摘要
当实际数据出现突变时,基于最小二乘、扩展卡尔曼滤波的GPS定位解算存在定位结果精度低和稳定性差的问题。提出一种自适应渐消扩展卡尔曼滤波算法,通过自适应渐消迭代系统噪声协方差,来实现抑制数据突变影响。试验结果表明:该算法相比最小二乘、扩展卡尔曼滤波,其定位精度有所提高;相比传统渐消扩展卡尔曼滤波,其收敛速度、稳定性有所提高。
In GPS positioning computation,when the actual data is changed,the Least Squares,the Extended Kalman Filter positioning results have low precision and poor stability problems. This paper proposes an Adaptive Fading Extended Kalman Filtering algorithm,through adaptive iterative system noise covariance,the modification to achieve less data mutation.Experimental results show that the algorithm is compared with the Least Squares,the Extended Kalman Filter,the positioning accuracy is improved.Compared with the traditional Fading Extended Kalman Filter,its convergence speed and stability are improved.
出处
《火力与指挥控制》
CSCD
北大核心
2016年第3期177-182,共6页
Fire Control & Command Control
基金
江西省自然科学基金(20142BAB207001)
江西省教育厅科学技术基金资助项目(GJJ14369)
