改进的衰减记忆UKF算法在伪距定位中的研究

Research on Improved Memory Attenuation UKF in Pseudo Ranges Positioning

研究伪距定位中衰减记忆无迹卡尔曼滤波(MAUKF)方法,针对衰减记忆UKF滤波器可能因衰减因子引入造成滤波精度降低、滤波收敛速度并没有得到改善的问题,本文依据预测残差的统计量,对衰减记忆UKF滤波算法进行了改进。仿真结果表明,该算法相比衰减记忆UKF算法提高了定位精度和收敛速度。

Researching the method of memory attenuation unscented Kalman filter （MAUKF） in pseudo ranges position. As the filter precision may be reduced due to the attenuation factor and the convergence rate of MAUKF don＇t enhance, we improved it based on the statistics of forecasting residual. The simulations reveal that the algorithm improves the position accuracy and convergence rate.