Research on linear sparse sonar array for targets azimuth bearing estimation
Hongmei Zhang, Xiwei Sun, Mingjie Chen
Abstract
Hongmei Zhang, Xiwei Sun, Mingjie Chen
Abstract
For the problem of underwater targets bearing estimation, the performance of linear sonar array is researched. To get big sonar array aperture and then to achieve high angular resolution with few sensor elements, sparse random array is introduced. To address the coherent problem of incident signals that radiate from targets, the CS (compressive sensing) based method is proposed to estimate the bearing angles of sonar targets, due to the compressive property of far field target signal. Contrast with the conventional designed sonar array, the new designed sonar array and proposed DOA (direction of arrival) estimation algorithm can achieve high angular resolution and de-correlation ability for incident signals from far-field sonar targets.
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For the problem of underwater targets bearing estimation, the performance of linear sonar array is researched. To get big sonar array aperture and then to achieve high angular resolution with few sensor elements, sparse random array is introduced. To address the coherent problem of incident signals that radiate from targets, the CS (compressive sensing) based method is proposed to estimate the bearing angles of sonar targets, due to the compressive property of far field target signal. Contrast with the conventional designed sonar array, the new designed sonar array and proposed DOA (direction of arrival) estimation algorithm can achieve high angular resolution and de-correlation ability for incident signals from far-field sonar targets.
Key concepts: Sonar, Synthetic aperture sonar, Azimuth, Bearing (navigation), Sonar signal processing, Acoustics, Compressed sensing, Computer science