基于统计矢量的多传感器精度估计方法

A Statistical Vector Based Sensor Precision Evaluation Method for Multi-sensor Fusion System

多传感器数据融合系统能否准确掌握传感器的实际探测精度,对数据关联的参数选择、合成算法的权重分配等非常重要,对融合性能影响很大。然而,在目标位置真值未知的情况下,传感器难以依据自身的探测信息准确评估其探测精度。论文基于多传感器对共同目标探测信息的内在冗余性,提出了一种传感器精度在线估计方法,以统计矢量服从正态分布的水平评估为基础构造参数适应度函数,利用遗传算法估计传感器精度参数,并进行了仿真实验。结果表明,所提方法能够有效地估计多平台下的多传感器精度,随着传感器对目标测量数据的增多,传感器精度参数估计的准确度会提高,当相对运动的两传感器对共同目标的探测数据量达到1000时,传感器精度参数估计值的相对误差可控制在10%以内。

It is significant to obtain the accurate precision of sensors in multi-source fusion system for the parameters'selection of data association,the weight allocation of synthesis algorithm and so on.According to the inherent redundancy of multi-sensors'measurement on common targets,the paper puts forward a statistical vector based method to evaluate the sensor precision without the targets'true position.The principles and data processing procedure are described in detail.The simulations on computer are carried out and the influence of data quantity on evaluation is analyzed.The results show that the proposed method can effectively estimate the sensors'precision on the multi-platform,and the accuracy of sensors'precision can increase the amount of measuring date.When the amount of data is up to 1000,the relative error can be controlled within 10%.