系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (9): 2699-2706.doi: 10.12305/j.issn.1001-506X.2022.09.01

• 电子技术 •    下一篇

声速不确定条件下的运动水下航行器自定位

贾天一1,2,*, 高婧洁3, 申晓红2, 刘宏伟1   

  1. 1. 西安电子科技大学雷达信号处理国家重点实验室, 陕西 西安 710071
    2. 西北工业大学航海学院, 陕西 西安 710072
    3. 长安大学信息工程学院, 陕西 西安 710064
  • 收稿日期:2021-11-05 出版日期:2022-09-01 发布日期:2022-09-01
  • 通讯作者: 贾天一
  • 作者简介:贾天一(1992—), 男, 讲师, 博士, 主要研究方向为传感器网络目标定位、阵列波达方向估计|高婧洁(1988—), 女, 讲师, 硕士研究生导师, 博士, 主要研究方向为水声网络定位技术|申晓红(1965—), 女, 教授, 博士研究生导师, 博士, 主要研究方向为水下无线通信、信号检测及信息处理|刘宏伟(1971—), 男, 教授, 博士研究生导师, 博士, 主要研究方向为雷达信号处理、自动目标识别、认知探测和协同探测
  • 基金资助:
    国家自然科学基金(62192714);国家自然科学基金(62031021);国家自然科学基金(61901057);雷达信号处理国家级重点实验室支持计划(JKW202107)

Moving underwater vehicle localization with uncertain sound speed

Tianyi JIA1,2,*, Jingjie GAO3, Xiaohong SHEN2, Hongwei LIU1   

  1. 1. National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China
    2. School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
    3. School of Information Engineering, Chang'an University, Xi'an 710064, China
  • Received:2021-11-05 Online:2022-09-01 Published:2022-09-01
  • Contact: Tianyi JIA

摘要:

传统利用水下声学定位系统的航行器自定位存在两方面问题, 一方面没有考虑测量周期内航行器的运动, 另一方面没有考虑水声声速的不确定。为解决上述问题, 构建了航行器运动状态下的时间测量定位模型, 并对声速不确定性进行建模。分别推导了基于加权最小二乘的运动航行器定位方法和基于最大似然估计的声速更新方法。利用所提模型和时间测量, 不仅可以估计航行器位置, 还可以更新声速。仿真结果验证了本文所提方法在各种参数设置下均优于现有方法, 并且在时间测量噪声不大时可以达到克拉美罗下界(Cramer-Rao lower bound, CRLB), 在时间误差不大时, 声速更新结果显著提高。

关键词: 水下航行器自定位, 水声定位, 声速估计, 最大似然估计, 加权最小二乘

Abstract:

The traditional localization of vehicle using an underwater acoustic positioning system has two problems. One is the motion of the vehicle during observation period is ignored, and the other is that the uncertainty of underwater sound speed is not taken into account. A time measurement model for localization is constructed for the vehicle in motion, and the uncertainty of sound velocity is modeled to solve the above problems. A localization method for the moving vehicle is derived based on weighted least squares estimator, and a sound speed update method based on maximum likelihood estimator is proposed as well. Apart from estimating the vehicle position, the proposed model and the time mesurement are able to update the sound speed. The simulation results verify that the proposed methods outperform the existing methods for various parameter settings and achieve Cramer-Rao lower bound (CRLB) when the time measurement noise is not large. Moreover, the performance of the sound speed update is significantly improved when the time error is not large.

Key words: localization of underwater vehicle, acoustic localization, speed estimation, maximum likelihood estimation, weighted least squares

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