摘要
针对当前单目标跟踪数据融合中存在的迭代求解计算量大,难以满足实时计算要求的问题,提出了一种将模糊数学和非负特征向量理论相结合的数据融合算法。该方法克服了卡尔曼滤波法、最小二乘法需要建立统一的测量方程,进行迭代求解、计算量大的问题。与传统方法相比,该方法能充分利用测量数据,提高目标跟踪精度,计算简便,便于工程实现。
Aiming at the existing problem of single-target tracking in real-time data processing at present, the method of Data Fusion algorithms based on fuzzy mathematics is discussed. The weight of equipment can be calculated based on the theory of probability source combination and characteristic vector of non-negative matrix. The modified algorithm can restrain bad influences of outliers and improve the tracking accuracy and decrease the computational complexity of minimum mean-square value algorithm and the Kalman filtering algorithm.
出处
《指挥控制与仿真》
2009年第1期65-66,69,共3页
Command Control & Simulation
关键词
数据融合
数据处理
模糊数学
data fusion
data processing
fuzzy mathematics
