基于噪声顺序解相关的两阶段Kalman滤波融合

针对传统两阶段Kalman滤波只能处理单一或部分复杂噪声情形,在充分考虑多雷达跟踪系统的误差噪声有色建模和四类噪声相关性建模基础上,建立一种基于噪声顺序解相关的两阶段Kalman滤波融合算法。首先给出能有效避免噪声相关性耦合化的噪声解相关顺序,进而应用等价变换技术来获得有色噪声、过程噪声和测量噪声三者间不相关的目标跟踪融合模型,最后应用平方根分解和单位下三角阵求逆技术来实现多雷达量测噪声相关系统的集中式Kalman滤波融合,并通过4个仿真实验验证了该算法对复杂噪声情形的有效性和高精度。

Two Stage Kalman Filter Fusion Based on Sequential Decorrelation of Noise

Aimed at the problem that the traditional two stage Kalman filtering can only deal with single or part of complex noises, a two stage Kalman filtering fusion algorithm based on sequential de correlation of noise is proposed in full consideration of the modeling of colored noise and four kinds of noise correlation in multi radar tracking system. First, this paper is to give the order of noise de correlation which can effectively avoid the coupling of noise correlation, and then to obtain a target tracking fusion model uncorrelated among the colored noise, the process noise and the measurement noise by using the equivalent transformation technology. Finally, the centralized Kalman filtering fusion of multi radar measurement noise correlation system is realized by using the square root decomposition and the unit lower triangular matrix inversion technology.