Automated matched-field tracking in shallow water 2000 IEEE international symposium

P. Baxley, R. Brannan
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引用次数: 1

Abstract

Matched-field tracking (MFT) is the application of matched-field processing (MFP) to a moving source. This involves either post-processing MFP outputs to detect tracks of target peaks, or generalizing the search space of the processor to include candidate source tracks. The latter approach, referred to as automated MFT, is examined in this paper. By integrating matched-field correlations over candidate source tracks, the true track can be detected (as determined by the highest integrated correlation) and the target track parameters estimated. In addition, the integration process results in a gain in detectibility for the true source track. For the general case of a source moving in three-dimensions through an environment which varies in three dimensions, the technique is computationally restrictive, because of the large number search parameters. However, for a vertical line array (VLA) in a range-independent environment, and an assumption of constant-depth, constant range-rate tracks, the search space is reduced to the range and depth at the beginning (or end) of the track, and the range-rate. The integration process can then be performed by a simple shift-then-average scheme applied to range-depth ambiguity-surface time samples. For a constant-velocity source, the range-rate can generally be assumed to be constant, except for a period in which it passes through the closest-point-of-approach (CPA). For that case, a CPA estimator, which attempts to match data from a moving source with that expected for candidate CPA tracks, is implemented. For horizontal line arrays (HLAs), a hybrid planewave beamforming/matched-field processing, track-before-detect (TBD) technique, which takes advantage of the azimuthal-filtering capability of HLAs to limit the bearing search, may be used. This approach provides estimates of the full track parameters (range, depth, course, and speed) with a processing load substantially lower than that required for a fully three-dimensional MFP search. These techniques are applied to experimental tonal data collected on a VLA and HLA during the 1996 Shallow Water Evaluation Cell Experiment (SWellEX-96), which occurred in 200-m water, 6 km southwest of San Diego.
浅水自动匹配场跟踪2000 IEEE国际学术研讨会
匹配场跟踪(MFT)是将匹配场处理(MFP)应用于运动源。这涉及到对MFP输出进行后处理以检测目标峰值的轨迹,或者将处理器的搜索空间一般化以包含候选源轨迹。后一种方法,称为自动化MFT,在本文中进行了研究。通过对候选源航迹的匹配场相关性进行积分,可以检测到真实航迹(由最高积分相关性确定)并估计目标航迹参数。此外,集成过程还提高了对真实源轨迹的可探测性。对于一般情况下,一个源在三维空间中通过一个三维变化的环境移动,由于大量的搜索参数,该技术在计算上受到限制。然而,对于距离无关环境下的垂直线阵列(VLA),假设航迹深度恒定,航迹距离速率恒定,搜索空间被简化为航迹起始(或结束)的距离和深度,以及航迹距离速率。然后,积分过程可以通过应用于距离-深度模糊性-表面时间样本的简单平移-平均方案来执行。对于恒定速度的源,距离速率一般可以假定为恒定的,除了它经过最接近点(CPA)的一段时间外。对于这种情况,将实现CPA估计器,它将尝试将来自移动源的数据与候选CPA轨道的预期数据相匹配。对于水平线阵列(HLAs),一种混合的平面波波束形成/匹配场处理,可以使用跟踪前检测(TBD)技术,该技术利用了水平线阵列的方位滤波能力来限制方位搜索。这种方法提供了完整航迹参数(范围、深度、航向和速度)的估计,其处理负荷大大低于完全三维MFP搜索所需的处理负荷。这些技术应用于1996年浅水评价单元实验(SWellEX-96)期间VLA和HLA收集的实验色调数据,该实验发生在圣地亚哥西南6公里的200米水域。
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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