection for Claim 3);
However, modified Chen doesn’t teach determining a first difference value which refers to a time between acquiring the steering angle and acquiring the motion state information, and a second difference value which refers to a time between acquiring the movement velocity and acquiring the motion state information; and using the steering angle as the target steering angle and using the movement velocity as the target movement velocity when both the first difference value and the second difference value are less than a preset difference value.
Nevertheless, Adams teaches determining a first difference value which refers to a time between acquiring the steering angle and acquiring the motion state information, and a second difference value which refers to a time between acquiring the movement velocity and acquiring the motion state information (__Adams discloses acquiring the residual and state of the vehicle at first and second time according to Fig. 6 and the associated paragraphs. It is also disclosed that the determination of the target measurement (according to the associated errors) is made based on comparing the time between the first and second with a threshold amount of time (See mapping for the next limitation for further clarification)__); and using the steering angle as the target steering angle and using the movement velocity as the target movement velocity when both the first difference value and the second difference value are less than a preset difference value. (Fig 6 at least steps 616 and 610, Col 16 Last paragraph, Col 29, Lines 51-62, __According to the at least cited paragraphs of Adams, system determines whether the residual is remained at or above the threshold for at or more than a threshold amount of time (reads on a preset difference value in the claim that refers to a preset time difference value). If so, the system identifies an error associated with a sensor or component of the vehicle, and applies correction factors. According to Col 30, Lines 14-20, if the first residual is less than a threshold period of time, the second measurement of a quantity of interest (e.g. pitch, velocity) (reads on target steering angle and target velocity) can be associated as the first measurement (measurement in the previous time, which reads on the acquired data (like steering angle and velocity), Col 30, Lines 21-30. Therefore, the disclosure of Adams teaches the features recited in the claim. Adams discloses acquiring the residual and state of the vehicle at first and second time according to Fig. 6 and the associated paragraphs. Further according to Fig. 6 and its corresponding paragraphs, the time difference is used to measure the time period (time difference) of changing that value/residual which is used by the controller to determine if the time period is higher that a time threshold. In other words, if the time period is shorter than a threshold time period, the value is determined based on the acquired value in the previous time, which reads on the features in the claim. __)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and apparatus for a vehicle as taught by Chen with performing strapdown inertial navigation algorithm/solution as taught by Steinhardt and further using CAN to acquire and filter vehicle information as taught by Cui (or Riewe) and determining a time difference between acquiring steering angle and state information and also a time difference between acquiring velocity and motion state information and also a time difference between acquiring the velocity and motion state information and use those time differences for the determination of the target steering angle and target velocity by comparing it with a threshold time difference as taught by Adams, with a reasonable expectation of success, with the motivation of increasing the accuracy and efficiency of the navigation information.
Regarding claims 10, 18, 20, Chen in view of the prior arts relied upon, discloses the navigation information processing method according to claim 1 (See rejection of claim 1), the electronic device according to claim 12 (See rejection for claim 12) and the non-transitory computer-readable storage medium according to claim 19 (See rejection for claim 19), wherein the vehicle information comprises a steering angle ([0035], [0047], [0049], “heading angle of the center of the rear axle,”, [0125], “heading angular speed”, (__under the broadest reasonable interpretation of the examiner “Heading angle” in the references refers to “steering angle” as recited in the claim__) and a movement velocity (e.g., [0028], “vehicle speed information”), and the fusing the navigation information and the vehicle information by using a preset Kalman filter to obtain target navigation information ((e.g., Figs. 1-4 and Fig. 6, and [0003], [0027], “adopting a Kalman filtering model, to obtain a posteriori position and attitude estimation.”, [0036]-[0037], [0118-[0121]),),
Although Chen discloses comprises obtaining a velocity residual value of the movement velocity (e.g., [0044], “position increment [] on the basis of [] and a heading angle”, [0055], [0066], [0077],__heading difference reads on velocity residual__, also claim 16, ); forming the two-dimensional observation vector by using the steering angle and the movement velocity ([0072], “obtain a heading observation of the vehicle at the current moment, on the basis of the heading increment of the vehicle and a heading angle of the vehicle”, [0214], claim 6, claim 16, __heading increment of the vehicle which is obtained on the basis of the wheel speed information ([0064]) reads on the movement velocity and the heading angle reads on steering angle__), and forming an observation noise by using the angle residual value and the velocity residual value (at least [0117], “observation noise”, [0214], [0216], “calculating a heading difference value between the heading observation of the vehicle at the current moment and a heading apriority of the vehicle at the current moment”) [0219], ; calculating a Kalman gain value of the Kalman filter based on the observation noise (at least [0083]-[0087], [0116]-[0117], “Kalman gain”, “observation matrix”, “covariance matrix”); and performing data correction on the navigation information based on the two-dimensional observation vector and the Kalman gain value to obtain the target navigation information ([0055], “inputting the position difference value into a Kalman filtering model, and obtaining an optimal position estimation at the current moment.”, [0056]-[0057], [0060], “the position difference value between the position observation at the current moment and the position apriority of the vehicle at the current moment is input into the Kalman filtering model, so that a more accurate optimal position estimation at the current moment is obtained.”).
However, Chen doesn’t explicitly disclose an angle residual value of the steering angle.
Nevertheless, Adams teaches obtaining an angle residual value of the target steering angle (Abstract, “residual associated with a measurement corresponding to the state”, and at least, Col 2, Lines 25-34, Col 7, Lines 50-54), “determine the state of the vehicle 102 based on one or more odometry sensors 110. The odometry sensors may include wheel speed sensors, motor speed sensors, steering angle sensors, and the like., Fig. 6, __the states of the vehicle as disclosed in the reference are steering angle and speed and determining residual associated with the state reads on the limitation”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and apparatus to obtain navigation information as taught by Chen with adding the step of obtaining angle residual value of the steering angle as taught by Adams, in order to improve the accuracy of the navigation information by considering using correct data for both velocity and steering angle in the process which improve the accuracy and reliability of the method.
Regarding claim 11, Chen in view of prior arts relied upon teaches the navigation information processing method according to claim 10, wherein the performing data correction on the navigation information based on the two-dimensional observation vector and the Kalman gain value to obtain the target navigation information (e.g., Fig. 1-4, Fig. 6) comprises: performing, by using a data correction formula, the data correction on the navigation information based on the two-dimensional observation vector and the Kalman gain value to obtain the target navigation information (Fig. 2, Fig. 4, and at least [0036], [0055], “obtaining an optimal position estimation at the current moment”, [0060], “a more accurate optimal position estimation at the current moment is obtained.”, [0082]-[0087]), wherein the data correction formula is as follow:
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wherein
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is the target navigation information at a current time;
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is a target navigation information at a previous time of the current time;
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is the two-dimensional observation vector; and
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is the Kalman gain value that is equal to
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, wherein
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is a transition matrix,
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is a covariance, and
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is the observation noise. (See equation written in paragraph [0083], __ the reference use the same formula for estimating posterior position and attitude which read on target navigation that is calculated as recited in the claim with the same formula. According to cited paragraph, the terms in both formula recited in the two formulas recited in the claim are also have the same definition as the corresponding terms in the formulas disclosed in para [0084]-[0085]__)
Claims 7-9 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, in view of Cui (or Riewe), further in view of Titterton and Weston (or in alternative rejection for one of the claimed limitations, in view of Garrett et al., US 20150362320 A1, hereinafter “Garrett”) and further in view of a known mathematical method, for example, at https://lpsa.swarthmore.edu/NumInt/NumIntFourth.html, hereinafter “Fourth-Order”.
Regarding claims 7 and 16, Chen in view of prior arts relied upon teaches the navigation information processing method according to claim 1, wherein the motion state information comprises position coordinates (e.g., [0006], “obtaining a position and attitude increment of the vehicle”, [0035], “position and attitude information of the vehicle may include position coordinates and a body attitude angle of the vehicle.”), a three-dimensional motion velocity ([0100]), and an attitude quaternion ([0081], “q.sub.k+1 represents a vehicle attitude quaternion”, separately performing differentiation on the position coordinates (Chen, [00012], “partial derivative of the position”), the three-dimensional motion velocity ([0008], vx, vy and, vz), and the attitude quaternion to obtain a first derivative result ([0027], “three-axis gyroscope and three-axis acceleration information of the IMU are integrated to obtain apriori predictions of the attitude, speed and position of a vehicle.”, [0081], “a vehicle attitude quaternion”);
However, Chen doesn’t disclose the performing a strapdown solution on the motion state information to obtain navigation information comprises: separately performing differentiation on the position coordinates, the three-dimensional motion velocity, and the attitude quaternion to obtain a first derivative result; wherein a derivative result of the three-dimensional motion velocity is a three-dimensional motion acceleration; (Note: the unbolded part of the claim is taught by Chen however not under the strapdown solution) wherein a derivative result of the three-dimensional motion velocity is a three-dimensional motion acceleration (This limitation is inherent based on mathematical fact); performing bias correction on the three-dimensional motion acceleration in the first derivative result to obtain a second derivative result; and performing fourth-order approximation operation on the second derivative result to obtain the navigation information.
Nevertheless, Titterton and Weston (Strapdown Inertial Navigation Technology, 2nd Edition, 2004) teaches performing a strapdown solution on the motion state information to obtain navigation information (e.g., Chapter 2 and 3) comprises: separately performing differentiation on the position coordinates (e.g., Chapter 2 and 3, at least as an example Section 3.4.1, page 23, Eqn. (3.1)), the three-dimensional motion velocity (e.g., Chapter 2 and 3, at least as an example Section 3.4.2, page 24, Eqn. (3.4)), and the attitude quaternion to obtain a first derivative result (Section 3.5, Page 25-27, Eqns. (3.10)-(3.12)), wherein a derivative result of the three-dimensional motion velocity is a three-dimensional motion acceleration (It is inherent due the mathematical fact); Furthermore, although Titterton and Weston teaches performing bias correction on the three-dimensional motion acceleration in the first derivative result to obtain a second derivative result (e.g., Section 3.5.3, Page 32, last paragraph “A correction for the acceleration caused by the vehicle’s velocity over the surface of a rotating Earth”, Page 33, Fig. 3.15, block “Coriolis correction”), Garrett, also teaches performing bias correction on the three-dimensional motion acceleration in the first derivative result to obtain a second derivative result (Garrett, [0017]);
Furthermore, the limitation of performing fourth-order approximation operation on the second derivative result to obtain the navigation information, is a well-known method of approximation in mathematics as for example and for the purpose of compact prosecution is taught at https://lpsa.swarthmore.edu/NumInt/NumIntFourth.html.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and apparatus for a vehicle as taught by Chen with performing strapdown inertial navigation algorithm/solution as taught by Titterton and Weston, with a reasonable expectation of success, with the motivation of obtaining high-rate estimates of vehicle state information by using inertial measurement devices enabling continuous and reliable estimation of the navigation in GPS-denied environments. Furthermore, using the fourth-order approximation operation to improve accuracy of the navigation information.
Regarding claim 8 and 17, Chen in view of prior arts teaches the navigation information processing method according to claim 7, however, Chen doesn’t explicitly teaches the performing bias correction on the three-dimensional motion acceleration in the first derivative result to obtain a second derivative result comprises: performing the bias correction on the three-dimensional motion acceleration by using a preset calculation formula to obtain an acceleration correction result, and forming the second derivative result by using a derivative result of the position coordinates, a derivative result of the attitude quaternion, and the acceleration correction result, wherein the preset calculation formula is as follow:
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, wherein
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is an acceleration correction result,
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is a navigation coordinate system,
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is a three-dimensional motion acceleration,
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is a Coriolis acceleration caused by vehicle motion and rotation of the earth,
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is a centripetal acceleration to the ground caused by the vehicle motion, and
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is a gravitational acceleration.
However, Titterton and Weston (Strapdown Inertial Navigation Technology, 2nd Edition, 2004) teaches the performing bias correction on the three-dimensional motion acceleration in the first derivative result to obtain a second derivative result comprises: performing the bias correction on the three-dimensional motion acceleration by using a preset calculation formula to obtain an acceleration correction result, and forming the second derivative result by using a derivative result of the position coordinates, a derivative result of the attitude quaternion, and the acceleration correction result, wherein the preset calculation formula is as follow:
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, wherein
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is an acceleration correction result,
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is a navigation coordinate system,
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is a three-dimensional motion acceleration,
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is a Coriolis acceleration caused by vehicle motion and rotation of the earth,
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is a centripetal acceleration to the ground caused by the vehicle motion, and
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is a gravitational acceleration. (Section 3.5.3, page 32, formula (3.27) and the definition of terms in the preceding paragraphs reads on the claim, Section 3.5.1 and 3.5.2, Page 27, third paragraph, “
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is the acceleration caused by its velocity over the surface of a rotating Earth, usually referred to as the Coriolis acceleration.”, also Page 32, last paragraph “A correction for the acceleration caused by the vehicle’s velocity over the surface of a rotating Earth, usually referred to as the Coriolis acceleration.”, Page 33, Fig 3.15, block “Coriolis correction”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and apparatus for a vehicle as taught by Chen with performing strapdown inertial navigation solution as taught by Titterton and Weston, with a reasonable expectation of success, with the motivation of increasing the accuracy of the navigation system.
Regarding claim 9, Chen in view of prior arts relied upon teaches the navigation information processing method according to claim 7 (See rejection of claim 7), however, Chen doesn’t teach wherein the performing fourth-order approximation operation on the second derivative result to obtain the navigation information comprises: performing the fourth-order approximation operation on the second derivative result by calculating a slope to obtain the navigation information, wherein a process of calculating the slope is as follow:
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wherein
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is the navigation information,
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is the second derivative result, K1 to K4 are the slopes at different times in the target time period from a beginning to an end, Xn to Xn+3 are the motion state information at different times in the target time period from the beginning to the end, Xn+1dot to Xn+3dot are derivative results at different times in the target time period from the beginning to the end, and dt is a time interval between two times.
However, the reference relied upon as Fourth-Order teaches the performing fourth-order approximation operation on the second derivative result to obtain the navigation information comprises: performing the fourth-order approximation operation on the second derivative result by calculating a slope to obtain the navigation information, wherein a process of calculating the slope is as follow:
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wherein
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is the navigation information,
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is the second derivative result, K1 to K4 are the slopes at different times in the target time period from a beginning to an end, Xn to Xn+3 are the motion state information at different times in the target time period from the beginning to the end, Xn+1dot to Xn+3dot are derivative results at different times in the target time period from the beginning to the end, and dt is a time interval between two times (__The equations represent Fourth Order Runge Kutta Method with is common method in mathematics that used in estimation of the state of a dynamic system., e.g., See https://lpsa.swarthmore.edu/NumInt/NumIntFourth.html. Furthermore, on page 3 of the cited reference, using the slopes as recited in the claim is taught, “We then use a weighted sum of these slopes to get our final estimate of y*(t₀+h)”, “weighted average slope approximation”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the dead reckoning method and apparatus for a vehicle as taught by Chen with performing strapdown inertial navigation solution as taught by Titterton and combining it with fourth order approximation which is a well-known mathematical method (for example, see Fourth-Order reference), with a reasonable expectation of success, with the motivation of improving the accuracy of the navigation system.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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/H.H./Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669