改进无色卡尔曼滤波算法在GPS系统中的应用

Application of Modified Unscented Kalman Filter Algorithm in GPS System

基于无色卡尔曼滤波算法在GPS卫星定位系统中的应用,提出了GPS卫星定位系统中的改进无色卡尔曼滤波算法。该算法在迭代一定次数后引入遗忘因子,根据误差协方差矩阵自适应调整无色卡尔曼滤波算法中的过程噪声方差矩阵,以提高模型的准确度。通过采集大量实测数据的仿真测试结果表明,改进无色卡尔曼滤波算法在定位精度上较无色卡尔曼滤波算法大幅提高,表明其对于精确定位有更加重要的意义和更为广阔的应用前景。

The modified Unscented Kalman Filter algorithm was proposed based on UKF algorithm used in GPS systems. The proposed algorithm improves the accuracy of the model by using a forgetting factor to adaptively adjust the process noise covariance matrix according to the error covariance matrix in UKF algorithm after some iterations. The employment of the proposed algorithm on the real satellite data shows its significant improvements on the position precision over the UKF algorithm, indicating its greater significance and broader coverage of applications in precise positioning systems.