| 推广的遗忘因子递推最小二乘算法在GPS中的应用 |
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| 引用本文： | 袁代林,朱允民,马洪.推广的遗忘因子递推最小二乘算法在GPS中的应用[J].四川大学学报(自然科学版),2002,39(4):595-601. |
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| 作者姓名： | 袁代林 朱允民 马洪 |
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| 作者单位： | 四川大学数学学院,成都,610064 |
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| 摘 要： | 作者将推广的遗忘因子递推最小二乘算法应用到GPS以确定动态目标的轨迹，并与推广的Kalman滤波进行比较，发现两种算法在GPS中具有各自的优点，当噪声相关性较大又不能准确地得到其方差时，推广的遗忘因子递推最小二乘算法好于推广的Kalman滤波算法。
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| 关 键 词： | 全球定位系统 GPS Kalman滤波算子 遗忘因子递推最小二乘算法 目标轨迹 估计误差 |
| 文章编号： | 0490-6756(2002)04-0595-07 |
Application of the Extented Forgetting Factor Recursive Least Squares Estimator to GPS |
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| YUAN Dai lin,ZHU Yun min,MA Hong.Application of the Extented Forgetting Factor Recursive Least Squares Estimator to GPS[J].Journal of Sichuan University (Natural Science Edition),2002,39(4):595-601. |
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| Authors: | YUAN Dai lin ZHU Yun min MA Hong |
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| Abstract: | The authors apply the algorithm of the extended forgetting factor recursive least squares estimator to GPS,so as to track a motive object.And compare it with the extended Kalman filtering,find that the algorithms both have their advantages respctively.If the noises are time correlated and the authors can't acquire the variance of noises accurately,the extended forgetting factor recursive least squares estimator will perform better than the extended Kalman filtering. |
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| Keywords: | GPS EKF EFRLS |
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