Strategies for unwrapping multisensors interferometric side scan sonar phase

C. Sintes, B. Solaiman
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引用次数: 14

Abstract

This paper concerns the description of a method of 2/spl pi/ bias removal for the interferometric phase. The first part is the description of different noise sources for interferometric side-scan sonar. In fact, these noise sources can generally be classified into two categories: a. environmental noise category (variable celerity, sonar motion, etc.), and, b. interferometric process related noise (decorrelation baseline, decorrelation of wave train, propagation, multipath propagation). Each source of noise is described as a physical phenomena. This study aims at developing a global density of probability function (dpf) including all statistical phenomena corresponding to the 'b' category of noise (interferometric process). The second part checks the statistical properties of phase on real data and uses them as a confidence factor in the 2/spl pi/ bias removal process. The third part deals with the global process using the vernier technique to derive benefit from the interferometric multi arrays and the theoretical properties (vernier efficiency) connected to the specific configuration of the sonar. The main conclusion of this paper concerns the theoretical interest of the global comprehension of the vernier technique (statistical properties checked on experimental data and intrinsic properties of the vernier) to plan strategies to remove the 2/spl pi/ bias and gain of treatment on real data. Based on these results different applications are possible such as the incorporation of noise in simulation process; this allows data collection in more complex virtual experimental scene than in a real scene for example.
多传感器干涉侧扫声纳相位展开策略
本文描述了一种干涉相位2/spl pi/偏置去除方法。第一部分是对干涉侧扫声纳中不同噪声源的描述。实际上,这些噪声源一般可以分为两类:一类是环境噪声(变速、声纳运动等),另一类是干涉过程相关噪声(去相关基线、波列去相关、传播、多径传播)。每个噪声源都被描述为一种物理现象。本研究旨在建立一个全局概率函数密度(dpf),包括与“b”类噪声(干涉过程)相对应的所有统计现象。第二部分在实际数据上检查相位的统计特性,并将其用作2/spl pi/偏置去除过程中的置信因子。第三部分讨论了利用游标技术从干涉多阵列中获益的全局过程,以及与声纳特定配置相关的理论特性(游标效率)。本文的主要结论涉及游标技术的整体理解(实验数据检查的统计性质和游标的内在性质)的理论兴趣,以计划消除2/spl pi/偏差和实际数据处理增益的策略。基于这些结果,可以在模拟过程中加入噪声;例如,这允许在比真实场景更复杂的虚拟实验场景中收集数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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