US 11,899,473 B2
Counter drone system
Jason Levin, Costa Mesa, CA (US); Palmer F. Luckey, Newport Beach, CA (US); Julian Hammerstein, Murrieta, CA (US); and Joseph Chen, Irvine, CA (US)
Assigned to Anduril Industries, Inc., Costa Mesa, CA (US)
Filed by Anduril Industries, Inc., Irvine, CA (US)
Filed on Jun. 1, 2022, as Appl. No. 17/830,000.
Application 17/830,000 is a continuation of application No. 16/415,924, filed on May 17, 2019, granted, now 11,385,659.
Prior Publication US 2023/0082239 A1, Mar. 16, 2023
Int. Cl. G05D 1/12 (2006.01); B64D 7/00 (2006.01); F41H 11/02 (2006.01); H04W 4/021 (2018.01); G01H 9/00 (2006.01); G01S 7/41 (2006.01); B64C 39/02 (2023.01); G01S 7/48 (2006.01); B64U 101/15 (2023.01)
CPC G05D 1/12 (2013.01) [B64C 39/024 (2013.01); B64D 7/00 (2013.01); F41H 11/02 (2013.01); H04W 4/021 (2013.01); B64U 2101/15 (2023.01); B64U 2201/10 (2023.01); G01H 9/00 (2013.01); G01S 7/41 (2013.01); G01S 7/4802 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A system for countering a threat drone, comprising:
a plurality of sensor systems, wherein a sensor system of the plurality of sensor systems comprises one or more sensors that are connected to a network;
a counter drone, wherein the counter drone is connected to the network; and
a processor configured to:
receive an indication of a potential target from the plurality of sensor systems;
generate a fused data set of the potential target, wherein the fused data set comprises the indication of the potential target and one or more of: another indication of the potential target, a raw sensor information, and/or a derived sensor information, wherein generating the fused data set comprises determining that the one or more of the another indication of the potential target, the raw sensor information, and/or the derived sensor information are all associated with the potential target and combining the one or more of the another indication of the potential target, the raw sensor information, and/or the derived sensor information;
determine that the potential target comprises the threat drone based at least in part on the fused data set, comprising:
determine that a characteristic of the potential target is within a range, is within a geofenced area, or has a trajectory that will take it within a radius of a geofenced area; and
in response to determining that the potential target comprises the threat drone, provide counter drone instructions to the counter drone, comprising:
determine a payload type based on a strategy to address the threat drone;
determine counter drone candidates based on the payload type;
determine flight paths of the counter drone candidates;
rank probabilities of threat drone interception of the counter drone candidates based on the determined flight paths;
select intercept drones of the counter drone candidates based on the ranked probabilities; and
provide the counter drone instructions to the selected intercept drones.