# US 11,115,585 B2 · Systems, methods, and devices for unmanned vehicle detection > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,115,585 B2 - Document ID: US11115585B2 - Status: Granted - Kind: B2 - Application number: 17/063,135 - Filed: 2020-10-05 - Published: 2021-03-18 - Granted: 2021-09-07 - Earliest claimed: 2017-01-23 - Assignees: Digital Global Systems, Inc. - Applicants: Digital Global Systems, Inc. - Inventors: David William Kleinbeck - Web page: https://patentgrep.com/patent/US11115585B2 ## CPC - H04N 23/61: based on recognised objects - G01R 29/0892: {Details related to signal analysis or treatment; presenting results, e.g. displays; measuring specific signal features other than field strength, e.g. polarisation, field modes, phase, envelope, maximum value} - G01S 5/0221: {Receivers} - G01S 5/02585: {at least one of the measurements being a non-radio measurement} - G01S 5/12: by co-ordinating position lines of different shape, e.g. hyperbolic, circular, elliptical or radial - G06T 7/70: Determining position or orientation of objects or cameras (camera calibration G06T7/80) - G06T 7/73: using feature-based methods - G08B 5/36: using visible light sources - G08B 25/08: using communication transmission lines {(G08B13/19658, G08B21/0286, G08B25/016 take precedence)} - G08B 25/10: using wireless transmission systems {(G08B25/009 takes precedence)} - G08B 29/185: {Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system} - H04N 7/181: {for receiving images from a plurality of remote sources} - H04N 23/60: Control of cameras or camera modules - H04N 23/69: Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming - H04N 23/695: Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects - G06T 2207/10016: Video; Image sequence - G06T 2207/20056: Discrete and fast Fourier transform, [DFT, FFT] - G06T 2207/30212: Military - G06T 2207/30232: Surveillance - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G08B: SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS ## Abstract Systems, methods, and apparatus for detecting UAVs in an RF environment are disclosed. An apparatus is constructed and configured for network communication with at least one camera. The at least one camera captures images of the RF environment and transmits video data to the apparatus. The apparatus receives RF data and generates FFT data based on the RF data, identifies at least one signal based on a first derivative and a second derivative of the FFT data, measures a direction from which the at least one signal is transmitted, analyzes the video data. The apparatus then identifies at least one UAV to which the at least one signal is related based on the analyzed video data, the RF data, and the direction from which the at least one signal is transmitted, and controls the at least one camera based on the analyzed video data. ## Claims ### Claim 1 An apparatus for detecting unmanned aerial vehicles in a radio frequency (RF) environment, comprising: at least one RF receiver and a video analytics module; wherein the apparatus is in network communication with at least one video sensor and at least one server; wherein the at least one video sensor is configured to capture images of the RF environment and stream video data to the apparatus; wherein the at least one RF receiver is configured to receive RF data and generate fast Fourier transform (FFT) data based on the RF data; wherein the at least one server is configured to identify at least one signal based on the FFT data; wherein the at least one signal comprises at least one drone radio signal and/or at least one drone controller signal; wherein the at least one server is configured to measure a direction from which the at least one signal is transmitted; and wherein the at least one server is configured to identify at least one unmanned aerial vehicle to which the at least one signal is related based on the RF data, the direction from which the at least one signal is transmitted, and analyzed video data created based on the video data. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein the video analytics module is configured to determine a distance from the at least one unmanned aerial vehicle and the inclination or declination of the at least one unmanned aerial vehicle based on the analyzed video data. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein the video analytics module is configured to determine a type of the at least one unmanned aerial vehicle based on the analyzed video data. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein the video analytics module is configured to detect if the at least one unmanned aerial vehicle has at least one future payload. ### Claim 5 (depends on 1) The apparatus of claim 1, wherein the video analytics module is further operable to determine if the at least one unmanned aerial vehicle is utilizing more than one camera based on the analyzed video data and the RF data. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein the video analytics module is operable to perform facial recognition, reading license plates, and/or querying databases. ### Claim 7 (depends on 1) The apparatus of claim 1, wherein the video analytics module is further operable to determine if there is more than one unmanned aerial vehicle when the at least one signal comprises multiple drone radio signals and/or multiple drone controller signals. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein the video analytics module is operable to track a formation of the at least one unmanned aerial vehicle. ### Claim 9 (depends on 1) The apparatus of claim 1, wherein the at least one unmanned aerial vehicle is at least two unmanned aerial vehicles, and wherein the apparatus is operable to determine if the at least two unmanned aerial vehicles are in a tethered operation or a non-tethered operation. ### Claim 10 (depends on 1) The apparatus of claim 1, wherein the video analytics module is operable to detect humans, animals, and land-based vehicles based on the analyzed video data. ### Claim 11 (depends on 1) The apparatus of claim 1, wherein the apparatus is operable to measure a deterministic approximation of a flight path for the at least one unmanned aerial vehicle based on the RF data and the analyzed video data. ### Claim 12 (depends on 1) The apparatus of claim 1, wherein the apparatus is operable to provide points of reference to the video sensor. ### Claim 13 A system for detecting unmanned aerial vehicles in a radio frequency (RF) environment, comprising: at least one apparatus constructed and configured for network communication with at least one camera and at least one server; wherein the at least one apparatus comprises at least one RF receiver; wherein the at least one camera is configured to capture images of the RF environment and stream video data to the at least one server; wherein the at least one RF receiver is configured to receive RF data and generate fast Fourier transform (FFT) data based on the RF data; wherein the at least one server is configured to identify at least one signal based on the FFT data; wherein the at least one server is configured to measure a direction from which the at least one signal is transmitted; and wherein the at least one server is configured to identify at least one unmanned aerial vehicle to which the at least one signal is related based on the RF data, the direction from which the at least one signal is transmitted, and analyzed video data created based on the video data. ### Claim 14 (depends on 13) The system of claim 13, wherein each of the at least one camera comprises a multiplicity of lenses. ### Claim 15 (depends on 14) The system of claim 14, wherein the multiplicity of lenses includes a synthesized aperture between 70 degrees and 150 degrees. ### Claim 16 (depends on 13) The system of claim 13, wherein the at least one camera is stationary. ### Claim 17 (depends on 13) The system of claim 13, wherein the at least one camera has pan, tilt, and zoom features. ### Claim 18 A method for detecting unmanned aerial vehicles in a radio frequency (RF) environment, comprising: providing at least one apparatus constructed and configured for network communication with at least one camera and at least one server, wherein the at least one apparatus comprises at least one RF receiver; the at least one RF receiver receiving RF data in the RF environment and generating fast Fourier transform (FFT) data based on the RF data; the at least one server identifying at least one signal based on the FFT data; the at least one server measuring a direction from which the at least one signal is transmitted; the at least one apparatus providing a point of reference for the at least one camera based on the direction from which the at least one signal is transmitted; the at least one camera capturing images of the RF environment and streaming video data to the at least one apparatus; and the at least one server identifying at least one unmanned aerial vehicle to which the at least one signal is related based on the RF data, and the direction from which the at least one signal is transmitted, and analyzed video data created based on the video data. ### Claim 19 (depends on 18) The method of claim 18, wherein the at least one apparatus comprises a multiplicity of apparatus and the at least one camera comprises a multiplicity of cameras, and wherein the multiplicity of apparatus and the multiplicity of cameras are in a cluster layout connecting to a multi-node analytics and control platform. ### Claim 20 (depends on 19) The method of claim 19, wherein the multi-node analytics and control platform includes an orchestrator, and wherein the orchestrator is operable to orchestrate the monitoring of a plurality of existing threats and the monitoring of a plurality of new threats.