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 .
35 USC § 101
Claims 1, 6, 7, and 9 are directed to patent-eligible subjected matter under 35
U.S.C. § 101. Although the claims recite processing and fusion of acceleration sensor signals, which may involve mathematical concepts, the claims, when considered as a whole, integrate any such judicial exception into a practical application. In particular, the claimed processing uses signals from multiple acceleration sensors of a vehicle and takes into account interference acceleration parameters representing mechanical vibrations acting on the sensor unit and the positional relationship between the sensor installation positions and movement axes of the vehicle. Accordingly, the claimed processing is specifically applied to take into account physical interference affecting vehicle acceleration measurements, thereby improving the accuracy and reliability of vehicle sensing. Thus, the claims reflect and improvement to another technology or technical field and are not directed to a judicial exception under Step 2A, Prong Two of the subject matter eligibility analysis. See MPEP §§ 2106.04(d)(1) and 2106.05(a).
Accordingly, claims 1-9 are patent-eligible under 35 U.S.C. § 101.
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.
Claims 1, 3, and 5-9 are rejected under 35 U.S.C. 103 as being unpatentable over
Baur et al. (Pub. No. US 2012/0303220) (hereinafter Baur) in view of Rothkopf et al. (Pub. No. US 2012/0078570) (hereinafter Rothkopf).
As per claims 1, 6, 7, and 9, Baur teaches a method/system for processing sensor signals of a sensor unit for a motor vehicle, including a first sensor for detecting a motion quantity, a computer for processing the sensor signal, and a second sensor for providing redundant sensor information (see ¶¶ [0005] and [0010]-[0011]). Baur specifically teaches that sensors of identical construction may be used as reference sensors for checking the plausibility of an event (see ¶ [0006]) and that the two sensors may have identical construction and/or identical operating effect (see ¶¶ [0010]-[0011]).
Baur further teaches embodiments in which the first and second sensors are specifically acceleration sensors. In the embodiment of Fig. 2, two acceleration sensors 11 and 12 determine acceleration in the x-direction, and in Fig. 3, acceleration sensors 13 and 14 determine acceleration in the z-direction (see ¶¶ [0024]-[0026]). The sensor signals are supplied to a computer where they are processed and/or post-processed and filtered (see ¶ [0021]). Thus, Baur teaches obtaining respective acceleration signals from first and second acceleration sensors of the same type and processing those signals together.
Regarding predefined interference acceleration parameters representing mechanical vibrations acting on the sensor unit, Baur explicitly explains that spatially separated sensors of the same construction and effect exhibit different dynamic signal curves due to different mechanical coupling, Baur identifies the resulting different vibration behavior as including “amplitude differences, phase shifts, and different resonance frequencies” and further explains that different vibration behavior occurs even when the sensors are positioned on the same printed circuit board, principally because of different distances from fastening points (see ¶ [0014]).
Accordingly, Baur explicitly recognizes that the measured signals of otherwise identical acceleration sensors contain position-dependent mechanical-vibration effects and that the sensor installation location/mechanical coupling determines the vibration interference appearing in the respective sensor outputs.
However, Baur fails to explicitly teach fusing the acceleration signals according to a processing specification that also takes into account predefined interference acceleration parameters representing the positional relationship between the installation positions of the acceleration sensors and movement axes of the vehicle.
Rothkopf, however, teaches receiving linear acceleration information from a plurality of accelerometers and processing the acceleration signals together by determining a relative acceleration between accelerometers and using the known distance between the accelerometers to determine angular motion (see ¶¶ [0024]-[0027]). The accelerometers may be positioned at opposite portions of the device and may be offset from likely axes of rotations (see ¶ [0025]).
Accordingly, Rothkopf teaches processing of acceleration signals dependent upon the spatial relationship of the acceleration-sensor installation positions to the relevant rotational/movement axes.
Rothkopf further teaches that the accelerometers are preferably positioned such that they do not lie along a common possible axis of rotation (see ¶¶ [0044]-[0046]). Thus, Rothkopf explicitly recognizes that the acceleration measured at each sensor depends upon the sensor’s installation position relative to an axis of vehicle/device movement or rotation.
Furthermore, Rothkopf explicitly applies this arrangement to a vehicle. Specifically, Rothkopf teaches that multiple accelerometers may be implemented in a vehicle such as a car or airplane (see ¶ [0042]) and Fig. 9 shows a vehicle having a first accelerometer near the rear and a second accelerometer near the front, including placement at opposite corners (see ¶ [0043]). Rothkopf further explains that the acceleration signals from these spatially separated sensors are processed so that common linear vehicle acceleration may be cancelled in the relative acceleration calculation, whereas position-dependent acceleration resulting from vehicle rotation can be determined (see ¶¶ [0044] and [0049]-[0055]).
Rothkopf also explicitly teaches fusion/combination of acceleration information from redundant accelerometers. With three or more accelerometers, angular-motion estimates obtained from different accelerometers pairs may be compared and the information may be averaged (see ¶¶ [0050]-[0054]). Rothkopf further explains that because the accelerometers occupy different positions, their relative accelerations are expected to differ and that, when more than one relative acceleration is usable, the values may be averaged together (see ¶¶ [0027]’ [0050] and [0053]).
It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify Baur’s processing of the signals of the redundant acceleration sensors to employ Rothkopf’s position-dependent processing and fusion of multiple accelerometer signals, such that the processing takes into account the known installation positions of the acceleration sensors relative to the vehicle movement/rotation axes., because Baur explicitly recognizes that the installation/mechanical coupling of otherwise identical acceleration sensors produces different vibration behavior, including amplitude differences, phase shifts, and different resonance frequencies (see ¶ [0014]), while Rothkopf teaches that signals from spatially separated accelerometers can be processed based upon their known positional relationship to axes of rotation to distinguish common translational acceleration from position-dependent rotational acceleration (see ¶¶ [0022]-[0027]), thereby reducing mechanically and positionally induced contributions to the acceleration measurement and providing a more reliable determination of vehicle motion.
As per claim 3, the combination of Baur and Rothkopf teaches the system as stated above. Baur further teaches that the mechanical vibrations represented by the interference acceleration parameters of the processing specification include a mechanical resonance of the sensor unit at the installation position (see ¶ [0014]).
As per claim 5, the combination of Baur and Rothkopf teaches the system as stated above. Rothkopf further teaches that the accelerations represented by the interference acceleration parameters of the processing specification are determined: (i) relative to multiple or all movement axes of the vehicle, and/or (ii) relative to at least one detection direction of the first and other acceleration sensors (see ¶¶ [0024], [0030]-[0033] and [0037], i.e., three accelerometers and determine a relative acceleration from acceleration information in each of several axes).
As per claim 8, the combination of Baur and Rothkopf teaches the system as stated above. Baur further teaches that the acceleration sensors of the sensor unit: (i) are arranged symmetrically with respect to a center of gravity of the vehicle and/or an intersection of the movement axes of the vehicle when they are installed in the vehicle, and/or (ii) are arranged in such a way that the mechanical vibrations and accelerations represented by the interference acceleration parameters of the processing specification act on the acceleration sensors in different directions (see ¶¶ [0021]-[0027], i.e., arranging two homogenous/redundant acceleration sensors at approximately the same location but with opposite orientations, such that one sensor produces a positive output and the other produces a negative output corresponding to the same acceleration. Baur teaches this arrangement for x-direction acceleration and z-direction acceleration). Baur also explicitly explains that mechanical coupling produces vibration effects including amplitude differences, phase shifts, and resonance-frequency differences (see ¶ [0014]).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Baur in view
of Rothkopf and further in view of Eastwell (Pub. No. US 2012/0296601).
As per claim 2, the combination of Baur and Rothkopf teaches the system as stated above except that the processing specification includes a formation of a weighted arithmetic mean of all read-in sensor signals of the sensor unit, wherein each sensor signal of the read-in sensor signals is assigned a weighting factor dependent on the positional relationship of the installation position of a corresponding acceleration sensor relative to movement axes of the vehicle.
Eastwell, however, teaches monitoring motion of a substantially rigid body relative to a desired first location using a plurality of spatially separated motion sensors (see ¶¶ [0047]-[0051]) and explicitly states that a weighted average of aligned signals from two or more sensors may be used to estimate linear acceleration at a position defined by a corresponding weighted average of the sensor positions, where the sum of the weights equals to one (see ¶ [0061], Eq. (16)). Eastwell explains that a plurality of motion sensors are positioned at respective locations (ri), displaced from a desired location (r) and that a processing module aligns the respective motion vectors and combines the aligned motion vectors to estimate motion at the desired first location (see ¶ [0063]). Eastwell further explicitly provides that the position vector (r) of the first location is weighted average of the position vectors of the respective sensor locations and that the estimate of motion at that first location comprises the corresponding weighted average of the aligned sensor motion vectors (Eastwell claim 15 and ¶ [0061]). Thus, Eastwell establishes a direct relationship between the spatial positions of the sensors and the respective weights used in combining their signals: the weighting factors used to form the weighted sensor-signal combination correspond to the weighting factors defining the desired position from the respective sensor-position vectors. Eastwell therefore teaches that the contribution of each sensor signal to the combined acceleration estimate is selected according to the spatial relationship between the corresponding sensor position and the location for which the acceleration is being determined.
It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the vehicle acceleration-signal processing of Baur as modified by Rothkopf to employ Eastwell’s position-dependent weighted averaging of the acceleration sensor signals because Rothkopf already teaches that the acceleration detected by spatially separated vehicle accelerometers is dependent upon the accelerometers’ respective positions relative to vehicle rotational/movement axes, while Eastwell teaches combining signals from spatially separated acceleration sensors using weighted average corresponding to the spatial positions of those sensors, thereby compensating for differences in measured acceleration resulting from the respective sensor locations and providing a more accurate estimate of vehicle acceleration at a specified position.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Baur in view
of Rothkopf and further in view of Butler et al. (Pub. No. US 2022/0113636) (hereinafter Butler).
As per claim 4, the combination of Baur and Rothkopf teaches the system as stated above except that the mechanical vibrations are determined by taking into account: (i) mechanical resonance characteristics of the sensor unit, and/or (ii) sensitivities of the first and other acceleration sensors at predefined resonant frequencies, and/or (iii) excitation characteristics at the installation position.
Butler, however, teaches an accelerometer having a first mechanical resonance frequency and an electronic system that receives the acceleration signal and electronically dampens the amplitude at that mechanical resonance frequency (see Abstract). More particularly, Butler explicitly teaches a calibration method comprising measuring the first mechanical resonance frequency and its amplitude, determining circuit values to dampen that mechanical resonance frequency to a desired level, and setting those values accordingly (see claim 25 and ¶¶ [0027]-[0030]). Butler further teaches, in a multiple-accelerometer measurement system, tuning the damping circuits to the particular values of the first mechanical resonance frequency and its amplitude (see [0027] and [0079]).
It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to further configure the acceleration-signal processing of Baur, as modified by Rothkopf, to account for mechanical resonance characteristics as taught by Butler because Baur explicitly recognizes that mechanical coupling causes resonance-frequency and amplitude differences in sensor outputs, while Butler teaches measuring those resonance characteristics and determining compensation based on them, thereby reducing resonance-induced distortion and improving the accuracy of the resulting acceleration signal.
Prior art
The prior art made record and not relied upon is considered pertinent to applicant’s
disclosure:
Navin et al. [‘919] discloses systems and methods for calibrating multiple inertial measurement units on a system include calibrating a first of the inertial measurement units relative to the system using a first calibration model and calibrating the remaining inertial measurement unit(s) relative to the first inertial measurement unit using a second calibration model. The calibration of the remaining inertial measurement unit(s) to the first inertial measurement unit can be based on a rigid body model by aligning a rotational velocity of the first inertial measurement unit with a rotational velocity of the remaining inertial measurement unit(s).
Masad et al. [‘655] discloses an inertial measurement system comprising at least one sensor cluster comprising a plurality of inertial sensors for sampling at least one of acceleration and angular velocity of said at least one sensor cluster with respect to each axis in a plurality of axes of a reference frame, and for producing individual outputs associated with said at least one of acceleration and angular velocity, at least three of said inertial sensors said sampling with respect to each same respective said axis; and a processing engine for receiving said individual outputs, combining said individual outputs to yield respective combined outputs, detecting which of said individual outputs diverges from at least one of their inter-comparison, and its respective combined output, according to a decision rule, said processing engine configured to dynamically self-calibrate a parameter that includes individual scale factor of those said inertial sensors whose said individual outputs were detected to diverge.
Contact information
Any inquiry concerning this communication or earlier communications from the
examiner should be directed to MOHAMED CHARIOUI whose telephone number is (571)272-2213. The examiner can normally be reached Monday through Friday, from 9 am to 6 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached on (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Mohamed Charioui
/MOHAMED CHARIOUI/Primary Examiner, Art Unit 2857
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