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 .
Response to Arguments
Applicants’ arguments filed 8/26/2026 have been fully considered but they are not persuasive. Applicant argues
1) the phase array antenna of Parker does not transmit a radar signal.
Response: paragraph 61 of parker states “ ECM modulation configuration data and receive blanking signal unit 30 interacts with the Keysight unit 34. Modulation Function Generation—designated as 34 in FIGS. 1A-3, Is specialized algorithm software that has been developed to transmit (Jam) a specific radio frequency, designated by 38 in FIG. 1A-3 and 42 in FIGS. 1A and 3, which is unique to a specific unmanned aerial vehicles/systems utilizing a database library that was created and categorized with the specific radio frequencies used on all common unmanned aerial vehicles/systems”. Indicating system 10 is transmits a signal to jam the UAVs. Which is a radio signal. Since the claim only teach the primary radar device transiting a radio device to deactivate the UAVs, by the broadest reasonable interpretation of the claims in light of the spec the transmitter 10 of Parker is being used in the same manner as the radar of the current application.
2) Parker does not teach "the same phased array antenna systems of the primary radar system both operate for detection and emit the high-intensity RF beam for deactivation of detected UAV's."
Response: claim 1 does not require the primary radar to detect a signal but merely transmit a beam for deactivation with the phase array section of it.
3) Parker does not teach "determining a need to deactivate score" does not identify any computed value or score.
Response: Parker either determines the UAV needs to be destroyed which would be a score of yes or does not which would be a score of no. The applicant does not define an equation for calculating a score in the claim.
4) Zhang does not teach” the control system comprises a signal processor configured for receiving and processing said sensing data to determine a likelihood measure indicative of probability that source of the sensing data is a UAV, thereby enabling deactivation of detected UAV's.”
Response: Parker teaches in paragraph 73, “The RF detection receiver and processors 24 determine the: radio (carrier) frequency, pulse width or pulse duration, pulse repetition interval, signal amplitude and polarization; to a lesser extent the scan pattern and rate. These characteristics are then compared within the library database 36 to the known characteristics of the most likely sUAS RF elements. Zhang is merely used to as a citation of determining a likelihood based on detected data.
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.
Claim(s) 1-3, 9-11, 14, and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Parker et al (US 20170192089) in view of Weinstein et al (US 10040554).
Regarding claim 1, 14, and 18, Parker teaches a primary radar comprising one or more phased array antenna systems (fig 1a item 10 and para 46), a sensor arrangement (fig 1a, items 12, 14, 16), and a control system; said sensor arrangement comprises one or more sensors configured for collecting sensing data indicative of presence and location of one or more unmanned aerial vehicles (UAV's) within a predetermined region (abstract and fig 3 and 4, items 103, 104, and 105), and to provide said sensing data to the control system (para 21, “Once the decision has been made to engage the target sUAS, the tracking system then guides the fire control trigger to release the countermeasure at the exact moment needed to affect your target with minimal collateral damage to areas surrounding the target sUAS. The connection between the tracking optic and the fire control trigger contains dozens of microprocessors and electronic, electro-optic, and electro-mechanical components. When the system engages the fire control triggering mechanism,”); the control system comprises at least one processor configured for processing the sensing data, determining a need to deactivate score for the one or more UAV's (para 21, “Once the decision has been made to engage the target sUAS, the tracking system then guides the fire control trigger to release the countermeasure at the exact moment needed to affect your target with minimal collateral damage to areas surrounding the target sUAS. The connection between the tracking optic and the fire control trigger contains dozens of microprocessors and electronic, electro-optic, and electro-mechanical components. When the system engages the fire control triggering mechanism,”), and generating operational instructions to the primary radar system for generating deactivation beam directed toward location of said one or more UAV's, thereby deactivating said one or more UAV's (para 21, “the images are aligned and matched, the interrupt is released allowing the transmission of the desired interdiction transmission. As soon the system intersects the designation point, the fire control trigger is released executing a perfectly aimed deterrent countermeasure”), said operational instructions comprise data on location of the one or more UAV's and instructions to said primary radar system to emit, by the one or more phased array antenna systems of the primary radar system, a focused high intensity RF beam directed at said location of the one or more UAV's to at least partially deactivate said one or more UAV's, thereby providing said deactivation beam (para 12, “If the threat assessment level exceeds a certain threshold, the system can automatically deploy interdiction 10 to incapacitate or destroy the target 44” and para 46, “FIGS. 1A and 2, is a signal processing technique used in sensor (Antenna) arrays for directional signal transmission; this is achieved by combining elements in a phased array in such a way that signals at particular angles experience constructive interference while others experience destructive interference; this equipment can be purchased “Off-The-Shelf” and one common manufacturer of this type of equipment is Motorola. Directional Antenna—designated as 10 in FIGS. 1A and 2” and para 61, “ ECM modulation configuration data and receive blanking signal unit 30 interacts with the Keysight unit 34. Modulation Function Generation—designated as 34 in FIGS. 1A-3, Is specialized algorithm software that has been developed to transmit (Jam) a specific radio frequency, designated by 38 in FIG. 1A-3 and 42 in FIGS. 1A and 3, which is unique to a specific unmanned aerial vehicles/systems utilizing a database library that was created and categorized with the specific radio frequencies used on all common unmanned aerial vehicles/systems”).
Regarding claim 1, Weinstein teaches said sensor arrangement comprises one or more acoustic sensors operable for detecting acoustic signals associated with UAV operation, and wherein the one or more acoustic sensors utilize received signal strength (RSS) for determining data on location of one or more signal sources (“claim 2, “; first filtering means for detecting frequency and/or amplitude characteristics within said acoustic signals received by said first acoustic antenna array, indicative of said UAV, and operative to derive a first angle from which acoustic signals are being received from said UAV with respect to said first receiver antenna array; a second acoustic receiver antenna array comprising at least three antenna elements, positioned at a second location different from said first location, operative to passively receive acoustic signals emitted from said UAV; second filtering means for detecting frequency and/or amplitude characteristics within said acoustic sign”). It would have been obvious to modify Parker to include said sensor arrangement comprises one or more acoustic sensors operable for detecting acoustic signals associated with UAV operation, and wherein the one or more acoustic sensors utilize received signal strength (RSS) for determining data on location of one or more signal sources because it is merely a substitution of a well known method to determine location of a UAV for deactivation of Parker with the method to determine location of a uav of Weinstein to yield a predictable UAV detection device.
Regarding claim 2 and 19, Parker teaches said sensor arrangement comprises two or more sensors configured to be positioned in two or more different positions in vicinity of the primary radar system, thereby providing sensing data enabling triangulation of one or more UAV's positions (fig 1 and 2, items 12 and 14)
Regarding claim 3 and 20, Parker teaches said sensor arrangement comprises one or more sensors selected from optical sensors, RF sensor, and acoustic sensors a lidar, a secondary radar unit and a camera operable in visible or infrared wavelength range (fig 1a, items 16).
Regarding claim 9, Parker teaches said control unit comprises a signal locator module configured and operable for receiving and processing said sensing data and for determining data on location of signal source, generating sensing data associated with one or more UAV's (para 13, “Radio Frequency Direction Finding (DF), Electro Optical and Infra-Red (EO/IR) imagers, and Laser Range Finding (LRF), used to derive necessary location and spectral characteristics of a commercial unmanned aerial system (UAS) or drone”)
Regarding claim 10, Parker teaches said signal locator is configured for determining location of said signal source in accordance with direction and distance data included in said sensing data (para 20, “the field of view and displays the suspect sUAS target(s) along with vital pieces of data including range-to-target, target velocity, deterrent angle, compass heading, wind velocity and direction, deterrent zone size, countermeasure type”)
Regarding claim 11, Parker teaches said need to deactivate score is determined based on said sensing data and pre-stored conditions comprising conditions associated with one or more of: size of UAV, UAV signature, UAV position, and UAV movement pattern (para 20, “Once the suspect sUAS is tagged the LRF produces an X, Y and Z data point that is sent to the countermeasure system (14) for automatic alignment of the destructive or non-destructive deterrent element (10), (RF, Laser, Impulse, Munitions, etc.). This is a significant advantage over current military systems for providing the necessary steps for increased safety when operating in a civilian/commercial environment. During the time that the suspect sUAS is being viewed through the EO/IR camera system, the images and heat signatures are compared with known sUAS images and heat signatures for possible type identification/classification and threat assessment” and para 21).
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.
Claim(s) 6-8 and 23-25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Parker in view of Weinstein as applied to claim 1 and 18 above, and further in view of Zhang et al (CN 110274595).
Regarding claim 6 and 23, Zhang teaches a control system comprises a signal processor configured for receiving and processing said sensing data to determine a likelihood measured indicative of probability that source of the sensing data is a UAV, thereby enabling deactivation of detected UAV's (“floor detection may include: step S201, obtaining the to-be-detected data of the unmanned aerial vehicle. the current state information of the unmanned vehicle that is unmanned aerial vehicle floor in the detection process for maximum likelihood estimation, for example, vertical speed, pitch angle rate and roll rate, etc., step S202, obtaining the training sample data corresponding to detection data, step S203, using the training sample data obtained by determining the prior probability function corresponding to the detection data; step S204, the prior probability function to be detected data obtained according to the step S201 and the step S203 obtained by constructing the likelihood function corresponding to to-be-detected data, step S205, calculating the likelihood function building deconstruction, to obtain the maximum likelihood estimation value”). It would have been obvious to modify Parker to include a control system comprises a signal processor configured for receiving and processing said sensing data to determine a likelihood measured indicative of probability that source of the sensing data is a UAV, thereby enabling deactivation of detected UAV's because it is merely a substitution of a well-known method to determine if an object is a UAV of Parker with the method to determine if an object is a UAV of Zhang to yield a predictable UAV determiner.
Regarding claim 7 and 24, Zhang teaches said signal processor comprises trained machine learning module, trained for determining one or more UAV's presence within received sensing data (“floor detection may include: step S201, obtaining the to-be-detected data of the unmanned aerial vehicle. the current state information of the unmanned vehicle that is unmanned aerial vehicle floor in the detection process for maximum likelihood estimation, for example, vertical speed, pitch angle rate and roll rate, etc., step S202, obtaining the training sample data corresponding to detection data, step S203, using the training sample data obtained by determining the prior probability function corresponding to the detection data; step S204, the prior probability function to be detected data obtained according to the step S201 and the step S203 obtained by constructing the likelihood function corresponding to to-be-detected data, step S205, calculating the likelihood function building deconstruction, to obtain the maximum likelihood estimation value”). It would have been obvious to modify Parker to include said signal processor comprises trained machine learning module, trained for determining one or more UAV's presence within received sensing data because it is merely a substitution of a well-known method to determine if an object is a UAV of Parker with the method to determine if an object is a UAV of Zhang to yield a predictable UAV determiner.
Regarding claim 8 and 25, Zhang teaches said signal processor operates for determining said likelihood measure in accordance with one or more parameters of signal source selected from: speed, size, moving pattern, physical shape, and acoustic signal (“floor detection may include: step S201, obtaining the to-be-detected data of the unmanned aerial vehicle. the current state information of the unmanned vehicle that is unmanned aerial vehicle floor in the detection process for maximum likelihood estimation, for example, vertical speed, pitch angle rate and roll rate, etc., step S202, obtaining the training sample data corresponding to detection data, step S203, using the training sample data obtained by determining the prior probability function corresponding to the detection data; step S204, the prior probability function to be detected data obtained according to the step S201 and the step S203 obtained by constructing the likelihood function corresponding to to-be-detected data, step S205, calculating the likelihood function building deconstruction, to obtain the maximum likelihood estimation value”). It would have been obvious to modify Parker to include said signal processor operates for determining said likelihood measure in accordance with one or more parameters of signal source selected from: speed, size, moving pattern, physical shape, and acoustic signal because it is merely a substitution of a well-known method to determine if an object is a UAV of Parker with the method to determine if an object is a UAV of Zhang to yield a predictable UAV determiner.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Parker in view of Weinstein as applied to claim 1 above, and further in view of Weberstetter (ES 2748668 T3).
Regarding claim 13, Weberstetter teaches a control unit comprises a verification module configured for continuously receiving sensing data from the sensor arrangement and for processing the sensing data to determine activity status of said one or more UAV's to thereby determine success score of the deactivation beam (“the combat measures of the sequence are carried out individually and the success of each combat measure is verified after it has been carried out, in which if the combat measure is successful, the sequence is aborted and, otherwise, the next combat measure of said sequence is carried out”). It would have been obvious to modify Parker to include a control unit comprises a verification module configured for continuously receiving sensing data from the sensor arrangement and for processing the sensing data to determine activity status of said one or more UAV's to thereby determine success score of the deactivation beam because it would tell the operator if the deactivation of the enemy drone worked.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIMOTHY A BRAINARD whose telephone number is (571)272-2132. The examiner can normally be reached Monday - Friday 8:30 a.m.-5 p.m.
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TIMOTHY A. BRAINARD
Primary Examiner
Art Unit 3648
/TIMOTHY A BRAINARD/Primary Examiner, Art Unit 3648
