[1]王苏慧,王黎明,韩星程,等.基于最大一致的水下目标协同定位[J].机械与电子,2022,(12):9-14.
　WANG Suhui,WANG Liming,HAN Xingcheng,et al.Cooperative Positioning of Underwater Targets Based on Maximum Consistency[J].Machinery & Electronics,2022,(12):9-14.
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基于最大一致的水下目标协同定位()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2022年12期
页码:
9-14
栏目:
设计与研究
出版日期:
2022-12-24

文章信息/Info

Title:
Cooperative Positioning of Underwater Targets Based on Maximum Consistency
文章编号:
1001-2257 ( 2022 ) 12-0009-06
作者:
王苏慧 1 ; 王黎明 1 ; 韩星程 1 ; 叶泽甫 2 ; 朱竹君?2
1. 中北大学信息探测与处理山西省重点实验室,山西 太原 030051 ; 2. 山西格盟中美清洁能源研发中心有限公司,山西 太原 030032
Author(s):
WANG Suhui1 ;  WANG Liming1 ;  HAN Xingcheng1 ;  YE Zefu2 ;  ZHU Zhujun2
( 1.Shanxi Key Laboratory of Information Detection and Processing , North University of China , Taiyuan 030051 , China ; 2.Shanxi Gemeng Sino-US Clean Energy R&D Center Co. , Ltd. , Taiyuan 030032 , China )
关键词:
最大一致性; 平均一致性; 协同定位; 无迹 Kalman 滤波
Keywords:
maximum consensus ;  average consensus ;  cooperative localization ;  traceless Kalman filter
分类号:
TP212.9
文献标志码:
A
摘要:
针对水下运动目标定位时,现有的平均一致无迹Kalman 滤波器仅能实现近似一致而带来定位精度低的问题,提出一种分布式最大一致无迹 Kalman 信息滤波算法。首先,建立目标与传感器模型,构建水下目标协同定位框架;然后,通过等价变换将集中式无迹 Kalman 滤波算法改写为信息滤波形式,降低传感器计算维数;最后,对改写后的信息向量和信息矩阵采用最大一致处理策略,并引入虚拟节点技术来处理节点同值问题。结果表明,所提算法的定位轨迹与目标实际轨迹重合度更高且误差整体水平更小,验证了所提算法的有效性。
Abstract:
A distributed maximum consistent traceless Kalman information filtering algorithm was proposed to address the problem that the existing mean consistent traceless Kalman filter can only achieve approximate localization and bring low localization accuracy when localizing underwater moving targets. Firstly , a cooperative localization framework for underwater targets was constructed by establishing target and sensor models ; then , the centralized traceless Kalman filtering algorithm was rewritten as a traceless Kalman information filtering algorithm by equivalence transformation to reduce the number of sensor computational dimensions ; finally , the rewritten information vector and information matrix were processed by a maximally consistent distributed strategy , and a virtual node technique was introduced to deal with the node homogeneity problem.The proposed algorithm is validated by simulation , and the localization trajectory of the proposed algorithm overlaps more with the actual trajectory of the target and the overall level of error is smaller , which verifies the effectiveness of the proposed algorithm.

参考文献/References:

[ 1 ] 方子涵,李旦,蒋鹏,等 . 无线传感器网络中延迟补偿的分布式时钟同步算法 [ J ] . 仪器仪表学报, 2021 ,42( 12 ): 92-100.

[ 2 ] 刘妹琴,韩学艳,张森林,等 . 基于水下传感器网络的目标跟踪技术研究现状与展望[ J ] . 自动化学报, 2021 , 47( 2 ): 235-251.
[ 3 ] ZHAN D Z , ZHENG H R , XU W.Tracking control of autonomous underwater vehicles with acoustic localization and extended Kalman filter [ J ] .Applied sciences , 2021 , 11 ( 17 ): 8038-8055.
[ 4 ] LI W Y , WEI G L , HAN F , et al.Weighted average consensus-based unscented Kalman filtering [ J ] .IEEE Transactions on cybernetics , 2016 , 46 ( 2 ): 558-567.
[ 5 ] LIU P , TIAN Y P , ZHANG Y.Distributed Kalman filtering with finite-time max-consensus protocol [ J ] . IEEE Access , 2018 , 6 : 10795-10802.
[ 6 ] 王领,申晓红,康玉柱,等 . 水声传感器网络信号到达时间差目标定位的最小二乘法估计性能[ J ] . 兵工学报,2020 , 41 ( 3 ): 542-551.
[ 7 ] 张薇 . 自主式水下机器人辅助的水声传感网定位算法研究[ D ] . 石家庄:河北师范大学,2020.
[ 8 ] 于镇滔,王忠庆,刘鹏 . 基于最大一致容积 Kalman 滤波器的多机器人协同定位[ J ] . 导航定位与授时, 2022 ,9 ( 1 ): 104-110.

备注/Memo

备注/Memo:
收稿日期: 2022-06-05
基金项目:山西省基础研究计划资助项目( 20210302124545 );山西省高等学校科技创新基金( 2020L0301 )
作者简介:王苏慧 ( 1998- ),女,河北石家庄人,硕士研究生,研究方向为水下目标定位跟踪;王黎明 ( 1974- ),男,山西运城人,教授,研究方向为 X 射线图像处理、多维信号获取与处理、无损检测技术等。
更新日期/Last Update: 2023-01-04