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
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. EP23215087, filed on 12/07/2023.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 12/06/2024 and 12/23/2024 are in compliance with the provisions of 35 CFR 1.97. Accordingly, the IDS have been considered by the examiner.
Claim Objections
Claim 1 recites: “fuse the data from the active radar component and the data from the passive radar component, and,” - the trailing comma after “and,” appears to be a typographical error.
Claim 7 recites “the active radar component is configured to perform a estimation of the direction of arrival.” The article “a” should read “the” before “estimation.”
Claim 7 recites “determined in at least one of the following ways… of arrival, and an auxiliary sensor”. Under BRI, the claim requires both: (1) the active radar component is configured to perform the DOA estimation, and (2) an auxiliary sensor or the sensor fusion device is configured to estimate the DOA. The “or” within alternative (2) is disjunctive - the prior art need teach only one of “an auxiliary sensor” or “the sensor fusion device” for that branch. The specification at [0031] uses “In addition, or alternatively” language, which may suggest the applicant intended the disjunctive reading. However, under SuperGuide Corp. v. DirecTV Enters., Inc., 358 F.3d 870, 885–86 (Fed. Cir. 2004), the claim as written with “and” requires both ways. The Examiner invites Applicant to amend to “or” if the disjunctive was intended.
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 9-11 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.
Claims 9 and 11 each recite, as a final step, “detecting the object based on the direction of arrival and on the ambient radio waves reflected off the object.” This limitation is indefinite for the following reasons.
The claims recite four steps: (1) detecting an electromagnetic interference signal emitted by the object; (2) providing an estimation of a direction of arrival of the electromagnetic interference signal; (3) receiving ambient radio waves reflected off the object; and (4) detecting the object based on the direction of arrival and on the ambient radio waves reflected off the object. A direction of arrival is a one-dimensional angular measurement providing a bearing to the object but no range, velocity, or position information. The ambient radio waves are reflected electromagnetic energy. The claim does not recite what operation is performed on the direction of arrival and the ambient radio waves to accomplish the detection. The direction of arrival (an angular bearing) and the ambient radio waves (reflected electromagnetic energy) are different types of data that cannot be combined without some processing step, such as fusing, correlating, triangulating, or otherwise jointly processing the data, to yield an object detection. The claim omits any such step. It is therefore unclear what “detecting the object based on the direction of arrival and on the ambient radio waves” requires a practitioner to do.
By contrast, independent Claim 1 explicitly recites a sensor fusion device that is configured to “receive data from the active radar component and data from the passive radar component, fuse the data from the active radar component and the data from the passive radar component, and, detect, based on the fused data … the object.” Claim 1 specifies the intermediate data fusion operation that bridges the gap between the raw inputs and the object detection output. The specification similarly describes this step at [0032]: “detecting the object based on the direction of arrival of the interference signal and on the ambient radio waves reflected off the object, by fusing respective data” (emphasis added). Claims 9 and 11 omit this fusion step, leaving it unclear how the direction of arrival and the ambient radio waves are used together to accomplish the detection.
Because the metes and bounds of the final “detecting” step cannot be ascertained, a person of ordinary skill in the art cannot determine what acts are required to perform the claimed detection when given only an angular bearing and raw reflected ambient radio waves without any recited processing or fusion operation. See MPEP 2173.05(g).
Claim 10 depends from Claim 9 and is rejected under 35 U.S.C. 112(b) by virtue of its dependency on a rejected base claim.
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 1-7 and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Beasley, P. J., & Ritchie, M. A. (2023). Multi-Band Hybrid Active-Passive Radar Sensor Fusion. 2023 IEEE Radar Conference (RadarConf23), 1-6. https://doi.org/10.1109/RadarConf2351548.2023.10149774) in view of Kanter (US 6,133,866). Background evidence of the art admitted by Applicant: Brenner et al., “Signals and data fusion in a Deployable Multiband Passive-Active Radar (DMPAR),” 2012 (hereinafter “Brenner”). The Brenner is used only for background evidence and not to teach over the claims.
Regarding Claim 1, Beasley et al. in view of Kanter (‘866) teaches:
Beasley et al. teaches: A sensor network configured to detect an object, the sensor network comprising: (Abstract: “An experimental hybrid radar setup is presented where a low-cost Software Defined Radio (SDR) based radar system is used for hybrid sensing of targets using active and Passive Bistatic Radar (PBR)”; Section II: describing the bladeRAD hybrid radar system used for simultaneous active and passive target sensing). The hybrid radar system comprising both active and passive components and a fusion mechanism constitutes a sensor network configured to detect an object.
Beasley et al. teaches: an active radar component configured to detect the object by transmitting a radio signal and receiving an echo of the radio signal (Section II.A: “the active radar component was operated in an S-Band Frequency-Modulated-Continuous-Wave (FMCW) mode, with identical 18 dBi parabolic dish antennae used for the transmit and receive channels”; Table I: listing the active FMCW radar parameters including central RF of 2.44 GHz, sample rate of 60 MSPS, and waveform LFM Up-Chirp; Section III.A: describing active radar signal processing in which the transmitted chirp is mixed with the received signal to extract range and Doppler data from target echoes).
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Beasley et al. teaches: a passive radar component configured to receive ambient radio waves from stationary emitters and to detect the object based on a reflection of the ambient radio waves off the object (Section II.A: “For the PBR component, a non-cooperative DVB-T tower was used as an IoO”; Table I: listing the passive DVB-T radar parameters including central RF of 0.69 GHz and Tx Power of 170 kW from the broadcast tower; Section II.B: “The PBR IoO was located in Sandy Heath, 8.696 km to the southeast, with an estimated antenna height of 292 meters above sea level”; Section III.B: “In conventional passive radar signal processing, the surveillance channel is cross-correlated with Doppler-shifted replicas of the reference channel”; Fig. 2 showing separate passive surveillance and passive reference antennas for receiving DVB-T signals). The DVB-T broadcast tower constitutes a stationary emitter, and the PBR component detects the object based on reflections of the DVB-T broadcast signals off the target.
Beasley et al. teaches: a sensor fusion device (Section III.C: “decentralised information fusion was used to combine the active and PBR radar detections”; Eq. (1):
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; Fig. 4 showing the hybrid signal processing combining active and PBR CFAR detector outputs). The decentralized fusion processing constitutes a sensor fusion device that combines data from the active and passive components.
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Beasley et al. does not explicitly teach, but Kanter (‘866) teaches: wherein the active radar component is configured to detect an electromagnetic interference signal emitted by the object and to provide an estimation of a direction of arrival of the electromagnetic interference signal (Abstract: “A method of operating a radar to track echo signals from a target in the presence of a barrage jammer is shown to comprise the steps of actively determining the apparent direction of the combination of echo signals from a target and jamming signals, passively determining the actual direction and average power of a barrage jammer”; Col. 3, lines 10-25: “When the radar transmitter 24 is turned off, the radar system 10 may be operated in a passive mode to determine not only the angular location relative to the antenna boresight θJ, but also the average power, PJ, of the stand-off barrage jammer 14”; Col. 3, lines 10-25: “Before the stand-off barrage jammer 14 masks the target aircraft 12 and the transmitter 24 is turned off, yet while the radar system 10 is experiencing the so-called “pulling effect” of the barrage jammer 14, the radar system 10 measures the average angle,
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, of the target aircraft 12 plus the barrage jammer 14, as well as the average power, PT, from the two sources”; Col. 3, lines 22-25: “From the foregoing measurements, the digital computer 36 derives the angular location of the target, θT”). Kanter’s monopulse radar system detects the barrage jammer signal (electromagnetic interference signal emitted by/associated with the jammer aircraft), passively determines the angular location (direction of arrival) of the jammer, and uses this information to derive the target angular position.
Beasley et al. teaches: wherein the sensor fusion device is configured to receive data from the active radar component and data from the passive radar component (Section III.C: “2D Cell-Averaging (CA) Constant-False-Alarm-Rate (CFAR) detectors were used to determine detections in the individual active and PBR range-Doppler surfaces”; Fig. 4 showing both the active radar processing flow and the passive radar processing flow feeding into the hybrid CFAR detector stage). The fusion mechanism receives detection data from both the active and PBR sensors.
Beasley et al. teaches: fuse the data from the active radar component and the data from the passive radar component, and, detect, based on the fused data from the active radar component and the data from the passive radar component, the object (Section III.C: “The binary output of the active and PBR CFAR detectors were then combined using a 1-of-k (OR) decision rule, such that a hybrid detection, Hdet, was made when either the active radar Adet or PBR Pdet made a detection”; Section V, IV-B: “even at considerably lower power levels, the active sensor still improved the empirical hybrid Pd”; Tables II and III showing that the hybrid radar detection probability exceeds that of the individual sensors). The OR-rule fusion combines detections from both sensors and produces a hybrid detection of the object.
It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to modify the active radar component in the hybrid system of Beasley to include the capability to detect electromagnetic interference signals emitted by a target and estimate their direction of arrival, as taught by Kanter. One would have been motivated to do so because Beasley expressly identifies resilience to electronic countermeasures as a key benefit of hybrid active-passive radar architectures (Section I, Item 4: “Resilience to Electronic Counter Measures: The passive element of the hybrid radar is inherently more resilient to jamming, than active radar, due to the jamming entity not being aware of the passive receivers location”), and Kanter provides a validated technique for leveraging the very interference signals that degrade active radar performance - by passively extracting the jammer’s angular location - to improve target tracking rather than merely tolerating the interference. The combination of active and passive radar components with data fusion for enhanced target detection was well established in the art by at least 2012, as evidenced by Brenner et al.’s DMPAR system architecture comprising active X-band and UHF radars fused with passive PCL receivers exploiting FM, DAB, and DVB-T broadcast signals on a common sensor platform with centralized and decentralized fusion processing (Brenner, Section 2, Fig. 2). Incorporating Kanter’s interference detection and direction-of-arrival estimation into Beasley’s active radar component would enable the hybrid system to exploit interference signals as an additional source of target-bearing information, directly addressing the electronic countermeasure scenario that Beasley identifies as a primary motivation for hybrid radar architectures. There is a reasonable expectation of success because Kanter demonstrates that a monopulse radar is capable of passively determining the angular location and power of a barrage jammer using its existing antenna and receiver hardware with computational processing (Col. 2, describing the phased array antenna, monopulse receiver, FFT signal processor, and digital computer), and Beasley’s active FMCW radar similarly employs transmit and receive antennas with digital signal processing (Section II.A, Section III.A), providing the hardware foundation necessary to implement Kanter’s interference detection and DOA estimation technique.
Regarding Claim 2, Beasley in view of Kanter (‘866) teaches the sensor network according to Claim 1.
Beasley teaches: wherein the active radar component comprises a monostatic radar device (Section II.A: “the active radar component was operated in an S-Band Frequency-Modulated-Continuous-Wave (FMCW) mode, with identical 18 dBi parabolic dish antennae used for the transmit and receive channels”; Fig. 2: showing co-located Active Tx and Active Rx antennas at the hybrid radar position).
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Regarding Claim 3, Beasley in view of Kanter (‘866) teaches the sensor network according to Claim 1.
Beasley teaches: wherein the sensor fusion device is configured to calculate a position of the object based on a spatial distance between the active radar component and the passive radar component (Section I, 1): “A hybrid combination of active and passive radar capitalises on the strengths of passive radar (e.g. no transmitter cost, covert operation, spatial diversity)”; Section I: describing the DMPAR (Deployable Multiband Passive/Active Radar for Air Defense) system architecture in which “the centralised DMPAR concept yields superior performance in all the proposed scenarios” and “the centralised DMPAR has a detection range triple that of the single monostatic active radar itself”; Section II.B: describing the experimental geometry with the DVB-T tower at a known distance of 8.696 km from the radar, with the active and passive components operating from the same position but the passive component exploiting a spatially distant illuminator; Section III.D: “A correct detection decision was made by comparing the detections on each range-Doppler surface to the target GPS ground truth data”). Beasley teaches that the hybrid fusion mechanism exploits the spatial diversity inherent in the active-passive configuration - where the active radar provides direct range/Doppler and the passive radar provides bistatic range/Doppler referenced to a spatially separated transmitter - to calculate target positions, and Beasley further references the DMPAR literature in which co-located and distributed configurations of active and passive radars exploit spatial separation for improved detection range and position estimation.
Regarding Claim 4, Beasley in view of Kanter (‘866) teaches the sensor network according to Claim 1.
Beasley teaches: wherein at least one of the passive radar component and the active radar component is mobile (Section II.B: “The radar experiments were conducted in a field in Bedfordshire, UK”; Section II.A: describing the bladeRAD system as a “low-cost experimental hybrid radar system, developed from a combination of Nuand bladeRF micro 2.0 SDRs”; Section V: “Future work will look to further verify the performance benefits in hybrid radar sensing. Moreover, a two node multistatic hybrid radar experiment is planned”). The bladeRAD hybrid radar system is a portable, field-deployable SDR-based system that was transported to and operated in a field experimental setting, demonstrating that at least one of the active and passive radar components is mobile in the sense of being configured for changing place. Under BRI, a portable, field-deployable radar system satisfies the “mobile” limitation of Claim 4.
Regarding Claim 5, Beasley in view of Kanter (‘866) teaches the sensor network according to Claim 1.
Beasley teaches: wherein at least one of the active radar component, the passive radar component, and the sensor fusion device is configured to track the object (Section III.D: “The Pd was calculated as the ratio of range-Doppler surfaces the target was correctly detected in, Ndets, vs the total number of range-Doppler surfaces in the scenario, Nsurf”; Section IV.A: describing continuous sensing of car and drone targets over 15-second and 10-second measurement intervals with a “10 Hz radar update rate”; Fig. 4: showing the processing flows for both active and passive sensors producing continuous range-Doppler surfaces over time). The active and passive radar components continuously detect the target over time across successive range-Doppler surfaces, constituting tracking of the object by following the target’s position along its trajectory.
Regarding Claim 6, Beasley in view of Kanter (‘866) teaches the sensor network according to Claim 1.
Beasley teaches: wherein the sensor fusion device is configured to provide a system track of the object (Section III.C: “The binary output of the active and PBR CFAR detectors were then combined using a 1-of-k (OR) decision rule, such that a hybrid detection, Hdet, was made when either the active radar Adet or PBR Pdet made a detection”; Section III.D: describing the calculation of hybrid detection probability over time across multiple range-Doppler surfaces; Tables II and III: showing continuous hybrid detection results across the measurement scenarios). The hybrid (fused) detection output produced by the sensor fusion mechanism over successive time intervals constitutes a system track of the object, as it combines data from both the active radar component and the passive radar component to produce a time-series of detection decisions that follow the object.
Regarding Claim 7, Beasley in view of Kanter (‘866) teaches the sensor network according to Claim 1.
Claim 7 recites that the direction of arrival of the electromagnetic interference signal is determined in “at least one of the following ways… and.” This appears to be conjunctive under Super Guide Corp. v. DirecTV Enters., Inc., 358 F.3d 870, 885-86 (Fed. Cir. 2004) and requires both “the active radar component is configured to perform a estimation of the direction of arrival, and an auxiliary sensor or the sensor fusion device is configured to estimate the direction of arrival” to be taught by the prior art.
Beasley does not explicitly teach, but Kanter (‘866) teaches: the active radar component is configured to perform a[n] estimation of the direction of arrival (Col. 3, lines 10-25: “When the radar transmitter 24 is turned off, the radar system 10 may be operated in a passive mode to determine not only the angular location relative to the antenna boresight θJ, but also the average power, PJ, of the stand-off barrage jammer 14”; Abstract: “passively determining the actual direction and average power of a barrage jammer”). Kanter (‘866) teaches that the active radar component (monopulse radar system 10) is configured to perform the estimation of the direction of arrival of the interference signal (barrage jammer) by operating in a passive mode using its existing phased array antenna and monopulse receiver.
Beasley does not explicitly teach, but Kanter (‘866) teaches: the sensor fusion device is configured to estimate the direction of arrival (Col. 3, lines 22-27: “From the foregoing measurements, the digital computer 36 derives the angular location of the target, θT, in accordance with the following:
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.) The resultant difference channel signal and the resultant sum channel signal are fed to an FFT signal processor 34. The monopulse ratio for each resolved target is then determined in a conventional manner by a digital computer 36. Kanter’s digital computer 36 receives measurement data from the radar’s passive and active operating modes - specifically the jammer angle and power (measured passively), and the combined target-plus-jammer angle and power (measured actively) - and derives the target angular location from those measurements. The digital computer 36 / processor estimates the direction of arrival of the target based on the interference signal measurements. In the combined system of Beasley and Kanter (‘866), the sensor fusion device - which is the processor or radar data processing equipment that receives and processes data from both the active and passive radar components (Beasley, Section III.C - would perform this same computational derivation of the target’s angular location from the interference signal measurements, in addition to performing the hybrid data fusion described in the Claim 1 rejection. The sensor fusion device is therefore configured to estimate the direction of arrival.
The motivation to combine and reasonable expectation of success are as stated in the rejection of Claim 1.
Regarding Claims 9 and 11, Beasley in view of Kanter (‘866) teaches:
The bodies of Claims 9 and 11 recite substantively identical functional elements, differing only in their preambles.
Beasley does not explicitly teach, but Kanter (‘866) teaches: detecting an electromagnetic interference signal emitted by the object (Abstract: “A method of operating a radar to track echo signals from a target in the presence of a barrage jammer is shown to comprise the steps of actively determining the apparent direction of the combination of echo signals from a target and jamming signals”; Col. 3, lines 10-25: “When the radar transmitter 24 is turned off, the radar system 10 may be operated in a passive mode to determine not only the angular location relative to the antenna boresight θJ, but also the average power, PJ, of the stand-off barrage jammer 14”). The barrage jammer signal constitutes an electromagnetic interference signal emitted by an entity associated with the target, and Kanter’s radar system detects this interference signal.
Beasley does not explicitly teach, but Kanter (‘866) teaches: providing an estimation of a direction of arrival of the electromagnetic interference signal (Col. 3, lines 10-25: “the radar system 10 may be operated in a passive mode to determine not only the angular location relative to the antenna boresight θJ, but also the average power, PJ, of the stand-off barrage jammer 14”; Abstract: “passively determining the actual direction and average power of a barrage jammer”). The passively determined angular location constitutes an estimation of the direction of arrival of the electromagnetic interference signal.
Beasley teaches: receiving ambient radio waves reflected off the object (Section II.A: “For the PBR component, a non-cooperative DVB-T tower was used as an IoO”; Section III.B: “the surveillance channel is cross-correlated with Doppler-shifted replicas of the reference channel, creating a matrix of range compression filters, each replica matched to a particular potential target Doppler velocity”; Fig. 2: showing the passive surveillance antenna receiving reflected DVB-T signals). The PBR component receives the DVB-T broadcast signals (ambient radio waves) after they have reflected off the object.
detecting the object based on the direction of arrival and on the ambient radio waves reflected off the object
Beasley teaches a sensor fusion mechanism that detects objects based on fused active and passive radar data (Section III.C: “decentralised information fusion was used to combine the active and PBR radar detections” and Eq. 1.
Kanter (‘866) teaches detecting the object based on the direction of arrival of the interference signal (Col. 3, lines 10-25: “From the foregoing measurements, the digital computer 36 derives the angular location of the target, θT, in accordance with the following:” Eq. 1).
In the combined system, Beasley’s fusion mechanism provides detecting the object based on the direction of arrival and on the ambient radio waves reflected off the object, because Kanter (‘866)’s DOA estimation of the interference signal and Beasley’s passive radar ambient radio wave reflections are both available as inputs to the sensor fusion mechanism, which detects the object based on both data sources.
It would have been obvious to a PHOSITA before the effective filing date of the claimed invention to perform the method of detecting an electromagnetic interference signal, estimating its direction of arrival, and combining this with passive radar ambient radio wave data for object detection, by applying the interference detection and DOA estimation technique of Kanter to the hybrid active-passive radar method of Beasley. One would have been motivated to do so because Beasley identifies resilience to electronic countermeasures as a primary advantage of hybrid radar (Section I, Item 4), and Kanter provides a validated method for exploiting interference signals to derive target angular position, thereby converting a threat to active radar performance into an additional source of target information that enhances the hybrid detection method. There is a reasonable expectation of success because both Beasley and Kanter operate in the same field of radar target detection, and Kanter’s method of passively determining interference signal DOA uses standard monopulse radar processing that is implementable on the digital signal processing architecture of Beasley’s SDR-based active radar.
Regarding Claim 11, the claim is substantially the same as claim 9 and thus, the same cited sections and rationale as corresponding method claim 9 is applied.
Regarding Claim 10, Beasley in view of Kanter (‘866) teaches the method according to Claim 9.
Beasley does not explicitly teach, but Kanter (‘866) teaches: provoking an emission of the electromagnetic interference signal based on transmitting a radar signal to the object (Cols. 1-2, lines 66-67, 1-2 respectively: “radar system 10 (here a pulse Doppler monopulse radar) is shown to be tracking a target 12 in the presence of a barrage-type stand-off jammer 14”; Col. 2, lines 2-24: “The latter is shown to be effective in jamming the radar system 10 (meaning that the effective radiated power of the stand-off jammer 12 is of sufficient magnitude to degrade the signal-to-noise ratio of the radar system 10 to such a degree that the target aircraft cannot be detected)”; Col. 1, lines 39-54: “the transmitter 24 is activated to transmit several pulses and the average angle of the jammer plus target as well as the average power from the jammer plus target are determined”; Claim 1: “(b) activating the radar transmitter when the target exits from the effective zone of the jammer and measuring the average angle,
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, and the average power, PJ+T, of the target plus jammer”). Kanter (‘866) teaches that the radar system transmits radar signals to illuminate the target area, which provokes the barrage jammer (associated with the target or protecting the target) to emit interference signals; the radar transmissions function as a stimulus that elicits the interference response from the jammer.
It would have been obvious to a PHOSITA before the effective filing date of the claimed invention to include the step of provoking an emission of the electromagnetic interference signal by transmitting a radar signal to the object, as taught by Kanter, in the hybrid radar method of Beasley. One would have been motivated to do so because Kanter (‘866) teaches that active radar transmissions directed at a target protected by a jammer will provoke the jammer to emit interference signals (Cols. 1-2), and the resulting interference signals provide the input needed for the DOA estimation technique (Col. 3), thereby enabling the hybrid system to actively generate the interference measurement opportunities on which the method relies for target localization. There is a reasonable expectation of success because Kanter demonstrates a validated operational sequence in which radar transmissions provoke jammer emissions that are then exploited for target localization and this sequence is directly applicable to the active radar component of the hybrid system of Beasley.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Beasley et al. (“Multi-Band Hybrid Active-Passive Radar Sensor Fusion,” 2023) in view of Kanter (US 6,133,866) and further in view of Jackson et al. (US 2021/0088629 A1). Background evidence of the art admitted by Applicant: Brenner et al., “Signals and data fusion in a Deployable Multiband Passive-Active Radar (DMPAR),” 2012 (hereinafter “Brenner”). The Brenner is used only for background evidence and not to teach over the claims.
Regarding Claim 8, Beasley in view of Kanter (‘866) teaches the sensor network according to Claim 1.
Beasley in view of Kanter (‘866) does not explicitly teach, but Jackson et al. (‘629) teaches: an additional passive radar component, wherein the sensor fusion device is configured to receive additional data from the additional passive radar component and to perform the data fusion based on the data and the additional data ([0020]: “the receiver system 22 may include multiple receivers at multiple locations. For example, a passive radar environment 10’ includes a receiver system 22” that includes a first receiver 42a located at a first location and a second receiver 42b located at a second location. Each receiver 42a, 42b receives the transmitter signal 24, the target signal 28 and the clutter signal 32”; [0006], Claim 6: “receiving the signals directly or indirectly from the transmitter using at least two receivers at two separate locations”; [0025]: “the reference signal 24 and clutter signal 32 are nulled from the received signal…so that a residual signal is comprised mostly of the target signal 28”). Jackson et al. (‘629) teaches that a passive radar system for target detection may include multiple spatially separated passive receivers (first receiver 42a and second receiver 42b), each receiving target reflections and reference signals, with the receiver system processing data from both receivers for target detection. The second passive receiver constitutes an additional passive radar component, and the combined processing constitutes data fusion based on data from the first and additional passive radar components.
It would have been obvious to a PHOSITA before the effective filing date of the claimed invention to add an additional passive radar component to the hybrid system of Beasley and Kanter, as taught by Jackson et al. (‘629). One would have been motivated to do so because Jackson et al. (‘629) teaches that deploying multiple passive radar receivers at separate locations improves detection capability for small targets such as unmanned aerial vehicles ([0012]: “Described herein are techniques using passive radar to detect, track and classify a target such as a moving object”; [0020] describing the multi-receiver configuration), and Beasley likewise identifies the detection of small targets (micro-drones) as a primary objective (Section II.B describing the DJI Phantom drone as a test target), demonstrating that adding spatial diversity through an additional passive radar component addresses the same detection challenge that motivates both references. The use of multiple passive radar receivers in a sensor fusion architecture for improved detection was further corroborated by Brenner et al.’s DMPAR system, which employs multiple passive receivers operating across different frequency bands (FM/DAB/DVB-T and L/S band) alongside active radars on a common platform with centralized and decentralized fusion (Brenner, Section 1, Fig. 1). There is a reasonable expectation of success because Jackson et al. (‘629) demonstrates that multiple spatially separated passive radar receivers are operative for target detection using signals of opportunity ([0016]: “the transmitter is part of a 5G cellular network”; [0020] describing the dual-receiver configuration), and Beasley’s existing decentralized fusion architecture (Section III.C, Eq. (1)) is inherently extensible to incorporate additional detection inputs since the OR-rule fusion mechanism accepts binary detection decisions from any number of contributing sensors.
Conclusion
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