No abstract

No abstract

No abstract

No abstract

In this paper, two-dimensional (2-D) direction of arrival (DOA) estimation problem with an L-shaped array is investigated. One of the major areas of concern of modern urban combat is to locate lives trapped in a building in the presence of enemy jamming conditions at very low signal-to-noise ratio. This study provides a suitable design of a tracking system that enables location of trapped survivors in hostile situation. A compressive sensing (CS) based model is proposed for an L-shaped array which offers more array aperture with reduced computational complexity. By exploiting the signal sparsity in the spatial domain, the problem of DOA estimation is transformed to the sparse reconstruction problem. To solve the reconstruction problem efficiently, the Orthogonal Matching Pursuit (OMP) algorithm is used in which single snapshot is sufficient to recover exact target locations. The results are compared with the standard Multiple Signal Classification (MUSIC) algorithm for L-shaped array in terms of recovery, root mean square error (RMSE), probability of resolution, computational complexity, failure rate and reconstruction time. Simulation shows that the proposed method considerably improves the DOA estimation performance at low signal-to-noise ratio (SNR).