多静态声纳跟踪的分布式环境反演

J. Pitton, A. Ganse, Gregory Anderson, D. Krout
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引用次数: 3

摘要

本文提出了一种适应声传播环境的跟踪算法。这种自适应是通过测量接触幅度将预期目标信噪比(SNR)纳入数据关联步骤来实现的。在这项工作中,预期信噪比是通过声学建模提供的;声学模型所需的底损和散射强度估计值通过基于实测多静声呐混响数据的声学模型反演得到。本文表明,分布式传感器的使用提供了对环境参数的改进估计,从而更好地估计预期的信噪比
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Environmental Inversion for Multi-Static Sonar Tracking
This paper presents an approach for adapting a tracking algorithm to the acoustic propagation environment. This adaptation is performed by incorporating the expected target signal-to-noise ratio (SNR) into the data association step through the measured contact amplitude. In this work, expected SNR is provided via acoustic modeling; estimates of bottom loss and scattering strength, required by the acoustic model, are obtained via inversion of the acoustic model based on measured multi-static sonar reverberation data. This paper shows that the use of distributed sensors provides improved estimates of the environmental parameters, and hence better estimates of the expected SNR
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