摘要
针对最小二乘迭代法定位精度不高和卡尔曼滤波迭代收敛次数较多并对初始位置过于敏感的缺点,采用最小二乘迭代法和改进的卡尔曼滤波相结合的模型方法,该算法先用最小二乘迭代法对初始位置进行定位,再用改进的卡尔曼法进行滤波,仿真结果表明,该算法与最小二乘迭代法、卡尔曼滤波法、最小二乘和卡尔曼滤波结合等现有算法相比,其迭代5次达到收敛,迭代次数最少,且定位精度提高了60%。该算法可在北斗伪距定位上进行应用,可用于导航定位、也可用于网络RTK初始位置的定位。
The least square iteration method has lower positioning accuracy,and Kalman filter has more much iteration number and high sensitivity to the initial position. Aiming at these defects,the method of least square iteration combined with improved Kalman filter is proposed. The algorithm uses the least square iteration method to locate the initial position,and then the improved Kalman filter is used for filtering. The simulation result shows that,comparing with the least square iteration method,the method of least square iteration combined with improved Kalman filter brings about convergence with 5 iterations,the number of iteration is the least,and the positioning accuracy is increased by 60%. The proposed method can be applied to Beidou pseudo ranges positioning,the global positioning system and the initial position of the network RTK.
出处
《电子测量与仪器学报》
CSCD
北大核心
2016年第5期779-785,共7页
Journal of Electronic Measurement and Instrumentation
基金
合肥市北斗卫星导航重大应用示范资助项目
