Research On Non-line-of-sight Errors In Complex Enverionment

With the advent of the information age,the rapid integration of communication and navigation services,location services in national defense security,economic construction,social life has become an indispensable part.Indoor positioning is also in the emergency rescue,special crowd monitoring,personal location services and management of large venues,etc.has broad application prospects.However,due to the complexity of the indoor environment,there are often obstacles between the transceiver equipment,which leads to the signal can only be reflected,diffraction and other ways to reach the user terminal,the signal occurred non-line-of-sight propagation,the resulting non-line-of-sight error also has a great impact on the positioning accuracy.Therefore,it is imminent to improve the location accuracy by reducing the non-line-of-sight error in the positioning process to meet the demand for location services.In this paper,the non-line-of-sight error distribution in complex indoor environment is studied for the problem of location accuracy due to the non-line-of-sight error in the indoor positioning process.By establishing the spatial multi-dimensional path loss model and the fitting non-line-of-sight error analysis model,the indoor signal distribution and the non-line-of-sight error value can be calculated.So as to eliminate the non-line-of-sight error in the positioning process,improve the positioning accuracy and enhance the operation speed.In this paper,the main contribution and innovation are as follows:(1)The signal energy loss under non-line-of-sight propagation is different from the energy loss of the line-of-sight propagation signal.Therefore,it can be indirectly judged whether the NLOS propagation is included by predicting the signal energy distribution.However the existing signal loss models are relatively unilateral in consideration of the influence factors,so the calculated signal strength values have large errors.In this paper,based on the Matne-Magna model,through the analysis of the loss degree of various factors on the signal energy,and by using the statistical analysis of multidimensional error signal attenuation distribution,we establish a multi-dimensional space path loss model.The comparison shows that the precision of the energy loss of the predicted signal is 19%higher than that of the Matne-Marne model in the same complex environment.(2)Because of the complexity and diversity of the indoor environment,the distribution of non-line-of-sight errors in different environments is different,and a certain formula can not be used to describe the distribution of non-line-of-sight errors in different environments.In this paper,we establish the non-line-of-sight error analysis model based on fitting by simulating the propagation path of the signal and analyzing the propagation degree of the signal.Thereby we calculate the indoor non-line-of-sight error distribution by the non-line-of-sight error analysis model based on fitting.The non-line-of-sight error value of any position in space is calculated by least squares fitting,which reduces the complexity of the analysis model and improves the prediction accuracy of non-line-of-sight error.Verified by testing,the accuracy of the non-line-of-sight error is less than 0.24 m by using the non-line-of-sight error analysis model,which has good prediction effect.The root mean square error of the non-line-of-sight error by fitting is only 7.031e-09,which can be shown that this method can better fit the non-line-of-sight error.In this paper,the method is applied to the localization,the positioning accuracy is 0.96m,compared with the quadratic linear programming algorithm based on the Taylor series expansion algorithm,the minimum weighted quadratic positioning technique based on the maximum likelihood estimation algorithm,and the improved Kalman filter algorithm Ratio,positioning accuracy and operation speed are improved.