摘要
考虑到毫米波雷达在噪声源较多的战场上存在较大的测量误差,为了提高毫米波雷达在坦克防撞系统中采集数据的可靠性,提出了用交互式多模型卡尔曼滤波算法对坦克前方机动车辆进行准确的目标跟踪。该算法运用不同机动模型的卡尔曼滤波器进行并行处理,以模型匹配似然函数为基础更新模型概率,并组合所有滤波器的修正后的状态估计值以得到状态估计。仿真结果表明,该算法能够有效的跟踪坦克前方行驶的车辆,获悉其距离、速度等信息,具有跟踪精度高的特点,降低了虚警率。
Considering the millimeter wave radar existing more measurement errors because of noise interference on the battlefield,in order to make the data of millimeter wave radar more reliable in the tank in anti-collision system,and use the Kalman filter algorithm to track the near goal in front of tanks.The algorithm uses different dynamic model of Kalman filter for parallel processing,thus realize the parallel filtering and update probability of the model on the basis of matching likelihood function,and combines with all filter to obtain state estimation.The algorithm can effectively track the chariot in front of the tank,acquire of the distance,speed and other information.It has the characteristics of high precision,and reduce the false alarm rate.
出处
《电子测量技术》
2016年第8期43-47,共5页
Electronic Measurement Technology
关键词
交互多模型
坦克
毫米波雷达
雷达组网
目标跟踪
interacting multiple model（IMM）
tank
millimeter wave radar
radar netting
target detection
