An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

Analysis of coordinate time series of DORIS stations on Eurasian plate and the plate motion based on SSA and FFT

This study focuses on analyzing the time series of DORIS beacon stations and plate motion of the Eurasian plate by applying Singular Spectrum Analysis(SSA)and Fast Fourier Transform(FFT).First,the rend terms and periodic signals are accurately separated by SSA,then,the periodic seasonal signals are detected using SSA,and finally,the main components of the time series are reconstructed successfully.The test results show that the nonlinear trends and seasonal signals of DORIS stations are detected successfully.The periods of the seasonal signals detected are year,half-year,and 59 days,etc.The contribution rates and slopes in E,N,and U directions of the trend items of each beacon station after reconstruction are obtained by least-square fitting.The velocities of these stations are compared with those provided by the GEODVEL2010 model,and it is found that they are in good agreement except the DIOB,MANB,and PDMB stations.Based on the DORIS coordinate time series,the velocity field on the Eurasian plate is constructed,and the test shows that the Eurasian plate moves eastward as a whole with an average velocity of 24.19±0.11 mm/y in the horizontal direction,and the average velocity of it is1.74±0.07 mm/y in the vertical direction.

Polar motion prediction using the combination of SSA and ARMA

High-precision polar motion(PM) prediction is of important significance in astronomy, geodesy, aviation,hydrographic mapping, interstellar navigation, and so on. SSA can effectively extract the trend and period terms of PM,in the process of achieving high-precision medium-and long-term polar motion prediction,it is necessary to solve the end effect problem and overfitting problem of SSA forecasting method;therefore, ARMA was applied to decreasethe end effect, and a suitable combination of reconstructed components was determined to avoid the high variance reaction of SSA overfitting. Based on the decomposition and reconstruction of the PM by SSA, the reconstructed components are determined to participate in the SSA iterative fitting model according to the variance contribution rate. The combination of the reconstructed components representing the polar motion period term and the trend term is determined according to the correlation analysis of the selected reconstructed components. After the above work, the principal component prediction sequence is obtained by fitting the period term and the trend term to convergence, respectively, and then, the SSA end effect is modified, and the residual term is predicted based on ARMA. The test results show that he prediction accuracy of SSA + ARMA at the front of the X and Y directions are improved by 96.90% and 97.53% compared with those of SSA, respectively,and the forecast accuracy of 365 days are improved by 37.93% and 19.53% in the X and Y directions compared with those of Bulletin A, respectively.