多路径环境下增强的声纳测深跟踪

A. Saucan, C. Sintes, T. Chonavel, Jean-Marc Le Caillec
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引用次数: 10

摘要

本文研究了多重干扰回波存在下侧扫声纳的DOA估计问题。我们说明了高分辨率方法和跟踪算法的潜在用途。该跟踪算法基于海底方位角的先验信息。由于模型的非线性和观测到的4600个数据的非高斯特性,该算法的实现基于粒子滤波。所提出的跟踪算法能够很好地解决多径干扰问题。注意到数据的重尾/非高斯特征,并显示出拉普拉斯分布可以更好地表征观测数据的尾部。推导了观测数据的多元拉普拉斯分布,并证明了粒子滤波与多元拉普拉斯分布的耦合比高斯假设提供了更好的估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced sonar bathymetry tracking in multi-path environment
In this paper we address DOA estimation for the side scan sonar in the presence of multiple interfering echoes. We illustrate the potential usage of high resolution methods and tracking algorithms. The proposed tracking algorithm is based on a apriori information on the sea-floor DOA angle. Because of the non-linearity of the model and non-Gaussian behavior of the observed 4600 data, the implementation of the proposed algorithm is based on the particle filter. The proposed tracking algorithm is shown to be able to resolve the multi-path interference problem. The heavy-tailed/non-Gaussian character of the data is noted and the Laplace distribution is shown to better characterize the tails of the observed data. The multivariate Laplace distribution is derived for the observed data and the particle filter coupled with the multivariate Laplace distribution is shown to provide better estimates than with the Gaussian assumption.
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