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Improving the Accuracy of GPS Positioning with an Exponential Stochastic Model

机译:用指数随机模型提高GPS定位精度

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摘要

Due to the difference of received satelliteȁ9;s observational error distributions relative to the receiver in satellite positioning, the least square estimation is not the best linear unbiased estimation and this causes bias in positioning result. The weight least square method is adopted in order to satisfy the best linear unbiased estimation and improve positioning accuracy. Weight factor model was constituted which has exponential relation to the signal intensity of received satellites. The coefficient of the exponential model was determined through actual test of the received data. In this study, the positioning accuracy of the weight algorithm with the exponential model was analyzed. Results show that the positioning bias is 27.51% of no weight positioning algorithm in max bias measure and the computation of positioning algorithm has almost no increase.
机译:由于在卫星定位中接收到的卫星the9相对于接收机的观测误差分布的差异,最小二乘估计不是最佳的线性无偏估计,这会导致定位结果出现偏差。为了满足最佳线性无偏估计并提高定位精度,采用了加权最小二乘法。建立了权重模型,该模型与接收卫星的信号强度成指数关系。指数模型的系数是通过对接收到的数据进行实际测试确定的。在这项研究中,分析了加权算法与指数模型的定位精度。结果表明,在最大偏差量度下,定位偏差为无权定位算法的27.51%,定位算法的计算量几乎没有增加。

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