采用熵函数法的多传感器空间配准算法的研究

郭军军; 元向辉; 韩崇昭

doi:10.7652/xjtuxb201411022

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采用熵函数法的多传感器空间配准算法的研究

更新时间：2025-07-09

- 采用熵函数法的多传感器空间配准算法的研究
- A Space Registration Algorithm for Multi-Sensor Target Tracking Using an Entropy Function
- 西安交通大学学报 2014年48卷第11期页码：128-134
- 作者机构：
  
  西安交通大学智能网络与网络安全教育部重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2014-04-25。作者简介: 郭军军(1987—),男,博士生;元向辉(通信作者),男,博士,讲师。基金项目: 国家“973计划”资助项目(2013CB329405);国家自然科学基金委创新研究群体资助项目(61221063);国家自然科学基金资助项目(61203221)
- DOI：10.7652/xjtuxb201411022
  中图分类号： O121.8;G558
- 网络首发：2014-11-10，
  
  纸质出版：2014
- 稿件说明：
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郭军军, 元向辉, 韩崇昭. 采用熵函数法的多传感器空间配准算法的研究[J]. 西安交通大学学报, 2014,48(11):128-134.

A Space Registration Algorithm for Multi-Sensor Target Tracking Using an Entropy Function[J]. 2014, 48(11): 128-134.
郭军军, 元向辉, 韩崇昭. 采用熵函数法的多传感器空间配准算法的研究[J]. 西安交通大学学报, 2014,48(11):128-134. DOI： 10.7652/xjtuxb201411022.

A Space Registration Algorithm for Multi-Sensor Target Tracking Using an Entropy Function[J]. 2014, 48(11): 128-134. DOI： 10.7652/xjtuxb201411022.

摘要

针对传感器空间配准问题

提出了一种基于滑窗法的极小化极大熵函数的传感器空间配准算法。该算法使用熵函数作为优化准则

根据传感器的量测模型推导出关于传感器系统偏差的目标函数

然后借助极大熵函数的思想

将目标函数的绝对值转化为对应的极大熵函数

并且使用拟牛顿法求得的极大熵函数的解作为传感器系统偏差的估计值。在单目标跟踪场景和多目标跟踪场景下

与传统传感器空间配准算法在相同的仿真条件下进行对比

仿真结果表明

所提算法能够有效地提高传感器距离量测和角度量测系统偏差的估计精度

从而实现高精度的空间目标跟踪。

Abstract

An algorithm using a mini-max entropy function is proposed for sensor registration. The algorithm uses an entropy function as the optimization criterion

and the objective function is formulated based on a measurement model. The principle of the maximum entropy is employed to transform the absolute value of the objective function into a maximum entropy function

and then a quasi-Newton method is used to minimize the maximum function to obtain the sensor biases. Simulation results in both the scenarios of a single target and the multiple targets and comparisons with the traditional registration algorithm show that the method has a significant an improvement in performance of reducing errors of the sensor biases.

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references

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