A Space Registration Algorithm for Multi-Sensor Target Tracking Using an Entropy Function

doi:10.7652/xjtuxb201411022

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A Space Registration Algorithm for Multi-Sensor Target Tracking Using an Entropy Function

更新时间：2025-07-09

- A Space Registration Algorithm for Multi-Sensor Target Tracking Using an Entropy Function
- Vol. 48, Issue 11, Pages: 128-134(2014)
- 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：
- DOI：10.7652/xjtuxb201411022
  CLC： O121.8;G558
- Online First：10 November 2014，
  
  Published：2014
- 稿件说明：
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A Space Registration Algorithm for Multi-Sensor Target Tracking Using an Entropy Function[J]. 2014, 48(11): 128-134.
DOI：

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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