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 Claims
Amendments to claims 1 – 2 and 14 have been entered.
Claims 1 – 20 are pending.
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.
Regrading the Graham factors, the ordinarily skilled understands the signal-to-noise (SNR) ratio wherein SNR
=
P
G
1
4
π
R
2
σ
1
4
π
R
2
A
e
1
N
wherein P is power, G is antenna Gain, R is range,
σ
is radar cross section,
A
e
is effective area of antenna, and N is noise. Gain is a function of angle and depends on a particular antenna radiation pattern. Gain at the line-of-sight (LOS) has nominal or maximal gain meaning that the angle directly at LOS is zero.
Claims 1, 3, 5, 9 – 11, 13 – 15 and 17 are rejected under 35 U.S.C. 103 as being obvious over Somanath (US 20220196830 A1) in view of Achour (US 20180351250 A1) and Mandelli (US 20230269676 A1).
As to claims 1, 10 – 11 and 13 – 15, Somanath discloses an automotive radar system (Fig. 4), comprising:
at least one transmitter unit and at least one receiver unit, wherein the at least one transmitter unit and the at least one receiver unit are configured to transmit and receive radar signals, wherein the at least one transmitter unit and the at least one receiver unit are co-located with a vehicle (Para. 17 wherein “reflections” indicate transceiving.); and a radar processor (Fig. 4), configured to:
determine an occupancy map, wherein the occupancy map identifies a location of an object with respect to the automotive radar system (Para. 31 “the updated radar-field/object tracking 302 may comprise accumulating radar reflections in a radar occupancy grid using dynamic accumulation times.”),
determine, using the occupancy map, a beamforming weight vector w, and transmit, using the at least one transmitter unit, the radar signal using the beamforming weight vector w (Para. 52 “using directed radar beams towards those radar-localization objects 112 or an accumulation of detections in a radar occupancy grid.”).
Note that directing or focusing radar beams imply beamforming or beam steering, which the Examiner believes inherently involves the use of weighting as evidenced by Kanemoto (US 20230124953 A1) stating that “the direction, width, and power of the beam may be adjusted by weighting based on the information on the beam control (Para. 55).”
Somanath does not teach “a probability value associated with the location of the object in the occupancy map” and “wherein the beamforming weight vector w is configured to enable a determination of a gain of the radar signal and the gain of the radar signal is at least partially determined by the probability value associated with the location.”
In the same field of endeavor, Achour teaches “the system determines a high probability that a pedestrian is in the path of a vehicle and controls the antenna array 110 to focus on that location as the ramifications of a mistake is greater than for another vehicle (Para. 45).”
In view of the teachings of Achour, it would have been obvious to a person having ordinary skill in the art before filing to apply weights in order to shape, focus and/or steer the beam to focus on higher probable threat locations thereby improving situational awareness and safety because pedestrians are known to have a lower radar cross section than other vehicles and society considers pedestrians to be of more value than damage to vehicles.
The issue is the interpretation of “the gain … determined by probability value associated with the location.” Claim 1. Looking at Para. 45, the cited portion of Achour, it appears that gain is increased due to the location of a pedestrian. However, Applicant may want to have a more strict interpretation wherein gain is a function of probability.
In the same field of endeavor, Mandelli teaches “The maximum distance, at which a minimum signal-to-noise ratio (SNR) may be achieved, can be determined based on the following: the determined transmit power, beamforming gains, path loss, and reflection coefficient for a given target object. Below the minimum SNR, the confidence of sensing measures may not be sufficient to provide meaningful information. Thus, if the transmit power is at a certain level in a certain direction (angle), one can estimate the most distant object. Doing so over all angles may create a coverage/sensing map, which can be “sensed” (para. 75).”
In view of the teachings of Mandelli, it is obvious to the ordinarily skilled before filing to increase gain and/or power in order to improve detection probability (confidence) thereby improving accuracy and safety.
As to claim 3, Somanath in view of Achour and Mandelli teaches the automotive radar system of claim 1, wherein the beamforming weight vector w is configured to enable a determination of a beam of the radar signal has an effective range that is less than or equal to a distance between the automotive radar system and the object (Somanath Para. 52).
As to claims 5 and 17, Somanath in view of Achour and Mandelli teaches the automotive radar system of claims 1 and 14, wherein the radar processor is configured to determine the occupancy map by: receiving, using the at least one receiver unit, a received radar signal; processing the received radar signal to identify a target object and a range to the target object; and determine the occupancy map using the range to the target object (Somanath Para. 17).
As to claim 9, Somanath in view of Achour and Mandelli teaches the automotive radar system of claim 1, wherein the object includes at least one of a static object and a dynamic object, wherein the static object may be an object selected from a guardrail, a building, a street obstruction, and a vegetation (Somanath background section Para. 2. It would be obvious to use well-known static objects to ensure that an object is correctly selected as stationary thereby improving accuracy), and the dynamic object may be an object selected from a pedestrian, a cyclist, an automobile, and another type of moving vehicle (Somanath Para. 46 “predicted motion of the radar occlusion 204” shown in Fig. 2).
As to claim 11, Somanath in view of Achour and Mandelli teaches the system of claim 10, wherein the beamforming weight vector is configured to enable a determination of an effective range of a beam of the radar signal that is less than or equal to a value determined by the location in the occupancy map (Somanath Para. 52. The focusing of radar beams to an object would imply equal to the distance of said object. See also Somanath Para. 64 wherein the radar localization takes into account a threshold to determine accuracy.).
As to claim 13, Somanath in view of Achour and Mandelli teaches the e system of claim 10, wherein the controller is configured to determine the occupancy map by: processing a received radar signal to identify a target object and a range to the target object; and determine the occupancy map using the range of the target object (Somanath Para. 17).
Claims 6 – 8 and 18 – 20 are rejected under 35 U.S.C. 103 as being obvious over Somanath in view of Achour and Mandelli and in further view of Levy-Israel (US 20190339376 A1).
As to claims 6 and 18, Somanath in view of Achour and Mandelli does not teach the automotive radar system of claims 1 and 14, wherein a field of vision of the automotive radar system is divided into a plurality of angle bins and the occupancy map defines distance values in association with angle bins of the plurality of angle bins.
Levy-Israel teaches “The confirmed detections 632 are provided to the direction of arrival module 610 which determines parameters 634 such as direction of arrival, thereby obtain range, Doppler, azimuth and elevation for the confirmed detection 632 (Para. 39).”
In view of the teachings of Levy-Israel, it would have been obvious to one having ordinary skill in the art to associate together range and angle in order to improve spatial resolution thereby improving image quality and accuracy. This would also allow for safety determination regarding height when passing under an object while traveling.
As to claims 7 and 19, Somanath in view of Achour and Mandelli does not teach the automotive radar system of claims 6 and 18, wherein the radar processor is configured to determine the beamforming weight vector w by determining a maximum value of the weight vector w that satisfies a requirement that an effective range of beams of the radar signal transmitted into each angle bin do not exceed the distance values associated with the same angle bin in the occupancy map.
Levy-Israel teaches “The detector 608 compares values in the Energy Map 626 to the energy threshold in order to identify a positive energy detection. Similarly, the detector 608 compares probability values in the probability map 628 to the probability threshold to determine positive phase detections. The detector 608 provides uses a weighted sum of the positive energy detection and the positive phase detection in order to confirm the detections 632. The confirmed detections 632 are provided to the direction of arrival module 610 which determines parameters 634 such as direction of arrival, thereby obtain range, Doppler, azimuth and elevation for the confirmed detection 632 (Para. 39).”
In view of the teachings of Levy-Israel, it would have been obvious to one having ordinary skill in the art to associate together range and angle within a maximum threshold value in order to reduce ambiguities due to aliasing thereby improving spatial resolution resulting in improved image quality and accuracy.
As to claim 8, Somanath in view of Achour and Mandelli does not teach the automotive radar system of claim 1, wherein the occupancy map associates a probability value with the location of the object (Somanath Para. 63 “signal-to-ratio”).
One of ordinary skill knows that SNR is associated with a SNR threshold that corresponds to probability of detection and false alarm rate.
Levy-Israel teaches the “The beamforming energy map generator 604 receives a steering matrix 624 and produces an Energy Map 626 for the Range-Doppler signal by associating an intensity of a signal with a range and velocity. The differential phase map generator 606 produces a differential phase probability map 628 (also referred to herein as a “probability map”) using the object detection probability calculations discussed with respect to Eqs. (2)-(9) (Para. 38).”
In view of the teachings of Levy-Israel, it would have been obvious to a person having ordinary skill before filing to apply weights based on probably of true desired object detection corresponding to SNR which depends on gain (intensity) in order to properly reduce false detections thereby improving overall accuracy.
As to claim 20, Somanath in view of Achour and Mandelli does not teach the method of claim 14, wherein transmitting the radar signal further comprising setting a configuration of a power amplifier in the at least one transmitter unit using the beamforming weight vector.
Although, Somanath and Achour are not directed to the design of radar hardware, one of ordinary skill would expect that the radar has a power amplifier as it is common, routine and standard.
Looking at the SNR equation shown above regarding the Graham factors, one of ordinary skill would understand the need, e.g.,
1
R
4
, to amplify the signal in order to improve SNR thereby improving accuracy. Having a power amplifier on the transmit side and low noise amplifier on the receive side is conventionally standard. In fact, many stages of such are typically used in order to preserve linearity. Levy-Israel shows power amplifiers 210 on the transmit side shown in Fig. 2.
Claims 4 and 16 are rejected under 35 U.S.C. 103 as being obvious over Somanath in view of Achour and Mandelli and in further view of McArthur (US 20200019160 A1).
As to claims 4 and 16, Somanath in view of Achour and Mandelli teaches the automotive radar system of claims 1 and 14, wherein the radar processor is configured to determine the occupancy map by: determining a location of the automotive radar system (Somanath Para. 20 “radar-localization”);
Somanath in view of Achour and Mandelli does not teach accessing a database storing locations of a plurality of objects to identify the object, wherein the location of the object is within a threshold distance of the location of the automotive radar system.
In the same field of endeavor, McArthur teaches “system 310 may detect that the vehicle is currently within the threshold distance based on the transmitted location data, and responsively instruct the vehicle to scan the target (and/or store sensor data associated with a scan of the target) (Para. 89).” McArthur further teaches “, a vehicle (e.g., vehicle 200) may store (e.g., in data storage 214) an indication of predetermined scanning targets (e.g., similar to target data 320) that are at known or predetermined locations in an environment. For instance, a given target (e.g., building, wall, tree, stationary object) may have been previously detected using one or more sensors of the vehicle or other vehicles. Thus, a geographic location of the given target could be stored in the data storage (e.g., 214) of the vehicle. Alternatively, for instance, a list of calibration targets can be provided to the vehicle by a remote server (e.g., system 310), or input to the vehicle by a user (e.g., via touch screen 254, microphone 256, etc.) (Para. 96).”
In view of the teachings of McArthur, it would have been obvious to a person having ordinary skill in the art to store localized objects in order to require less radar processing when traveling on a route that has already been traveled for thereby improving efficiency wherein only the localized objects within a maximum unambiguous distance stored to reduce the risk of false targets, e.g., ghosts, due to ambiguities thereby improving accuracy. Moreover, it would have been obvious to identify and store the identification and location of objects to better know which object to use to calibrate and/or localize from in order to improve accuracy without having to repeat more processing steps than needed therefore improving accuracy and efficiency.
Claim 12 is rejected under 35 U.S.C. 103 as being obvious over Somanath in view of Achour, Mandelli and Levy-Israel and in further view of McArthur.
As to claim 12, Somanath in view of Achour, Mandelli and Levy-Israel teaches the system of claim 10, wherein the controller is configured to determine the occupancy map by: determining a location of a radar system (Somanath Para 20 “radar-localization”); and
Somanath in view of Achour, Mandelli and Levy-Israel does not teach the feature accessing a database storing locations of a plurality of objects to identify the object, wherein the location of the object is within a threshold distance of the location of the radar system.
In the same field of endeavor, McArthur teaches “system 310 may detect that the vehicle is currently within the threshold distance based on the transmitted location data, and responsively instruct the vehicle to scan the target (and/or store sensor data associated with a scan of the target) (Para. 89).” McArthur further teaches “a vehicle (e.g., vehicle 200) may store (e.g., in data storage 214) an indication of predetermined scanning targets (e.g., similar to target data 320) that are at known or predetermined locations in an environment. For instance, a given target (e.g., building, wall, tree, stationary object) may have been previously detected using one or more sensors of the vehicle or other vehicles. Thus, a geographic location of the given target could be stored in the data storage (e.g., 214) of the vehicle. Alternatively, for instance, a list of calibration targets can be provided to the vehicle by a remote server (e.g., system 310), or input to the vehicle by a user (e.g., via touch screen 254, microphone 256, etc.) (Para. 96).”
In view of the teachings of McArthur, it would have been obvious to a person having ordinary skill in the art to store localized objects in order to require less radar processing when traveling on a route that has already been traveled for thereby improving efficiency wherein only the localized objects within a maximum unambiguous distance stored to reduce the risk of false targets, e.g., ghosts, due to ambiguities thereby improving accuracy. Moreover, it would have been obvious to identify and store the identification and location of objects to better know which object to use to calibrate and/or localize from in order to improve accuracy without having to repeat more processing steps than needed therefore improving accuracy and efficiency.
Allowable Subject Matter
Claim 2 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The prior art does not teach all the features of claim 2.
Conclusion
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/MICHAEL W JUSTICE/Examiner, Art Unit 3648