摘要
为实现高频地波雷达中的多目标跟踪,有效利用多普勒量测改善系统性能,采用多假设数据关联算法的多目标跟踪系统,提出了多普勒速度优先的二重波门设置和基于扩展卡尔曼滤波(EKF)的多假设算法。基于EKF的多假设算法,直接利用EKF过程中得到的参数更新观测向量方差,计算假设的概率,实现多假设数据关联。建立仿真场景,验证了二重波门设置能有效减少杂波干扰,并将基于EKF的多假设算法与独立假设下引入多普勒速度的关联算法比较,结果表明基于EKF的多假设算法在高频地波雷达这种较高杂波密度条件下效率更高,捕捉航迹和滤除虚假点迹的能力更强。
A double gate setting with priority of Doppler velocity and the Extended Kalman Filter(EKF) based Multiple Hypothesis Tracking(MHT) algorithm are proposed in order to realize Multiple Targets Tracking(MTT) in High Frequency(HF) ground-wave radar, and to effectively improve the performance of MTT by using the Doppler measurement. In the EKF based MHT, parameters obtained in the EKF are adopted directly to calculate the probability of each hypothesis. A simulation scene is built, and the EKF based MHT algorithm is compared with the one which assumes that the Doppler measurement is independent from the radius measurement. Simulation results show that the double gate setting helps induce number of clutter, and the EKF-based MHT algorithm is better than the other one under dense environments of HF ground-wave radar with stronger track-catching and false-alarm-filtering ability and higher efficiency.
出处
《太赫兹科学与电子信息学报》
2015年第1期35-39 45,45,共6页
Journal of Terahertz Science and Electronic Information Technology
关键词
多普勒速度
数据关联
二重波门设置
多假设算法
扩展卡尔曼滤波
Doppler velocity
data association
double gate setting
Multiple Hypothesis Tracking
Extended Kalman Filter