摘要
采用一种改进的K NN算法对多雷达观测数据进行聚类 ,结合聚类中心和目标预测值 ,应用卡尔曼滤波器估计目标状态 ,从而实现多雷达数据融合。实验结果表明这种方法是有效的。
This paper uses the improved K-nearest neighbor algorithm to cluster the observed data from multiradars,and integrates the centers of the clusters with premeasurements,then estimates the state of tragets with the Kalman filter to realize the multiradar data fusion. The result of the experimentation shows that the mathod is effective.
出处
《雷达与对抗》
2002年第2期5-10,共6页
Radar & ECM
关键词
观测值
聚类
雷达
数据融合
卡尔曼滤波
K-NN算法
multiradar data fusion
K-nearest neighbor algorithm
clustering
Kalman filtering
