改进的“最近邻”航迹相关算法研究

Research into Improved Nearest Neighbor Track Correlation Algorithm

从经典算法的改造出发,提出了改进的"最近邻"算法。传统的"最近邻"算法利用了Kalman等滤波算法中目标位置信息的预测值进行相关,而改进算法借用了"最近邻"算法的基本原理,利用了雷达回波参数的径向多普勒速度信息,对目标下一时刻的位置进行预测,然后进行相关处理。通过仿真对两种算法进行了比较,仿真结果表明该算法处理结果明显优于传统的"最近邻"算法。

This paper proposes an improved nearest neighbor algorithm based on the makeover of the classical algorithm. The classical NN algorithm uses the predicted information of the target position of Kalman filters for correlation. The improved NN uses the Doppler radical velocity to predict the next position of the target precisely. The two algorithms are compared by simulation, which shows that the improved one is better than the classical one in data processing.