Page 93 - 应用声学2019年第5期

第 38 卷 第 5 期 Vol. 38, No. 5
2019 年 9 月 Journal of Applied Acoustics September, 2019

⋄ 研究报告 ⋄

基于并行蚁群算法的长基线定位方法 ∗

张海如 † 汪 俊 王海斌

(中国科学院声学研究所 声场声信息国家重点实验室 北京 100190)

摘要 为了降低各个误差源对水声目标导航定位精度的影响，该文将水声目标导航定位问题抽象为带约束条
件的非线性优化问题，并论证了最优化表达式参数求解过程与降低误差源干扰的过程具有同一性；设计了并
行蚁群算法求其最优解。海试数据处理结果表明，该方法具有收敛速度快、解稳定和定位精度高等优点，能有
效地降低各个误差源对水声目标导航定位精度的影响。
关键词 长基线声学定位，导航定位，非线性优化，并行蚁群算法
中图法分类号: TP391 文献标识码: A 文章编号: 1000-310X(2019)05-0845-06
DOI: 10.11684/j.issn.1000-310X.2019.05.013

Parallel ant colony algorithm for long baseline acoustic positioning

ZHANG Hairu WANG Jun WANG Haibin

(State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China)

Abstract In order to reduce the influence of various error sources on the navigation accuracy of underwater
acoustic target, a novel long baseline positioning algorithm is proposed, which abstracts the problem of under-
water acoustic target navigation as a nonlinear optimization problem with constrained conditions. The analysis
indicates that the parameter solving process of the optimization expression has the identity with the process
of reducing error source interference. Then, its optimal solution is found by a parallel ant colony algorithm.
The experimental results from sea trial data show that the proposed algorithm has the advantages of fast
convergence speed, stable solution and high positioning accuracy. It can effectively reduce the influence of
various error sources on navigation accuracy of underwater acoustic target.
Key words Long baseline acoustic positioning, Navigation and localization, Nonlinear optimization, Parallel
ant colony algorithm

2018-11-29 收稿; 2019-03-08 定稿
中国博士后科学基金资助项目 (2016LH0016), 国家自然科学基金项目 (11434012), 国家自然科学基金国际 (地区) 合作与交流项目
∗
(41561144006)
作者简介: 张海如 (1987- ), 男, 天津人, 博士, 研究方向: 水声信号处理、计算智能、自适应信号处理。
† 通讯作者 E-mail: zhanghairu66@126.com