Target localization and pursuit by sensor-equipped UAVs using distance information

This paper describes a problem in which a network consisting of a sensor-equipped UAV and multiple beacons, operating in a large geographical space, uses distance measurements to estimate the position of a target and pursue it. The positions of the beacon are also not known to the UAV and needs to be estimated by the UAV, again using distance measurements. Distance measurements are assumed to have been obtained from methods which are noisy in nature, due to which Kalman filter is used to get more accurate location estimates of the beacons and the target. The trajectory of the UAV is decomposed into a discovery phase and a pursuit phase. In discovery phase only beacon positions are estimated and in the pursuit phase a pursuit guidance law is used to guide the UAV to approach the target. Performance of the algorithm is demonstrated through simulations.