A Novel Sparse Array Configuration with Low Coarray Redundancy for DOA Estimation in Mobile Wireless Sensor Network

Abstract

For tacking and localizing sources in the mobile wireless sensor network, underdetermined direction of arrival (DOA) estimation with high-accuracy is a crucial issue. In this paper, a novel sparse array configuration is developed for accurate DOA estimation from the perspective of sum-difference coarray (SDCA). As compared with most of the existing sparse array configurations, the proposed array can effectively reduce the overlap between difference coarray (DCA) and sum coarray (SCA) and can achieve more consecutive degrees of freedom (DOF), more sources can be resolved accordingly. Additionally, the proposed array has hole-free DCA and SDCA. Then, the concept of coarray redundancy ratio (CRR) is introduced for evaluating the coarray overlap quantitatively and the closed-form CRR expressions of the proposed array are derived in detail. Based on the good properties of the proposed array, vectorized conjugate augmented MUSIC (VCAM) is adopted for underdetermined DOA estimation. The theoretical propositions and numerical simulations demonstrate the superior performance of the proposed array in terms of CRR, consecutive DOF, and DOA estimation accuracy.

A High-Performance Energy-Balanced Forwarding Strategy for Wireless Sensor Networks

“…WSN is composed of a large number of low-power, microsmart sensor nodes that are randomly deployed to perform sensing tasks in the monitoring area. In recent years, WSNs have played an important role in the production of life, environmental monitoring, national security, and other fields [1][2][3][4][5]. Because sensor nodes are usually powered passively with limited energy and weak computing power, it is important to build an energy-efficient WSN.…”