Swarm UAV SAR for 3-D Imaging: System Analysis and Sensing Matrix Design

Abstract

The unmanned aerial vehicle (UAV) is a low-cost and high-efficiency lightweight synthetic aperture radar (SAR)-mounted platform that can be used for a variety of military and civilian missions. Using multiple UAVs to form a swarm can break through the limitations of a single platform and has broad application prospects. In this article, swarm UAV SAR that contains tens or hundreds of UAV platforms is proposed for the first time. The concept and advantages of swarm UAV SAR are investigated, and the mission outlook is given. Afterward, the swarm UAV 3-D linear array SAR (LASAR) is illustrated, which enables high-resolution 3-D imaging in a single flight. Since the antenna array of the swarm UAV 3-D LASAR is sparse, the compressed sensing (CS) algorithm is applied, whose reconstruction performance is closely related to the correlation coefficient of the sensing matrix. Hence, the signal model of swarm UAV 3-D LASAR is derived, and the expression of the sensing matrix is deduced. The sensing matrix design in this article aims at obtaining satisfactory reconstruction performance by optimizing the distribution of the antenna elements, which directly influences the correlation coefficient of the sensing matrix. Considering the limitation of the practical conditions, the sensing matrix design problem is modeled as a constrained integer programming problem. Finally, a sensing matrix design method based on discrete constrained differential evolution (DCDE) algorithm is proposed to solve the optimization problem. Experimental results demonstrate the effectiveness and superiority of the proposed method.