IP Library Granted Patent US 11,750,911
Granted Patent B2
US 11,750,911 · App. 18/128,680 · Granted Sep 5, 2023

Systems, methods, and devices for unmanned vehicle detection

Inventor: David William Kleinbeck (Lees Summit, MO)
Assignee: DIGITAL GLOBAL SYSTEMS, INC.
H04N23/61G01R29/0892G01S5/0221G01S5/02585G06T7/70G08B29/185H04N23/69H04N23/695G06T2207/10016G06T2207/30232
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Quick Facts
Patent No.
US 11,750,911
App. No.
18/128,680
Granted
Sep 5, 2023
Kind
B2
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 (41)

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 communication with at least one video sensor;

wherein the at least one video sensor is configured to capture images of the RF environment and transmit video data to the apparatus;

wherein the at least one RF receiver is configured to receive RF data;

wherein the apparatus is configured to identify at least one signal based on a first derivative and a second derivative of Fast Fourier Transform (FFT) data based on the RF data;

wherein the at least one signal is related to at least one unmanned aerial vehicle;

wherein the apparatus is configured to measure a direction from which the at least one signal is transmitted; and

wherein the apparatus is configured to identify the at least one unmanned aerial vehicle 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.

2. The apparatus of claim 1 , wherein the video analytics module is configured to determine a distance of the at least one unmanned aerial vehicle and an inclination or a declination of the at least one unmanned aerial vehicle.

3. The apparatus of claim 1 , wherein the video analytics module is configured to determine a type of the at least one unmanned aerial vehicle.

4. 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.

5. 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.

6. The apparatus of claim 1 , wherein the video analytics module is operable to perform facial recognition, read license plates, and/or query databases.

7. 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.

8. The apparatus of claim 1 , wherein the video analytics module is operable to track a formation of the at least one unmanned aerial vehicle.

9. 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.

10. The apparatus of claim 1 , wherein the video analytics module is operable to detect humans, animals, and land-based vehicles.

11. 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.

12. The apparatus of claim 1 , wherein the apparatus is operable to provide points of reference to the at least one video sensor.

13. A system for detecting unmanned aerial vehicles in a radio frequency (RF) environment, comprising:

at least one apparatus constructed and configured for communication with at least one camera;

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 transmit video data to the at least one apparatus;

wherein the at least one RF receiver is configured to receive RF data;

wherein the at least one apparatus is configured to identify at least one signal based on a first derivative and a second derivative of Fast Fourier Transform (FFT) data based on the RF data, wherein the at least one signal is related to at least one unmanned aerial vehicle;

wherein the at least one apparatus is configured to measure a direction from which the at least one signal is transmitted; and

wherein the at least one apparatus is configured to identify the at least one unmanned aerial vehicle 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.

14. The system of claim 13 , wherein each of the at least one camera comprises a multiplicity of lenses.

15. The system of claim 14 , wherein the multiplicity of lenses includes a synthesized aperture between 70 degrees and 150 degrees.

16. The system of claim 13 , wherein the at least one camera is stationary.

17. The system of claim 13 , wherein the at least one camera has pan, tilt, and zoom features.

18. A method for detecting unmanned aerial vehicles in a radio frequency (RF) environment, comprising:

providing at least one apparatus constructed and configured for communication with at least one camera, wherein the at least one apparatus comprises at least one RF receiver;

the at least one RF receiver receiving RF data;

the at least one apparatus identifying at least one signal based on a first derivative and a second derivative of Fast Fourier Transform (FFT) data based on the RF data, wherein the at least one signal is related to at least one unmanned aerial vehicle;

the at least one apparatus measuring a direction from which the at least one signal is transmitted;

the at least one camera capturing images of the RF environment and transmitting video data to the at least one apparatus; and

the at least one apparatus identifying the at least one unmanned aerial vehicle 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.

19. 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 connected to a multi-node analytics and control platform.

20. The method of claim 19 , wherein the multi-node analytics and control platform includes an orchestrator, and wherein the orchestrator is operable to orchestrate monitoring of a plurality of existing threats and a plurality of new threats.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 10, 2023
From: KLEINBECK, DAVID WILLIAM
To: DIGITAL GLOBAL SYSTEMS, INC.
Reel/Frame 063273/0258 →
Continuity (9)
Continuation 17466712 · Sep 3, 2021
Continuation 17063135 · Oct 5, 2020
Continuation 16694284 · Nov 25, 2019
Continuation 16274933 · Feb 13, 2019
Continuation In Part 16180690 · Nov 5, 2018
Continuation In Part 15412982 · Jan 23, 2017
Provisional Application 62722420 · Aug 24, 2018
Provisional Application 62632276 · Feb 19, 2018
Related Publication 20230254567A1 · Aug 10, 2023