Direction-of-Arrival Estimation Based on Sparse Recovery with Second-Order Statistics

• Main Authors: H. Chen, Q. Wan, R. Fan, F. Wen
• Format: Article
• Language: English
• Published: Spolecnost pro radioelektronicke inzenyrstvi 2015-04-01
• Series: Radioengineering
• Subjects: Direction-of-arrival estimation; level crossing; compressive sensing; dantzing selector; convex optimization
• Online Access: http://www.radioeng.cz/fulltexts/2015/15_01_0208_0213.pdf

Traditional direction-of-arrival (DOA) estimation techniques perform Nyquist-rate sampling of the received signals and as a result they require high storage. To reduce sampling ratio, we introduce level-crossing (LC) sampling which captures samples whenever the signal crosses predetermined reference levels, and the LC-based analog-to-digital converter (LC ADC) has been shown to efficiently sample certain classes of signals. In this paper, we focus on the DOA estimation problem by using second-order statistics based on the LC samplings recording on one sensor, along with the synchronous samplings of the another sensors, a sparse angle space scenario can be found by solving an $ell_1$ minimization problem, giving the number of sources and their DOA's. The experimental results show that our proposed method, when compared with some existing norm-based constrained optimization compressive sensing (CS) algorithms, as well as subspace method, improves the DOA estimation performance, while using less samples when compared with Nyquist-rate sampling and reducing sensor activity especially for long time silence signal.