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
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55 with effective filing date of 11/15/2023.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/13/2024 is in compliance with the provisions of 35 CFR 1.97. Accordingly, the IDS has been considered by the examiner
Specification
The disclosure is objected to because of the following informalities:
[0022] recites “the inertial reference frame may indicates an orientation” – but should recite “the inertial reference frame may indicate[s] an orientation”.
[0156] recites “Figure 10A is a schematically illustrates a sensor device 100A according to some examples.” – but should recite “Figure 10A schematically illustrates a sensor device 100A according to some examples.”
[0175] recites “a higher weight may be assigned to the last equation that to the first two equations” – but should recite “a higher weight may be assigned to the last equation [that] than to the first two equations”.
Appropriate correction is required.
Claim Objections
Claim 1, 2, 4, objected to because of the following informalities:
Each recites the preposition “relative” without the word “to” — e.g., claim 1 recites determining an orientation “relative an inertial reference frame” and that the radar transceiver and IMU are “fixedly mounted relative each other.” Correction to “relative to” is required. The intended meaning is apparent, so this is treated as an objection to form rather than, standing alone, a basis for indefiniteness.
Claim 2 recites “parameters … comprises”, however, this should be “parameters … comprise”.
Claim 4 refers to “the advanced antenna array,” whereas claim 1 introduces “an advanced antenna array radar transceiver.” For precise correspondence, claim 4 should refer to “the antenna array of the advanced antenna array radar transceiver” or otherwise identify the intended antecedent.
Claim 6 recites “inertial gravity”, which is imprecise. In view of the specification, it appears that “inertial gravity” is intended to refer to gravitational acceleration g [0173-0174], or a gravity vector g [0099], expressed relative to the inertial reference frame. Clarification is needed.
Claims 10 and 13 recite determination “based on joint processing … subject to” the fixed mounting. For structural clarity, the fixed-mounting requirement should be set forth in a separate wherein clause.
Claim 14 should recite program code that, when executed by the processing circuitry, causes the processing circuitry to perform the method of claim 13.
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 1 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.
Independent claims 1, 10, and 13 recite an “advanced antenna array radar transceiver.” The term “advanced” is a relative term whose scope is unclear. The specification does not provide an objective standard for determining which antenna-array radar transceivers are “advanced,” as distinguished from those that are not advanced. It does not appear that the record establishes a recognized meaning in the art that supplies such a standard. What the metes and bounds of the claimed limitation is not clear. Claims 2–9 depend from claim 1, claims 11–12 depend directly or indirectly from claim 1, and claims 14–15 refer to the method of claim 13; therefore, each incorporates the indefinite terminology.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 14 rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim recites “A computer program product comprising program code” without limiting the product to a non-transitory medium. Under BRI, and in light of the specification — which states that the disclosed computer program “may be implemented … stored on a transitory or non-transitory computer-usable or computer-readable storage medium” ([0265]) — the broadest reasonable interpretation of this claim encompasses a transitory, propagating signal (software/signal per se), which does not fall within any of the four statutory categories of § 101. See MPEP § 2106.03; In re Nuijten, 500 F.3d 1346 (Fed. Cir. 2007). The contrast with claim 15, which expressly recites a “non-transitory” medium, confirms that the omission in claim 14 is meaningful. The claim can be amended to recite a non-transitory medium (e.g., “A non-transitory computer-readable medium storing program code which, when executed by the processing circuitry, performs the method of claim 13”).
Claim Rejections - 35 USC § 103
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 1-3, 5, and 9-15 are rejected under 35 U.S.C. 103 as being unpatentable over Bando et al. (US 2018/0312170 A1) in view of Cao et al. (US 2016/0291143 A1).
Regarding Claims 1, 10, and 13, claims 1, 10, and 13 are independent claims directed, respectively, to a sensor device, a computer system, and a computer-implemented method. The functional content of claims 10 and 13 is substantively identical to claim 1, differing only in statutory category and in reciting the fixed mounting as a condition on the acquired data rather than as a positive structural element.
Regarding Claims 1, 10, and 13, Bando et al. (‘170) in view of Cao et al. (‘143) teaches:
Bando et al. (‘170) teaches: A sensor device comprising: a device mounted on the vehicle body that integrates plural motion sensors and estimation circuitry ([0034]: “the vehicle body 103 of the dump truck 100 is installed with: a vehicle-body IMU 104 …; a road-surface distance measurement device 105 …; … and a vehicle-body attitude measurement device 108”; [0035]: “the dump truck 100 further includes a vehicle-body slip angle estimation device 120”. The cooperating IMU, road-surface distance/velocity measurement device, and estimation device mounted to the common vehicle body constitute the claimed sensor device.
Bando et al. (‘170) does not explicitly teach, but Cao et al. (‘143) teaches: an advanced antenna array radar transceiver configured to measure motion of the radar device relative to the external environment ([0059]: “The receive antenna 16 has an array structure, for example, and is configured with plural antennas”; [0008]: “a radar movement estimator that estimates a radar movement velocity and a radar movement direction of the radar based on the reflected wave”; [0051]: “The transmit antenna 15 and the receive antenna 16 of the radar device 411 are fixed to a vehicle 511 at least in use”). Cao et al. (‘143)’s radar transceiver, employing a receive antenna of array structure comprising plural antenna elements, estimates the movement velocity and movement direction of the radar device itself relative to the surrounding stationary environment from the Doppler content of the reflected waves, thereby measuring motion of the sensor device relative to an external surface and providing corresponding radar data.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the road-surface-facing millimeter-wave radar of Bando et al. (‘170) as the array-antenna radar transceiver of Cao et al. (‘143). One would have been motivated to do so because Cao et al. (‘143) teaches that a receive antenna of array structure lets the radar estimate its own movement velocity and direction robustly and “highly accurately” even during wheel slip ([0009]), supplying the same vehicle-body-relative velocity Bando et al. (‘170)’s radar provides but with added arrival-direction resolution. There is a reasonable expectation of success because both references measure vehicle-body velocity from the Doppler content of radar returns in the same automotive context, and Cao et al. (‘143) demonstrates an array-antenna radar fixed to the vehicle body operating successfully ([0051]).
Bando et al. (‘170) teaches: a radar transceiver configured to measure motion of the sensor device relative to an external surface in a reference frame of the sensor device and provide corresponding radar data ([0072]: “The vehicle-body speed measurement device 1303 also engages in measurement of a relative velocity between the vehicle body 103 and the road surface with a millimeter-wave radar mounted directly to the vehicle body 103”; [0084]:“The vehicle-body speed measurement device 1303 can measure a velocity of the vehicle body 103 in the direction of each axis of the vehicle-body coordinate system b relative to the road surface”). Bando et al. (‘170)’s millimeter-wave radar thus measures the motion (relative velocity) of the vehicle body relative to the road surface (an external surface) expressed in the vehicle-body coordinate system (a reference frame of the sensor device), and provides the resulting velocity as radar data.
Bando et al. (‘170) teaches: an inertial measurement unit, IMU, configured to measure motion of the sensor device in a reference frame of the sensor device and provide corresponding IMU data ([0034]: “a vehicle-body IMU 104 that measures angular velocity, acceleration including gravity acceleration, or the like, in the vehicle-body coordinate system b”; [0052]: “as the vehicle-body IMU 104, the use of a three-axis acceleration sensor and a three-axis gyro sensor installed for each of the Xb axis, the Yb axis and the Zb axis of the vehicle-body coordinate system b may be contemplated”). The vehicle-body IMU measures the acceleration and angular velocity of the vehicle body in the vehicle-body coordinate system (a reference frame of the sensor device) and outputs the measured quantities as IMU data.
Bando et al. (‘170) teaches: processing circuitry configured to determine an orientation of the sensor device relative an inertial reference frame based on joint processing of the radar data and the IMU data. Bando et al. (‘170)’s estimation device is processing circuitry ([0035]: “a computing and control device such as a CPU …; a storage device such as HDD … and ROM … storing a program …; and RAM”). Bando et al. (‘170) defines a gravity-referenced global coordinate system that is an inertial reference frame ([0028]:“an Xe axis and a Ye axis set on a plane crossing perpendicular to a gravity direction … is referred to as a global coordinate system e”) and determines the orientation of the vehicle body relative to that inertial frame as roll, pitch, and yaw angles ([0050]: “An attitude … includes three conversion parameters from the global coordinate system e to the vehicle-body coordinate system b, which are referred to as a roll angle Ψ, a pitch angle φ and a yaw angle θ”; [0051] - coordinate conversion matrix Ceb from the global to the vehicle-body coordinate system,). This determination by Bando et al. (‘170) is based on joint processing of the radar data and the IMU data where each of the radar/road-surface velocity device and the vehicle-body IMU outputs its measurement to the common estimation device ([0035]: “each of the vehicle-body IMU 104, the road-surface distance measurement device 105 … outputs a measurement result of the device to the vehicle-body slip angle estimation device 120”, [0035]), and the estimation device jointly processes both data streams using the orientation relative to the inertial frame to remove the gravity component from the IMU acceleration and to express the jointly processed motion in the road-surface frame ([0053]: “the coordinate conversion matrix … from the global coordinate system e to the vehicle-body coordinate system b … is used to remove the gravity term … from the output value vector … of the acceleration sensor … to calculate an acceleration vector … caused by the motion of the vehicle body 103”). Bando et al. (‘170) thereby determines an orientation of the sensor device (vehicle body) relative to an inertial reference frame in the course of jointly processing the radar data and the IMU data.
Bando et al. (‘170) teaches: wherein the advanced antenna array radar transceiver and the IMU are fixedly mounted relative each other ([0034]: “the vehicle body 103 of the dump truck 100 is installed with: a vehicle-body IMU 104 …; a road-surface distance measurement device 105 …”; [0040]: “the road-surface distance measurement device 105 secured to the vehicle body 103”).
Regarding Claim 2, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the sensor device of claim 1.
Bando et al. (‘170) teaches: wherein parameters of the orientation of the sensor device relative the inertial reference frame comprises one or more Euler angle(s) (θx, θy, θz) ([0050]: “three conversion parameters from the global coordinate system e to the vehicle-body coordinate system b, which are referred to as a roll angle Ψ, a pitch angle φ and a yaw angle θ”; [0051]: “it is considered that the Ze axis, the Ye axis and the Xe axis are rotated in this order by respective angles”). The roll, pitch, and yaw angles that Bando et al. (‘170) uses to parameterize the orientation of the vehicle body relative to the gravity-referenced global (inertial) coordinate system are Euler angles about the three axes.
Regarding Claim 3, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the sensor device of claim 1.
Bando et al. (‘170) teaches: wherein the IMU data comprises at least a longitudinal acceleration (ax), a lateral acceleration (ay), and a yaw angular speed (ωz) (Fig. 2, [0052]: “the use of a three-axis acceleration sensor and a three-axis gyro sensor installed for each of the Xb axis, the Yb axis and the Zb axis of the vehicle-body coordinate system b”; Fig. 13, [0072]: “a yaw rate sensor 1301 is provided to measure angular velocity around the Zb axis of the vehicle-body coordinate system b”). Bando et al. (‘170)’s three-axis accelerometer measures acceleration along the longitudinal Xb axis (ax) and the lateral Yb axis (ay), and Bando et al. (‘170)’s gyro/yaw-rate sensor measures the angular velocity about the vertical Zb axis (ωz), so the IMU data comprises at least the recited longitudinal acceleration, lateral acceleration, and yaw angular speed.
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Regarding Claim 5, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the sensor device of claim 1.
Bando et al. (‘170) teaches: wherein the radar data comprises at least a longitudinal speed (νx), a longitudinal acceleration (ν̇x), and a lateral acceleration (ν̇y) ([0084]: “The vehicle-body speed measurement device 1303 can measure a velocity of the vehicle body 103 in the direction of each axis of the vehicle-body coordinate system b relative to the road surface”; [0084]: a time rate of change of the measured velocity is computed as acceleration, [0063]: “ν̇ may be a first order derivative value of a speed V … which may assume a difference at the time of sampling”). Bando et al. (‘170)’s radar-based vehicle-body speed measurement device provides the velocity of the vehicle body along each axis relative to the road surface including the longitudinal speed νx along the Xb axis and Bando et al. (‘170) computes the corresponding accelerations (longitudinal ν̇x and lateral ν̇y) as first time-derivatives of those measured velocities, so the radar data comprises at least the recited longitudinal speed, longitudinal acceleration, and lateral acceleration.
Regarding Claim 9, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the sensor device of claim 1.
Bando et al. (‘170) teaches: wherein the processing circuitry is further configured to acquire an orientation of the sensor device relative the external surface, and to determine an orientation of the external surface relative the inertial reference frame based on the orientation of the sensor device relative the external surface and the orientation of the sensor device relative the inertial reference frame. Bando et al. (‘170) acquires the orientation of the sensor device (vehicle body) relative to the external surface (road surface) as the coordinate conversion matrix Crb ([0036]: “The attitude-toward-road-surface estimation section 121 uses a series of distances from the road surface … to estimate a relative inclination between the vehicle body 103 and the road surface as a coordinate conversion matrix Crb from the vehicle-body coordinate system b to the road-surface coordinate system r”), and separately determines the orientation of the vehicle body relative to the inertial (global) frame as Ceb ([0050-0051]). Because Bando et al. (‘170) expressly maintains the road-surface, vehicle-body, and gravity-referenced global coordinate systems concurrently and provides the conversion matrices among them, the orientation of the external surface relative to the inertial reference frame is obtained from the composition of the orientation of the vehicle body relative to the external surface (Crb) and the orientation of the vehicle body relative to the inertial frame (Ceb).
Regarding Claim 11, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the sensor device of claim 1.
Bando et al. (‘170) teaches: A vehicle comprising the sensor device of claim 1 ([0026]: “The dump truck 100 is configured to include front and rear, left and right vehicle wheels 101, an axle 102 …, and a vehicle body 103”). Bando et al. (‘170)’s dump truck is a vehicle that carries the sensor device (vehicle-body IMU, road-surface radar/velocity device, and estimation circuitry) established in claim 1.
Regarding Claim 12, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the vehicle of claim 11.
Bando et al. (‘170) teaches: wherein the external surface is a ground surface supporting the vehicle, and wherein the orientation of the sensor device relative the inertial reference frame indicates an orientation of the vehicle relative the inertial reference frame ([0030]: “a plane including points with which a plurality of the wheels 101 come into contact is referred to as a road surface, and the road surface on which the dump truck 100 operates is assumed to be an approximately flat plane”; Fig. 2, [0050] - roll/pitch/yaw of the vehicle body relative to the gravity-referenced global frame). In Bando et al. (‘170) the external surface is the road surface that supports the dump truck’s wheels, and the orientation of the vehicle body relative to the inertial (global) frame is, by definition, the orientation of the vehicle relative to that inertial frame.
Regarding Claim 14, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the subject matter from which claim 14 depends (the method of claim 13).
Bando et al. (‘170) teaches: A computer program product comprising program code for performing, when executed by the processing circuitry, the method of claim 13 ([0035]: “a storage device such as HDD … and ROM … storing a program executed by the vehicle-body slip angle estimation device 120 … and the software implements various functions of the attitude toward-road-surface estimation section 121, the on-road-surface inertia quantity calculation section 122 and the wheel slip angle estimation section 123”). Bando et al. (‘170)’s program code, executed by the estimation processing circuitry to carry out its coordinate-conversion and joint-processing functions, is a computer program product comprising program code for performing the method of claim 13.
Regarding Claim 15, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the subject matter from which claim 15 depends (the method of claim 13).
Bando et al. (‘170) teaches: A non-transitory computer-readable storage medium comprising instructions, which when executed by the processing circuitry, cause the processing circuitry to perform the method of claim 13 ([0035]: “a storage device such as HDD (Hard Disk Drive) and ROM (Read Only Memory) storing a program executed by the vehicle-body slip angle estimation device 120”). Bando et al. (‘170)’s HDD/ROM storing the executable program is a non-transitory computer-readable storage medium whose instructions, when executed by the estimation processing circuitry, cause it to perform the method of claim 13.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Bando et al. ‘170) in view of Cao et al. (‘143), and further in view of Beez et al. (US 2005/0116854 A1).
Regarding Claim 4, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the sensor device of claim 1.
Bando et al. (‘170) in view of Cao et al. (‘143) does not explicitly teach, but Beez et al. (‘854) teaches: advanced antenna array is configured to illuminate different parts of the external surface to measure radial velocity and distance to the external surface in several different azimuth and elevation angles relative the external surface; ([0028]: “Each of patches 20 thus generates a lobe 28 … which is directed parallel to roadway surface 12. In contrast, patch 22 generates a lobe 30 … which is directed obliquely to roadway surface 12”; [0029]: “the three lobes 28 generated by patches 20 are also angularly displaced with respect to one another in the horizontal plane … thus forming a multibeam radar having a localization region fanned out over its width”; [0031]: “it is thus possible to determine the distance between radar sensor 10 and approximate point of incidence P of lobe 30 on roadway surface 12, as well as the components of the speed of the vehicle (of radar sensor 10) relative to roadway surface 12 along the axis of lobe 30”). Beez et al. (‘854)’s multibeam radar directs plural lobes onto the roadway surface at mutually different elevation angles (a lobe parallel to the roadway and a lobe oblique to the roadway) and at plural azimuth angles (three horizontally fanned lobes), and from the returns from the roadway surface it determines both the distance to the point of incidence on the roadway and the components of the vehicle’s speed relative to the roadway surface along the lobe axes. It illuminates different parts of the road surface to measure radial velocity and distance in several different azimuth and elevation angles relative to that surface.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to configure the array-antenna radar of the combination of Bando et al. (‘170) and Cao et al. (‘143) to illuminate the road surface with plural lobes at different azimuth and elevation angles, as taught by Beez et al. (‘854). One would have been motivated to do so because Beez et al. (‘854) teaches that directing a lobe obliquely to the roadway, in addition to parallel lobes, yields “a stronger and clearer radar echo” from the road surface for directly measuring the vehicle’s ground speed undistorted by wheel slip ([0009-0010]) - the same road-surface-relative velocity and range information the combination relies upon. There is a reasonable expectation of success because Beez et al. (‘854) measures both distance to, and speed relative to, the roadway surface using such lobes in the same automotive radar context, and the combination’s array antenna is inherently capable of forming plural directional lobes.
Claims 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Bando et al. (‘170) in view of Cao et al. (‘143), and further in view of Zeng et al. (US 2016/0299234 A1).
Regarding Claim 6, Bando et al. (‘170) in view of Cao et al. (‘143) teaches: the sensor device of claim 1.
Bando et al. (‘170) in view of Cao et al. (‘143) does not explicitly teach, but Zeng et al. (‘234) teaches: wherein the processing circuitry is configured to determine the orientation of the sensor device based on an underdetermined system of equations, defining a relationship among parameters of the orientation, the IMU data, the radar data, and inertial gravity (Zeng et al. (‘234) establishes the vehicle-body kinematic relation [0020]:
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eq. (1), in which “ga is the Earth gravitational vector in the inertia frame a”, “fb is the vehicle acceleration measured by accelerometers in the b-frame (IMU data)”, and ω is the “angular rates measured by gyros in the b-frame (IMU data)”. Zeng et al. (‘234) rearranges this relation to solve for the orientation, setting [0037]:
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and
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, and [0040] computes the roll angle φ and the pitch angle θ from the resulting rotation matrix).
The system so formed is underdetermined. Zeng et al. (‘234) states that [0026]: “the value Rabga is invariant to azimuth rotation, and thus only the roll and pitch angles of the vehicle are needed, where the yaw angle is set to zero” - that is, the scalar equations relating the orientation, the IMU output, and gravity do not determine all three orientation parameters, the yaw parameter being unresolvable from the relation itself. The velocity quantities entering the relation are obtained in part from radar returns off stationary objects, for which Zeng et al. (‘234) derives measurement equations whose error terms are [0042]: “introduced by radar Doppler measurements”. The relation therefore defines a relationship among parameters of the orientation, the IMU data, the radar data, and inertial gravity, and is underdetermined as claimed.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to determine the orientation in the combination of Bando et al. (‘170) and Cao et al. (‘143) from the equation system of Zeng et al. (‘234). One would have been motivated to do so because Zeng et al. (‘234) teaches that this relation yields the roll and pitch of a moving vehicle directly from the speed vector and the IMU output, dispensing with the dedicated vehicle-body attitude measurement device that Bando et al. (‘170) otherwise requires [0050]. There is a reasonable expectation of success because Zeng et al. (‘234) applies the relation to a road vehicle carrying a six-degree-of-freedom IMU and radar measuring velocity relative to stationary surroundings, the same sensor complement and operating context as the combination.
Regarding Claim 7, Bando et al. (‘170) in view of Cao et al. (‘143) and Zeng et al. (‘234) teaches: the sensor device of claim 6.
Zeng et al. (‘234) teaches: wherein the processing circuitry is configured to determine the orientation of the sensor device as a least squares solution to the underdetermined system of equations (Zeng et al. (‘234) solves Rabga = β by singular value decomposition, computing [0038-0039] “USVT=β(ga)T” and taking “the estimate for the rotation matrix Rab is: Re=UCVT”). The singular-value-decomposition solution of an equation of this form is the least squares solution for the rotation, minimizing the residual between Rabga and β; Zeng et al. (‘234) thereby determines the orientation as a least squares solution to the same underdetermined system relied upon for claim 6. This added limitation is supplied by Zeng et al. (‘234), already combined with Bando et al. (‘170) and Cao et al. (‘143) for claim 6; the motivation to combine is incorporated and applies here.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Bando et al. (‘170) in view of Cao et al. (‘143) and Zeng et al. (‘234), and further in view of Nilsson et al. (US 2014/0032068 A1) ].
Regarding Claim 8, Bando et al. (‘170) in view of Cao et al. (‘143) and Zeng et al. (‘234) teaches: the sensor device of claim 6.
Bando et al. (‘170) in view of Cao et al. (‘143) and Zeng et al. (‘234) does not explicitly teach, but Nilsson et al. (‘068) teaches: wherein the processing circuitry is configured to dynamically assign a respective weight to each equation of the underdetermined system of equations, the respective weight being based on a reliability of measurement data used by the equation (Nilsson et al. (‘068) estimates a vehicle road gradient by Claim 1: “conducting joint weighting of at least two input signals”, one “based on an accelerometer” and one “based on at least one force equation”, and determining “at least one weighting parameter for said sensor fusion on the basis of said detection of whether said at least one dynamic process is affecting said vehicle”. Where the detected dynamic process is a sharp turn, Nilsson et al. (‘068) gives Claim 7: “said input signal based on said force equation more influence in said sensor fusion than said input signal based on said accelerometer”. Nilsson et al. (‘068) clearly dynamically assigns a respective weight to each of the equations from which the gradient is estimated, the weight being set according to whether the detected condition affects the reliability of that equation’s measurement data.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to weight the individual equations of the orientation determination modified by Zeng et al. (‘234) according to the reliability of their measurement data, as taught by Nilsson et al. (‘068). One would have been motivated to do so because Nilsson et al. (‘068) teaches that an accelerometer based term and a force-equation term degrade under different driving conditions, so weighting each according to the condition detected gives a more accurate inclination estimate than weighting them equally. There is a reasonable expectation of success because Nilsson et al. (‘068) applies this weighting to the same class of accelerometer and vehicle-dynamics equations used in the combination, in a heavy-vehicle road-inclination context analogous to Bando et al. (‘170)’s.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kuragaki et al. (US 2004/0138802 A1) teaches ground-speed radar that indirectly measures pitch and roll from four radar sensors; not relied upon because it is radar-only (no IMU joint processing) and its pitch/roll are measured relative to the ground rather than derived, with an IMU, relative to an inertial frame — Bando et al. (‘170) is a stronger primary reference for the claimed radar–IMU architecture.
Hoffmann et al. (US 10,948,582 B2); Bialer et al. (US 2021/0011150 A1); Hamilton et al. (US 2022/0171069 A1) effectively teaches radar/array ego-velocity and slip-and-velocity measurement; similar to the advanced-antenna-array radar.
Kishigami et al. (US 2015/0198697 A1); Kurono et al. (US 2024/0192302 A1); Chen et al. (US 2022/0196798 A1); Shibata et al. (US 4,845,506) teaches antenna-array / antenna-system radar hardware; similar to Cao et al. (‘143) and Beez et al. (‘854) for the array and multi-lobe illumination teachings.
Kasaiezadeh et al. (US 2018/0297605 A1); Schiffmann et al. (US 2022/0126834 A1) teaches vehicle-dynamics/lateral-velocity and surface-friction estimation using inertial sensing; cumulative to Bando et al. (‘170) for the IMU/vehicle-body inertial teaching
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Prosecution Insights