摘要
SRUKF能够解决UKF在滤波过程中由于噪声和计算误差导致的误差协方差阵负定的问题,但也付出了增加运算量的代价。以多机编队对地面辐射源进行无源定位跟踪为应用背景,提出了一种改进的SRUKF算法。该算法采用比例修正的最小偏度单形采样策略,减少采样点的同时又能基本保持算法精度;借鉴简化UKF的思想,针对此应用背景下的线性化状态方程,对状态和状态误差协方差平方根的一步预测采用KF进行递推,从而进一步降低运算量。仿真结果表明,相对于采用比例对称采样的标准SRUKF算法,文中所提算法不但能够保持计算精度,而且减小了运算量,具有一定的工程实用意义。
The problem of non positive error covariance matrix in UKF algorithm caused by measurement errors and computational errors can be solved by SRUKF at the price of increasing the computation. An improved SRUKF algorithm is proposed in this paper, with multi-plane passively locating and tracking a target on the ground as the application background. The scaled minimal skew simplex sampling strategy is applied in the proposed algorithm, so that the number of sampled particles is reduced with the calculation precision almost kept. Borrowing the idea of the simplified UKF, the proposed algorithm uses KF to predict the state and the square-root of state error covariance in the linear state equation, and the computational complexity is further reduced. Simulation results indicate that the proposed algorithm not only keep the calculation precision but also reduces the computational complexity when compared to the standard SRUKF using the scaled symmetric sampling strategy. As a result, it has some engineering significance.
出处
《雷达科学与技术》
2012年第5期492-496,共5页
Radar Science and Technology
基金
航空科学基金(No.20105584004)
