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Unmanned aerial systems (UAS) are effective forsurveillance and monitoring, but struggle with persistent, long-term tracking due to limited flight time. Persistent trackingcan be accomplished using multiple vehicles if one vehiclecan effectively hand off the tracking information to anotherreplacement vehicle. In this paper we propose a solution tothe moving-target handoff problem in the absence of GPS. Theproposed solution uses a nonlinear complimentary filter forself-pose estimation using only an IMU, a particle filter forrelative pose estimation between UAS using a relative rangemeasurement, visual target tracking using a gimballed camerawhen the target is close to the handoff UAS, and track correlationlogic using Procrustes analysis to perform the final target handoffbetween vehicles. We present extensive simulation results thatdemonstrates the effectiveness of our approach and performMonte-Carlo simulations that indicate a 97% successful handoffrate using the proposed methods. 

Rapidly developing UAS technology necessitates reliable counter UAS systems. This paper proposes a formation controlled dragnet as a possible solution and compares potential intercept algorithms that can be used in this scenario. Proportional navigation and target-predictive path planning, both existing algorithms, are explored and an original approach, Adaptive Radius Optimal Defense (AROD), is introduced. Simulation results are given and the strengths and weaknesses of each approach are discussed. Based on the simulation results, some advantages that AROD offers over other existing algorithms are listed. Possible improvements and future research directions are also suggested.