Underdetermined direction of arrival estimation with nonuniform linear motion sampling based on a small unmanned aerial vehicle platform

Abstract

Uniform linear array (ULA) radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles (UAVs). In practice, a ULA’s multi-target direction of arrival (DOA) estimation performance suffers from significant performance degradation owing to the limited number of physical elements. To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform, we propose a nonuniform linear motion sampling underdetermined DOA estimation method. Using the motion of the UAV platform, the echo signal is sampled at different positions. Then, according to the concept of difference co-array, a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom (DOFs). Through position analysis of the original and motion arrays, we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs. Under the condition of no increase in the aperture of the physical array, the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA. The results of numerical simulations conducted herein verify the superior performance of the proposed method.