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首页> 外文期刊>Journal of Residuals Science & Technology >Research on Beidou Positioning System Based on Improved Kalman Filtering Algorithm
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Research on Beidou Positioning System Based on Improved Kalman Filtering Algorithm

机译：基于改进卡尔曼滤波算法的北斗定位系统研究

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For the low positioning accuracy of Direct Calculation (DC), the massive iterations of Weighted Least Squares algorithm (WLS), and the over sensitivity to the initial position of Kalman filtering iterative algorithm, we compute the receiver position by WLS combined with improved Kalman filtering algorithm(IKF) based on Beidou satellite signals. This algorithm firstly uses Weighted Least Squares iterative algorithm to locate the initial position and then the improved Kalman algorithm to perform filtering. The experimental results and simulation show that compared with Weighted Least Squares iterative algorithm and Kalman filtering algorithm, the positioning accuracy is increased greatly by this algorithm under the condition of the same number of iterations, which has important significance to accelerate the civilian process of BeiDou navigation
机译：由于直接计算（DC）的定位精度低，加权最小二乘算法（WLS）的大量迭代以及对卡尔曼滤波迭代算法初始位置的过度敏感，我们结合WLS和改进的卡尔曼滤波来计算接收器位置北斗卫星信号的算法（IKF）。该算法首先使用加权最小二乘迭代算法定位初始位置，然后使用改进的卡尔曼算法进行滤波。实验结果和仿真结果表明，与加权最小二乘迭代算法和卡尔曼滤波算法相比，在相同迭代次数的情况下，该算法的定位精度大大提高，对于加快北斗导航民航过程具有重要意义。

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