基于遗传算法的被动测距声纳子阵位置误差估计

IF 0.2 Q4 ACOUSTICS
Minyoung Eom, Do-Young Kim, G. Park, K. Shin, S. Oh
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引用次数: 1

摘要

被动测距声纳(PRS)是一种由左右舷三个子阵组成的被动声纳,具有探测目标并计算方位和距离的特点。方位和距离计算需要物理子阵位置信息,当子阵位置信息不准确时,方位和距离精度性能会下降。特别是,与使用两个时延平均值的轴承相比,使用两个时延平均值的轴承对距离精度性能的影响更大。为了改善这一问题,需要对子阵位置误差估计和误差补偿进行研究。本文基于优化搜索技术遗传算法估计子阵位置误差,提出了一种通过补偿位置误差引起的时延误差来提高距离精度性能的方法。此外,我们将使用海上数据验证所提出的算法及其性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Position error estimation of sub-array in passive ranging sonar based on a genetic algorithm
: Passive Ranging Sonar (PRS) is a type of passive sonar consisting of three sub-array on the port and starboard, and has a characteristic of detecting a target and calculating a bearing and a distance. The bearing and distance calculation requires physical sub-array position information, and the bearing and distance accuracy performance are deteriorated when the position information of the sub-array is inaccurate. In particular, it has a greater impact on distance accuracy performance using plus value of two time-delay than a bearing using average value of two time-delay. In order to improve this, a study on sub-array position error estimation and error compensation is needed. In this paper, We estimate the sub-array position error based on genetic algorithm, an optimization search technique, and propose a method to improve the performance of distance accuracy by compensating the time delay error caused by the position error. In addition, we will verify the proposed algorithm and its performance using the sea-going data
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来源期刊
CiteScore
0.60
自引率
50.00%
发文量
1
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