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In this paper, an angles of arrival(AOA) localization algorithm based on A-optimality criterion is proposed to solve the problem of unmanned aerial vehicle(UAV) Swarm locating various motion states targets. Firstly, a multi-sites AOA positioning model and a model of error variance changing with the received signal-to-noise ratio are established. Then, A-optimality criterion under this model is derived theoretically, and the optimal spatial configuration of UAV Swarm is analyzed by FIM. Secondly, the target is located by ML algorithm, and the change of flight angle and flight distance of UAV Swarm is analyzed with the minimum value of CRLB matrix trace as the objective function. At last, real-time path optimization is carried out on the flight path of UAV Swarm at the next moment. Simulation results show that path optimization is able to effectively improve the positioning accuracy of UAVs in various motion states.