| 贾雨晴,苏林,郭圣明,马力.浅海时变声速环境下的自适应匹配场定位算法实现*[J].,2018,37(4):518-527 |
| 浅海时变声速环境下的自适应匹配场定位算法实现* |
| An adaptive matched-field source localization algorithm in coastal water under the circumstances of time-evolving sound speed profiles |
| 投稿时间：2017-11-02 修订日期：2018-06-27 |
| 中文摘要: |
| 针对浅海环境下声速剖面失配引起的匹配场处理器失配问题，提出了一种自适应匹配场定位算法在声速剖面时变环境下的实现方式。将先验声速剖面集简化为经验正交函数表示，结合蒙特卡洛方法与环境扰动约束算法对当下时刻的目标声源进行匹配场定位。本文以某次试验获取的连续20小时的声速剖面数据为研究对象，通过仿真试验对该算法进行验证，结果表明：在先验声速剖面集的半小时之后，利用自适应算法的距离和深度定位成功率较常规匹配场算法有较大提升，其中，深度正确定位概率相对较低。 |
| 英文摘要: |
| The sound speed profile (SSP) in water column is highly variable in time and space and can not be accurately known among measurement periods in coastal water. These factors will lead to the modeling mismatch and influence the performance of source localization of matched field processing (MFP). An approach of adaptive matched-field localization of source range and depth estimation is discussed under the circumstances of time-evolving sound speed profiles. In this paper, we represent a priori SSPs by the empirical orthogonal functions (EOFs) and estimate the instant source position by combing the environmental perturbed constraint method with Monte Carlo method. Synthetic simulations are carried out with experimental SSP data lasted 20 hours and acoustic pressure data from a vertical line array. The simulation results show that the proposed algorithm can be used to locate the distance and depth of an a priori sound velocity profile set after half an hour The success rate is greatly improved compared with the conventional matching field algorithm, in which the probability of correct positioning in depth is relatively low. |
| DOI：10.11684/j.issn.1000-310X.2018.04.011 |
| 中文关键词: 时变声速环境,环境扰动约束,经验正交函数分解,声源定位 |
| 英文关键词: time-varying environment, environmental perturbed constraint,empirical orthogonal function,source localization |
| 基金项目:国家自然科学基金项目 (117043961006256) |
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