Unmanned aerial systems (UAS) are effective for surveillance and monitoring, but struggle with persistent, longterm tracking due to limited flight time. Persistent tracking can be accomplished using multiple vehicles if one vehicle can effectively hand off the tracking information to another replacement vehicle. In this paper we propose a solution to the moving-target handoff problem in the absence of GPS. The proposed solution uses a nonlinear complimentary filter for self-pose estimation using only an IMU, a particle filter for relative pose estimation between UAS using a relative range measurement, visual target tracking using a gimballed camera when the target is close to the handoff UAS, and track correlation logic using Procrustes analysis to perform the final target handoff between vehicles. We present extensive simulation results that demonstrates the effectiveness of our approach and perform Monte-Carlo simulations that indicate a 97% successful handoff rate using the proposed methods.
Unmanned aerial systems (UAS) are effective for surveillance and monitoring, but struggle with persistent, longterm tracking due to limited flight time. Persistent tracking can be accomplished using multiple vehicles if one vehicle can effectively hand off the tracking information to another replacement vehicle. In this paper we propose a solution to the moving-target handoff problem in the absence of GPS. The proposed solution uses a nonlinear complimentary filter for self-pose estimation using only an IMU, a particle filter for relative pose estimation between UAS using a relative range measurement, visual target tracking using a gimballed camera when the target is close to the handoff UAS, and track correlation logic using Procrustes analysis to perform the final target handoff between vehicles. We present extensive simulation results that demonstrates the effectiveness of our approach and perform Monte-Carlo simulations that indicate a 97% successful handoff rate using the proposed methods.
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