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GPS/Cellular Network Hybrid Positioning Method Based on Two Scatter Model

机译:基于两个散射模型的GPS /蜂窝网络混合定位方法

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Cellular network has low accuracy and GPS in complex environment has insufficient information, aiming at the irresistible detects in respective positioning system, present combined positioning method based on the GPS and cellular network, to improve the availability of the positioning, and improve the positioning accuracy. And the main factor of current effect on GPS / cellular hybrid positioning is non-line-of-sight propagation ( NLOS ). In this paper, based on the two scatter model inhibition of NLOS propagation effect, the idea is to transformed the NLOS error into a deterministic model factors, so the precision is mainly depends on the orientation of the measuring accuracy of the parameters and unrelated to non direct wave caused by parameter deviation, take scatter as a virtual base station, inhibition of cellular NLOS error, and auxiliary GPS positioning, to improve the dilution of position ( DOP ), namely in the GPS blind auxiliary positioning, further improving GPS / cellular hybrid positioning accuracy. Through the static, movement, ROS model, Gauss noise propagation environment, and use of error cumulative density function and RMSE to evaluate algorithm for hybrid positioning in this paper, the result has higher accuracy and stronger robustness.
机译:蜂窝网络精度低,复杂环境下的GPS信息不足,针对各个定位系统中难以抗拒的检测,提出了一种基于GPS和蜂窝网络的组合定位方法,以提高定位的可用性,提高定位精度。当前影响GPS /蜂窝混合定位的主要因素是非视距传播(NLOS)。本文基于对NLOS传播效应的两种散射模型抑制,将NLOS误差转化为确定性模型因素,因此精度主要取决于参数测量精度的方向,与非测量参数无关。由参数偏差引起的直接波,以散射为虚拟基站,抑制蜂窝NLOS误差,并辅助GPS定位,以提高位置稀释度(DOP),即在GPS盲辅助定位中,进一步改善GPS /蜂窝混合定位精度。通过静态,运动,ROS模型,高斯噪声传播环境,并利用误差累积密度函数和RMSE对混合定位算法进行评估,结果具有较高的准确性和较强的鲁棒性。

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