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A High Resolution Random Linear Sonar Array Based MUSIC Method for Underwater DOA Estimation

机译:基于水下DOA估计的高分辨率随机线性声纳阵列的基于音乐方法

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In existing sonar signal processing techniques, linear arrays are generally used which sampled at Nyquist rate that demands the inter-element spacing is less than or equal to half of the system wavelength. Otherwise, ambiguous bearing angles will generate in conventional DOA (direction of arrival) estimation methods, such as MUSIC, Capon algorithm. This fact restricts the array aperture, so as to the resolution of targets parameters in estimation. In this paper, a kind of random linear sonar array is designed which breakthrough the Nyquist sampling rate restriction and expand the sonar array with no additional sensor elements, and then the MUSIC algorithm is used to DOA estimation. Simulation are made under low signal SNR and multi centralized target sources, results show that, with the new designed sonar array, the resolution is extremely improved contrast with conventional designed array.
机译:在现有的声纳信号处理技术中,通常使用线性阵列,其在奈奎斯特速率下采样,要求元件间隔小于或等于系统波长的一半。否则,含糊不清的轴承角将在传统的DOA(到达方向)估计方法中产生,例如音乐,CAPON算法。这一事实限制了阵列孔径,以便在估计中分辨于目标参数。在本文中,设计了一种随机线性声卡阵列,其突破了奈奎斯特采样率限制并展开了没有附加传感器元件的声纳阵列,然后将音乐算法用于DOA估计。仿真在低信号SNR和多重集中目标源下进行,结果表明,随着新设计的声纳阵列,分辨率与传统设计阵列相比,分辨率极其改善。

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