摘要
针对一有三坐标雷达、两坐标雷达和红外探测器三种传感器的分布式多站多目标跟踪系统,提出了一种多制式传感器数据融合算法。算法以测量间最小距离为关联度,对测量集间的相似程度进行度量,用极大似然法估计目标位置,通过融合方法求得目标三维航迹。在作状态估计时,采用两组非线性卡尔曼滤波切换提高融合精度。
A data fusion algorithm of multiple typed sensors was put forward for a distributed multi-station multitarget tracking system which had a 3-dimensional radar, 2-dimensional radar and a infrared sensor in this paper. The algorithm measured the association between two measurements or two tracks based on the geometry distance. The maximum likelihood estimation was applied to assess the target position, and the 3-dimensional track of the target was acquired by fusion. The exchange of two nonlinear Kalman filters was used to improve the fusion accuracy in the state estimation.
出处
《上海航天》
北大核心
2005年第6期33-35,共3页
Aerospace Shanghai
关键词
多制式传感器
测量集
关联度
数据融合
极大似然法
非线性卡尔曼滤波
Multiple typed sensor
Measurement set
Association
Data fusion
Maximum likelihood
Nonlinear Kalman filtering
