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Estimation of Echo Parameters of Underwater Target Based on Compressed Sensing

机译:基于压缩感知的水下目标回波参数估计

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Underwater target echo acoustic scattering is an important research basis for active sonar target detection and recognition, the underwater environment is complex and changeable, increases the difficulty of underwater target detection, access to accurate and efficient target echo parameters help to achieve the detection and identification of underwater targets. In order to solve the problem of estimating the echo parameters of underwater targets, a new fast solution method based on compressed sensing is proposed. Compressed sensing algorithms are used to compress and sample the echo signals, construct a data dictionary, and use alternating direction method of multipliers (ADMM) optimizes the solution framework, decomposes the original global problem into sub-problems, and constrains the relationship between the sub-problems to obtain the solution of the original problem. Through data simulation analysis, the algorithm in this paper can not only effectively avoid large amounts of data the problem, but also reduce the complexity of time and the results are close to Cramer-Rao Bound.
机译:水下目标回波声散射是主动声纳目标检测和识别的重要研究基础,水下环境复杂多变,增加了水下目标检测的难度,获得准确有效的目标回波参数有助于实现对目标声波的检测和识别。水下目标。为了解决水下目标回波参数估计问题,提出了一种基于压缩感知的快速求解方法。压缩感知算法用于压缩和采样回波信号,构建数据字典,并使用乘法器的交替方向方法(ADMM)优化解决方案框架,将原始全局问题分解为子问题,并约束子问题之间的关系。 -问题以获取原始问题的解决方案。通过数据仿真分析,该算法不仅可以有效避免数据量大的问题,而且可以减少时间的复杂度,其结果接近于Cramer-Rao Bound。

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