基于学习策略的多速率多传感器融合定位方法

doi:10.7527/S1000-6893.2022.26904

集群智能与协同控制

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基于学习策略的多速率多传感器融合定位方法

陈博, 岳凯, 王如生, 胡明南

1. 浙江工业大学信息工程学院，杭州 310014

收稿日期:2022-01-06 修回日期:2022-01-20 发布日期:2022-03-11
通讯作者: 陈博,E-mail:bchen@zjut.edu.cn E-mail:bchen@zjut.edu.cn
基金资助:
浙江省重点研发计划（2022C03029）；浙江省自然科学基金（LR20F030004）

Learning-based multi-rate multi-sensor fusion localization method

CHEN Bo, YUE Kai, WANG Rusheng, HU Mingnan

1. College of Information Engineering, Zhejiang University of Technology, Hangzhou 310014, China

Received:2022-01-06 Revised:2022-01-20 Published:2022-03-11
Supported by:
Key Research and Development Program of Zhejiang Province （2022C03029）；Zhejiang Provincial Natural Science Foundation of China （LR20F030004）

摘要/Abstract

摘要： 考虑了一类目标运动模型未知且多传感器异步采样情况下的移动目标定位跟踪问题，提出了一种仅依赖于测量信息的数据驱动目标跟踪定位方法。为了解决运动模型未知的问题，依据测量模型及量测范围设计分布式神经网络结构，进而基于神经网络建立量测数据至状态变量的映射关系。在此基础上，针对多速率多传感器数据的异步问题，引入了一种基于上一量测更新时刻的数据补偿策略，构建以时间差为输入特征的权值网络模型，进而提出一种利用迭代学习逼近真实目标位置的目标定位算法。最后，通过实验对所提出方法的优越性和有效性进行了验证。

关键词: 目标跟踪, 多传感器融合估计, 神经网络, 多速率采样, 数据驱动

Abstract: This paper concerned with a class of problems of moving target tracking with unknown target motion model and multi-sensor asynchronous sampling. A data-driven target tracking algorithm is proposed， which only relies on measurement information. To solve the problem of the unknown motion model， a distributed neural network structure is designed based on the measurement model and measurement range， then the mapping relationship between the observation data and the state variables is established based on the designed neural network. A compensation strategy based on the measurement data at the last sampling instant is introduced to solve the multi-rate and multi-sensor sampling asynchronous problem. We also construct a weight network model with time difference as the input feature to estimate the real target position by iterative learning. An experiment is given to show the superiority and effectiveness of the proposed method.

Key words: target tracking, multi-sensor fusion, neural network, multi-rate sampled-data, data driven

中图分类号:

V219
TP391

陈博, 岳凯, 王如生, 胡明南. 基于学习策略的多速率多传感器融合定位方法[J]. 航空学报, 2022, 43(S1): 726904-726904.

CHEN Bo, YUE Kai, WANG Rusheng, HU Mingnan. Learning-based multi-rate multi-sensor fusion localization method[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726904-726904.

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于学习策略的多速率多传感器融合定位方法

Learning-based multi-rate multi-sensor fusion localization method

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