摘要
提出了在三维空间中引入径向速度的非线性卡尔曼滤波算法.先将观测数据从三维极坐标转换成直角坐标,然后将径向速度和状态变量之间的非线性方程在预测值处利用泰勒级数展开,得到其一阶近似的线性方程,最后用标准卡尔曼滤波算法进行滤波.仿真结果表明,当引入径向速度时,相对于只有目标的位置观测来说其收敛速度加快,均方误差减小,提高了跟踪性能.
Based on three-dimensional space, a new method for the nonlinear Kalman filter using the radial velocity is presented. The polar coordinates which where observed are converted to the rectilinear coordinates first. Then the nonlinear function of the radial velocity is expanded in a Taylor series around the predicted state estimate. So the standard Kalman filter can be used. Simulation results show that the evaluated error is decreased and the convergent velocity is accelerated when the radial velocity is introduced.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2005年第5期667-670,共4页
Journal of Xidian University
基金
"十五"国家预研资助项目(413070101)