基于雷达和光学传感器的目标状态联合估计研究  

Research on Joint Estimation of Target State Based on Radar and Optical Sensor

作　　者：沈立桥 李硕[1] 石忠华 任伦[1] 李晓松[1] SHEN Liqiao;LI Shuo;SHI Zhonghua;REN Lun;LI Xiaosong(Xi'an Electronic Engineering Research Institute,Xi'an 710100)

机构地区：[1]西安电子工程研究所,西安710100

出　　处：《火控雷达技术》2024年第3期73-78,83,共7页Fire Control Radar Technology

摘　　要：针对传统雷达和光学传感器的目标状态联合估计未考虑到不同传感器精度对于联合系统的影响而导致跟踪效果不理想的问题,提出一种基于雷达和光学传感器的目标状态间接联合估计方法,提高了联合系统对目标的跟踪性能。该方法首先建立了雷达和光学传感器的观测模型和基于非合作目标的CA运动模型,然后基于雷达和光学传感器的测量精度结合扩展卡尔曼滤波(Extended Kalman Filter,EKF)设计了一种间接联合估计算法,实验仿真结果表明该方法相比较传统的直接联合估计方法,可以更为准确地估计目标位置、速度和加速度等状态信息,有效提高了对非合作目标的跟踪精度。In order to solve the problem that the tracking effect of the joint estimation of target state of traditional radar and optical sensor did not take into account the influence of the accuracy of different sensors on the joint system,an indirect joint estimation method of target state based on radar and optical sensor was proposed,which improved the tracking performance of the joint system.In this method,the observation model of radar and optical sensor and the CA motion model based on non-cooperative target are established,and then an indirect joint estimation algorithm was designed based on the measurement accuracy of radar and optical sensor combined with extended Kalman filter(EKF).Experimental simulation results showed that this method can estimate the target position,velocity and acceleration more accurately than the traditional direct joint estimation method.The tracking accuracy of non-cooperative targets was effectively improved.

关 键 词：状态跟踪 间接联合估计 非合作目标 EKF算法 

分 类 号：TN95[电子电信—信号与信息处理]