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 .
Response to Arguments
Applicant’s remarks, see pages 8-12 concerning claims 1, 8 and 15 under 35 USC 102(a)(1) have been considered and deemed persuasive as the amendments overcome the rejection on record.
Applicant’s remarks concerning claims 6, 12, and 20 under 35 USC 103 have been considered and deemed persuasive.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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 1-5, 7-11, 13-19 are rejected under 35 U.S.C. 103 as being unpatentable over Dvorecki et al (US 20240053467 A1), hereinafter Dvorecki in view of Lux et al (US 20140316261 A1), hereinafter Lux in further view of Arage et al (US20160084943), hereinafter Arage.
Regarding claim 1, Dvorecki discloses:
an automotive radar system, comprising (Dvorecki , Abstract, Some demonstrative aspects include radar apparatuses, devices, systems and methods. In one example, an apparatus may include one or more Transmit (Tx) antennas to transmit radar Tx signals, one or more Receive (Rx) antennas to receive radar Rx signals, and a processor to generate radar information based on the radar Rx signals. The apparatus may be implemented, for example, as part of a radar device, for example, as part of a vehicle including the radar device. In other aspects, the apparatus may include any other additional or alternative elements and/or may be implemented as part of any other device):
at least one transmitter and at least one receiver (Dvorecki , Abstract),
wherein the at least one transmitter and the at least one receiver are configured to transmit and receive radar signals (Dvorecki , Abstract),
wherein the at least one transmitter and the at least one receiver are coupled to a vehicle (Dvorecki , Abstract);
and a processor configured to (Dvorecki ,Abstract):
receive, from the at least one receiver, a first received radar signal (Dvorecki , Abstract),
process the first received radar signal to generate a range-Doppler data frame (Dvorecki ,para [0151], In some demonstrative aspects, the result of the second FFT may provide, e.g., when aggregated over the antennas, a range/Doppler (R/D) map 505. The R/D map may have FFT peaks 506, for example, including peaks of FFT output values (in terms of absolute values) for certain range/speed combinations, e.g., for range/Doppler bins. For example, a range/Doppler bin may correspond to a range bin and a Doppler bin. For example, radar processor 503 may consider a peak as potentially corresponding to an object, e.g., of the range and speed corresponding to the peak's range bin and speed bin),
identify a first target cluster at a first range in the range-Doppler data frame (Dvorecki , para [0152], In some demonstrative aspects, the extraction scheme of FIG. 5 may be implemented for an FMCW radar, e.g., FMCW radar 400 (FIG. 4), as described above. In other aspects, the extraction scheme of FIG. 5 may be implemented for any other radar type. In one example, the radar processor 503 may be configured to determine a range/Doppler map 505 from digital reception data values of a PMCW radar, an OFDM radar, or any other radar technologies. For example, in adaptive or cognitive radar, the pulses in a frame, the waveform and/or modulation may be changed over time, e.g., according to the environment) and (para [0187], In some demonstrative aspects, the radar information 813 may include Point Cloud 2 (PC2) information, which may be generated, for example, based on the PC1 information. For example, the PC2 information may include clustering information, tracking information, e.g., tracking of probabilities and/or density functions, bounding box information, classification information, orientation information, and the like),
determine that the first range is less than a threshold distance (para [0065], In some demonstrative aspects, radar device 101 may be configured to map a scene by measuring targets' echoes (reflectivity) and discriminating them, for example, mainly in range, velocity, azimuth and/or elevation, e.g., as described below.
[0066] In some demonstrative aspects, radar device 101 may be configured to detect, and/or sense, one or more objects, which are located in a vicinity, e.g., a far vicinity and/or a near vicinity, of the vehicle 100, and to provide one or more parameters, attributes, and/or information with respect to the objects.
[0067] In some demonstrative aspects, the objects may include other vehicles; pedestrians; traffic signs; traffic lights; roads, road elements, e.g., a pavement-road meeting, an edge line; a hazard, e.g., a tire, a box, a crack in the road surface; and/or the like) Examine interprets the vicinity, near and/or far as a threshold distances,
extract a range spectrum data set from the range-Doppler data frame, wherein the range spectrum data set is associated with the first range (Dvorecki , para [0151]) ,
apply a low-pass filter to the range spectrum data set to extract a first portion of a spectrum of the range spectrum data set to select for near-range targets (Dvorecki , para [0066]) and (para [0138], In some demonstrative aspects, radar frontend 401 may include a filter, e.g., a Low Pass Filter (LPF) 410, which may be configured to filter the mixed signal from the mixer 409 to provide a filtered signal. For example, radar frontend 401 may include an ADC 411 to convert the filtered signal into digital reception data values, which may be provided to radar processor 402. In another example, the filter 410 may be a digital filter, and the ADC 411 may be arranged between the mixer 409 and the filter 410 ) and (further reference paras [0139-0142])
and transmit the first range to a vehicle controller (Dvorecki , Abstract).
Lux discloses:
compute an inverse fast Fourier transform (IFFT) of the first portion of the spectrum to generate a time-domain set of signal magnitudes (Lux, (para [0017], In still yet another embodiment, transforming the processed return signal from a frequency to a time domain data set includes utilizing an Inverse Fast Fourier Transform) and (further reference para [0102]),
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Dvorecki with Lux to incorporate the features of: compute an inverse fast Fourier transform (IFFT) of the first portion of the spectrum to generate a time-domain set of signal magnitudes. Both arts disclose radar system that detect targets within a predefine near-range that include inverse Fast Fourier Transform processing. Dvorecki discloses a system for automotive radar that may detection objects such as pedestrians within a near-vicinity, and Lux discloses the detection of living people wherein there is the ability to resolve within 20 meters of a search range to 2 meters of a search range (near-range). The modification would render the predictable results of enhanced time-domain analysis, improved target prioritization and situational awareness; and improved signal isolation. However, the combination of Dvorecki and Lux fails to disclose: apply a super-resolution spectral estimation to the time-domain set of signal magnitudes to identify a first range of a first target associated with the first target cluster using a distance resolution that is smaller than a distance resolution used to generate the range-Doppler data frame
Arage discloses:
apply a super-resolution spectral estimation to the time-domain set of signal magnitudes to identify a first range of a first target associated with the first target cluster using a distance resolution that is smaller than a distance resolution used to generate the range-Doppler data frame Arage et al US20160084943 para [0027], Applicant's prior system described in U.S. patent application Ser. No. 14/277,894 filed 15 May 2014 applies a composite detection strategy based on NCI spectrum together with a single receive channel spectrum analysis using ‘or logic’ in order to improve automotive radar range, range rate, and angle measurement resolution, and enhance system performance for near targets discrimination, target imaging, and lateral range rate estimation. A time delay between transmitted and received signals as well as the frequency shift due to Doppler effect is used to compute radial distance (e.g. r1 and/or r2 in FIG. 1) and relative velocity of a detected object, e.g. the first object 24A or the second object 24B, respectively. The received signal-phase differences of the detected signals 30 are used to estimate the angle, i.e. Direction-Of-Arrival (DOA) of a detected object by applying various angle finding techniques or algorithms such as Monopulse, digital beam forming, or super-resolution) and (further reference para [0053])
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify the combination of Dvorecki and Lux with Arage to incorporate the features of: apply a super-resolution spectral estimation to the time-domain set of signal magnitudes to identify a first range of a first target associated with the first target cluster using a distance resolution that is smaller than a distance resolution used to generate the range-Doppler data frame. The three arts each disclose radar system of objects within a near-range. The modification would render the predictable results of improved target separation, improve object classification, and improved tracking accuracy.
Regarding claim 2, Dvorecki discloses:
the automotive radar system of claim 1 (Dvorecki , Abstract),
wherein the processor is configured to, before receiving the first received signal (Dvorecki , Abstract):
determine, based on a second received radar signal, that an object is not detected by the automotive radar system (Dvorecki , paras [0065-0067]);
and store, into a memory accessible to the processor, a signal profile based upon the second received radar signal (Dvorecki , para [0049], The term “logic” may refer, for example, to computing logic embedded in circuitry of a computing apparatus and/or computing logic stored in a memory of a computing apparatus. For example, the logic may be accessible by a processor of the computing apparatus to execute the computing logic to perform computing functions and/or operations. In one example, logic may be embedded in various types of memory and/or firmware, e.g., silicon blocks of various chips and/or processors. Logic may be included in, and/or implemented as part of, various circuitry, e.g., radio circuitry, receiver circuitry, control circuitry, transmitter circuitry, transceiver circuitry, processor circuitry, and/or the like. In one example, logic may be embedded in volatile memory and/or non-volatile memory, including random access memory, read only memory, programmable memory, magnetic memory, flash memory, persistent memory, and/or the like. Logic may be executed by one or more processors using memory, e.g., registers, buffers, stacks, and the like, coupled to the one or more processors, e.g., as necessary to execute the logic).
Regarding claim 3, Dvorecki discloses:
the automotive radar system of claim 2 (Dvorecki , Abstract),
wherein the processor is further configured to subtract at least a portion of the signal profile from the range-Doppler data frame to remove at least one of bumper reflection signal and radar system component spill-over interference from the range-Doppler data frame (Dvorecki , para [0152]) and (para [0450], In some demonstrative aspects, a first installation scheme may include adding a coating on parts of vehicle 1700, e.g., a bumper or other element. For example, the coating may be configured to allow isolation of the synchronization channel, for example, from outside world interferences, multipath, and/or from self-interferences, e.g., which may be caused by radar front-ends 1720 and/or 1740).
Regarding claim 4, Dvorecki discloses:
the automotive radar system of claim 3 (Dvorecki , Abstract),
wherein the signal profile is a 0-Doppler range profile (Dvorecki , para [0044], The phrase “vehicle operation data” may be understood to describe any type of feature related to the operation of a vehicle. By way of example, “vehicle operation data” may describe the status of the vehicle, such as, the type of tires of the vehicle, the type of vehicle, and/or the age of the manufacturing of the vehicle. More generally, “vehicle operation data” may describe or include static features or static vehicle operation data (illustratively, features or data not changing over time). As another example, additionally or alternatively, “vehicle operation data” may describe or include features changing during the operation of the vehicle, for example, environmental conditions, such as weather conditions or road conditions during the operation of the vehicle, fuel levels, fluid levels, operational parameters of the driving source of the vehicle, or the like. More generally, “vehicle operation data” may describe or include varying features or varying vehicle operation data (illustratively, time varying features or data) and (paras [0065-0067]).
Regarding claim 5, Dvorecki discloses:
the automotive radar system of claim 1 (Dvorecki , Abstract),
wherein the received radar signal is a digital signal and processing the received radar signal to generate the range-Doppler data frame includes performing a first fast Fourier transform (FFT) on the digital signal in a first direction corresponding to range to generate a range data frame and performing a second FFT on the range data frame in a second direction corresponding to relative velocity to generate the range-Doppler data frame (Dvorecki , para [0148], In some demonstrative aspects, radar processor 503 may be configured to process a plurality of samples, e.g., L samples collected for each chirp and for each antenna, by a first FFT. The first FFT may be performed, for example, for each chirp and each antenna, such that a result of the processing of the data cube 504 by the first FFT may again have three dimensions, and may have the size of the data cube 504 while including values for L range bins, e.g., instead of the values for the L sampling times. [0149] In some demonstrative aspects, radar processor 503 may be configured to process the result of the processing of the data cube 504 by the first FFT, for example, by processing the result according to a second FFT along the chirps, e.g., for each antenna and for each range bin) and (para [0151]).
Regarding claim 6, Dvorekci discloses:
the automotive radar system of claim 1 (Dvorecki, Abstract),
Lux discloses:
wherein the threshold distance is equal to or less than five meters (Lux, para [0068], In many embodiments, rapidly switching among beams and frequencies allows multiple measurements to be made during a short enough time such that the heartbeat and/or respiration signals are essentially unchanging. When making multiple measurements in a short period of time, data should be collected at a rate sufficient to perform processing. In various embodiments, FINDER systems collect samples for each search area at a sampling rate between 200-1000 Hz. In several embodiments, to resolve a 20 meter search range into range zones of approximately 2 meters each, FINDER typically utilizes at least 10 frequencies. With medium gain antennas having a beam width on the order of 70 degrees, 360 degrees can be covered with 8 beams, arranged in the cardinal directions)
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Dvorecki with Lux to incorporate the features of: wherein the threshold distance is equal to or less than five meters. Both arts disclose radar system that detect targets within a predefine near-range that include inverse Fast Fourier Transform processing. Dvoreck discloses a system for automotive radar that may detection objects such as pedestrians within a near-vicinity, and Lux discloses the detection of living people wherein there is the ability to resolve within 20 meters of a search range to 2 meters of a search range (near-rang. The modification would render the predictable results of improved near-field object resolution, improved low speed safety functionalities, and improved occupant and road detections.
Regarding claim 7, Dvorecki discloses:
the automotive radar system of claim 1 (Dvorecki , Abstract),
wherein the vehicle controller is configured to modify an operation of a driver-assistance system based upon the first range (Dvorecki , para [0087], In some demonstrative aspects, vehicle controller 108 may configured to control radar device 101, and/or to process one or parameters, attributes and/or information from radar device 101.
[0088] In some demonstrative aspects, vehicle controller 108 may be configured, for example, to control the vehicular systems of the vehicle 100, for example, based on radar information from radar device 101 and/or one or more other sensors of the vehicle 100, e.g., Light Detection and Ranging (LIDAR) sensors, camera sensors, and/or the like.
[0089] In one example, vehicle controller 108 may control the steering system, the braking system, and/or any other vehicular systems of vehicle 100, for example, based on the information from radar device 101, e.g., based on one or more objects detected by radar device 101).
Regarding claim 8, Dvorecki discloses:
a signal processing system, comprising (Dvorecki , Abstract):
a radar system (Dvorecki , Abstract);
and a processor coupled to the radar system, the processor being configured to (Dvorecki , Abstract):
receive a first subframe of a first range-Doppler data frame (Dvorecki , para [0151]),
wherein the first range-Doppler frame is generated based upon a radar signal received from the radar system (Dvorecki , para [0151]),
identify a first target cluster at a first range in the first subframe (Dvorecki , paras [0151] and [0187]),
determine that the first range is less than a threshold distance (Dvorecki , paras [0065-0066]),
extract a first range spectrum data set from the first subframe (Dvorecki , para [0065]) and (para [0142], Reference is made to FIG. 5, which schematically illustrates an extraction scheme, which may be implemented to extract range and speed (Doppler) estimations from digital reception radar data values, in accordance with some demonstrative aspects. For example, radar processor 104 (FIG. 1), radar processor 210 (FIG. 2), radar processor 309 (FIG. 3), and/or radar processor 402 (FIG. 4), may be configured to extract range and/or speed (Doppler) estimations from digital reception radar data values according to one or more aspects of the extraction scheme of FIG. 5),
wherein the first range spectrum data set is associated with the first range (Dvorecki , para [0142]),
apply the low-pass filter to the second range spectrum data set to extract a second portion of a second spectrum of the second range spectrum data set to select for near-range targets (Dvorecki , paras [0066]) and (further reference paras [0138-1042]);
and transmitting at least one of the first range of the first target and the second range of the second target to a vehicle controller (Dvorecki , paras [0087-0089]).
Lux discloses:
compute the inverse fast Fourier transform (IFFT) of the second portion of the spectrum extracted from the second range spectrum data set to generate a second time-domain set of signal magnitudes (Lux, paras [0023], In yet another embodiment again, the sequence of samples taken from the time domain data set includes phase and quadrature data samples) and (further reference pas [0017] and [0102]) ,
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify Dvorecki with Lux to incorporate the features of: compute the inverse fast Fourier transform (IFFT) of the second portion of the spectrum extracted from the second range spectrum data set to generate a second time-domain set of signal magnitudes. Both arts disclose radar system that detect targets within a predefine near-range that include inverse Fast Fourier Transform processing. Dvoreck discloses a system for automotive radar that may detection objects such as pedestrians within a near-vicinity, and Lux discloses the detection of living people wherein there is the ability to resolve within 20 meters of a search range to 2 meters of a search range (near-range). The modification would render the predictable results of enhanced time-domain analysis, improved target prioritization and situational awareness; and improved signal isolation. However, the combination of Dvorecki and Lux fails to disclose: apply the super-resolution spectral estimation to the second time-domain set of signal magnitudes to identify a second range of a second target associated with the second target cluster using the distance resolution that is smaller than the distance resolution used to generate the first range-Doppler data frame.
Arage discloses:
apply the super-resolution spectral estimation to the second time-domain set of signal magnitudes to identify a second range of a second target associated with the second target cluster using the distance resolution that is smaller than the distance resolution used to generate the first range-Doppler data frame ( Arage paras [0027] and [0053]).
It would have been obvious to someone in the art prior to the effective filing date of the claimed invention to modify the combination of Dvorecki and Lux with Arage to incorporate the features of: apply the super-resolution spectral estimation to the second time-domain set of signal magnitudes to identify a second range of a second target associated with the second target cluster using the distance resolution that is smaller than the distance resolution used to generate the first range-Doppler data frame .The three arts each disclose radar system of objects within a near-range. The modification would render the predictable results of improved target separation, improve object classification, and improved tracking accuracy.
Claim 9 is rejected under the same analysis as claim 2
Claim 10 is rejected under the same analysis as claim 3
Claim 11 is rejected under the same analysis as claim 4.
Claim 12 is rejected under the same analysis as claim 6.
Regarding claim 13, Dvorecki discloses:
the signal processing system of claim 8 (Dvorecki , Abstract),
wherein the vehicle controller is configured to modify an operation of a driver-assistance system based upon the at least one of the first range of the first target and the second range of the second target (Dvorecki , paras [0087-0089]).
Regarding claim 14, Dvorecki discloses:
the signal processing system of claim 8 (Dvorecki , Abstract),
wherein the processor is further configured to transmit at least one of the first range of the first target and the second range of the second target to a vehicle controller by (Dvorecki , para [0256]):
determining that the first range of the first target is less than the second range of the second target (Dvorecki , paras [0065-0066]);
and transmitting the first range of the first target to the vehicle controller (Dvorecki , paras [0087-0089]).
Claim 15 is rejected under the same analysis as claim 1.
Claim 16 is rejected under the same analysis as claim 2.
Claim 17 is rejected under the same analysis as claim 3.
Regarding claim 18, Dvorecki discloses:
the method of claim 16, wherein storing the signal profile further comprises storing a 0-Doppler range profile into the memory, wherein the 0-Doppler range profile is derived from the received radar signal (Dvorecki, paras [0065-0067]).
Claim 19 is rejected under the same analysis as claim 5.
Claim 20 is rejected under the same analysis as claim 6.
References Cited But Not Relied Upon
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure as thus:
Davis et al US 20180252809 A1 discloses a software defined automotive radar with short-range radar (SRR) of distances up to 30 meters, Inverse Fast Fourier Transform (IFFT), and removal of bumper interference, wherein range resolution is between 0-30 meters (para [0029])
Lee US 20220224380 A1 discloses a multi-stream MIMO/Beamforming Radar system wherein Inverse Fast Fourier Transform (IFFT) is applied, antenna installed on bumper, and range-Doppler maps and processing
Wu et al US 11662427 B2 discloses a method and system for frequency offset modulating range division MIMO automotive radar wherein signal feed into a low pass filter (LPF), signals processed in slow-time Doppler FFT
Wu et al US 20220094397 A1 discloses an automotive MIMO radar system using efficient difference co-array processor, short-range (SRR) doppler applications, range-Doppler maps, and the application of Inverse Fast Fourier Transform
Amihood et al US-20230161027-A1 discloses near-range detection for smart device-based radar system wherein processing of near-range portions of the range-Doppler maps using near-range detection modules
Rodenbeck US-20220365206-A1 discloses automotive radar the performance of inverse FFT, range resolution, and comprises a low-pass filter, and vibratory information observed within range-Doppler space
Conclusion
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/KIMBERLY JENKINS/Examiner, Art Unit 3648
/VLADIMIR MAGLOIRE/Supervisory Patent Examiner, Art Unit 3648
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