Apparatuses and methods are described herein for identifying a Unmanned Aerial Vehicle (UAV), including, but not limited to, determining a first maneuver type, determining a first acoustic signature of sound captured by a plurality of audio sensors while the UAV performs the first maneuver type, det
Apparatuses and methods are described herein for identifying a Unmanned Aerial Vehicle (UAV), including, but not limited to, determining a first maneuver type, determining a first acoustic signature of sound captured by a plurality of audio sensors while the UAV performs the first maneuver type, determining a second acoustic signature of sound captured by the plurality of audio sensors while the UAV performs a second maneuver type different from the first maneuver type, determining an acoustic signature delta based on the first acoustic signature and the second acoustic signature, and determining an identity of the UAV based on the acoustic signature delta.
대표청구항▼
1. A method for identifying an Unmanned Aerial Vehicle (UAV), the method comprising: determining a first maneuver type;determining a first acoustic signature of sound captured by a plurality of audio sensors while the UAV performs the first maneuver type;determining a second acoustic signature of so
1. A method for identifying an Unmanned Aerial Vehicle (UAV), the method comprising: determining a first maneuver type;determining a first acoustic signature of sound captured by a plurality of audio sensors while the UAV performs the first maneuver type;determining a second acoustic signature of sound captured by the plurality of audio sensors while the UAV performs a second maneuver type different from the first maneuver type;determining a difference between the first acoustic signature and the second acoustic signature; anddetermining an identity of the UAV based on the determined difference. 2. The method of claim 1, wherein each of the first acoustic signature and the second acoustic signature is determined based on sound corresponding to the first acoustic signature and the second acoustic signature of the UAV captured with the plurality of audio sensors. 3. The method of claim 1, wherein the plurality of audio sensors is configured as a microphone array. 4. The method of claim 1, wherein determining the first maneuver type comprises: determining a first relative position and orientation of the UAV based on sound captured by the plurality of audio sensors;determining a second relative position and orientation of the UAV based on the sound captured by the plurality of audio sensors; anddetermining the first maneuver type based on the first relative position and orientation of the UAV and the second relative position and orientation of the UAV. 5. The method of claim 1, wherein determining the second maneuver type comprises: determining a third relative position and orientation of the UAV based on sound captured by the plurality of audio sensors;determining a fourth relative position and orientation of the UAV based on the sound captured by the plurality of audio sensors; anddetermining the second maneuver type based on the third relative position and orientation of the UAV and the fourth relative position and orientation of the UAV. 6. The method of claim 1, wherein the first maneuver type associated with the first acoustic signature is determined based on motion vectors of the UAV captured with at least one visual sensor. 7. The method of claim 1, further comprising: determining at least one timestamp associated with the first maneuver type; anddetermining the first acoustic signature based on the at least one timestamp. 8. The method of claim 1, wherein the second maneuver type associated with the second acoustic signature is determined based on motion vectors of the UAV captured by at least one visual sensor. 9. The method of claim 1, further comprising: determining at least one timestamp associated with the second maneuver type; anddetermining the second acoustic signature based on the at least one timestamp. 10. The method of claim 1, wherein each of the first maneuver type and the second maneuver type comprises one or more of moving in a straight line, banking left, banking right, ascending, descending, rolling, pitching, or yawing. 11. The method of claim 1, wherein the UAV is identified based on the acoustic signature delta by correlating the acoustic signature delta with a plurality of stored acoustic signature deltas associated with a plurality of UAV identities. 12. The method of claim 1, further comprising: determining at least one motion vector for the UAV;determining first identity data identifying the UAV based on the acoustic signature delta;determining second identity data identifying the UAV based on the at least one motion vector; andcorrelating the first identity data with the second identity data to determine the identity of the UAV. 13. The method of claim 12, wherein determining the at least one motion vector for the UAV comprises: receiving video stream data corresponding to the UAV from at least one visual sensor; anddetermining the at least one motion vector of the UAV based on the video stream data. 14. The method of claim 12, wherein determining the second identity data based on the at least one motion vector comprises correlating the at least one motion vector with a plurality of stored motion vectors associated with a plurality of UAV identities. 15. The method of claim 12, wherein the first identity data and the second identity data are time-aligned for the correlation based on a timestamp associated with the first identity data and a timestamp associated with the second identity data. 16. The method of claim 12, further comprising: determining third identity data based on radar data associated with the UAV; andcorrelating one or more of the first identity data, the second identity data, and the third identity data to determine the identity of the UAV. 17. The method of claim 12, further comprising: determining third identity data based on wireless communication signals associated with the UAV; andcorrelating one or more of the first identity data, the second identity data, and the third identity data to determine the identity of the UAV. 18. The method of claim 12, further comprising: determining third identity data based on infrared or thermal data associated with the UAV; andcorrelating one or more of the first identity data, the second identity data, and the third identity data to determine the identity of the UAV. 19. The method of claim 1, further comprising: determining information relating to the UAV;determining first identity data identifying the UAV based on the acoustic signature delta;determining second identity data identifying the UAV based on the determined information; andcorrelating the first identity data with the second identity data to determine the identity of the UAV. 20. The method of claim 1, wherein the identity of the UAV comprises information relating to a manufacturer, model, shape, size, or number of rotors of the UAV. 21. The method of claim 1, wherein the identity of the UAV includes information relating to characteristics of the UAV. 22. An identification apparatus configured to determine an identity associated with an Unmanned Aerial Vehicle (UAV), the identification apparatus comprising: an acoustic-based identification apparatus comprising a first processor configured to: determine a first maneuver type;determine a first acoustic signature of sound captured by a plurality of audio sensors while the UAV performs the first maneuver type;determine a second acoustic signature of sound captured by the plurality of audio sensors while the UAV performs a second maneuver type different from the first maneuver type;determine a difference between the first acoustic signature and the second acoustic signature; anddetermine the identity of the UAV based on the determined difference. 23. The identification apparatus of claim 22, further comprising a video/image-based identification apparatus including: a visual sensor array configured to capture visual data corresponding to the UAV; anda second processor configured to: determine at least one motion vector associated with motion of the UAV from the visual data; andoutput second identity data identifying the UAV based on the at least one motion vector; anda fusion engine configured to identify the UAV based on both the first identity data and the second identity data. 24. The identification apparatus of claim 23, wherein the first maneuver type is identified based on the at least one motion vector of the UAV captured with the visual sensor array. 25. The identification apparatus of claim 22, wherein the first processor is further configured to determine the first maneuver type by: determining a first relative position and orientation of the UAV based on sound captured by a plurality of audio sensors;determining a second relative position and orientation of the UAV based on the sound captured by the plurality of audio sensors; anddetermining the first maneuver type based on the first relative position and orientation of the UAV and the second relative position and orientation of the UAV. 26. The identification apparatus of claim 22, wherein the first processor identifies the UAV based on the acoustic signature delta by correlating the acoustic signature delta with a plurality of stored acoustic signature deltas associated with a plurality of UAV identities. 27. The identification apparatus of claim 22, wherein the acoustic-based identification apparatus further comprises an audio sensor array comprising the plurality of audio sensors configured to capture the sound generated by the UAV. 28. A non-transitory computer-readable medium containing processor-readable instructions such that, when executed, cause a processor of an identification apparatus to perform a process to identify an Unmanned Aerial Vehicle (UAV), the process comprising: determining a first maneuver type;determining a first acoustic signature of sound captured by a plurality of audio sensors while the UAV performs the first maneuver type;determining a second acoustic signature of sound captured by the plurality of audio sensors while the UAV performs a second maneuver type different from the first maneuver type;determining a difference between the first acoustic signature and the second acoustic signature; anddetermining an identity of the UAV based on the determined difference. 29. An apparatus configured to determine an identity of an Unmanned Aerial Vehicle (UAV), the identification apparatus comprises: means for determining a first maneuver type;means for determining a first acoustic signature of sound captured by a plurality of audio sensors while the UAV performs the first maneuver type;means for determining a second acoustic signature of sound captured by the plurality of audio sensors while the UAV performs a second maneuver type different from the first maneuver type;means for determining a difference between the first acoustic signature and the second acoustic signature; andmeans for determining an identity of the UAV based on the determined difference.
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이 특허에 인용된 특허 (2)
Salloum, Hady; Sedunov, Alexander; Sedunov, Nikolay; Sutin, Alexander, Passive acoustic detection, tracking and classification system and method.
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