| Error accumulation is a thorny problem affecting the accuracy of inertia l navigation system.In the process of navigation calculation,the tiny errors of inertia l devices will accumulate rapidly in the form of the three power.Because of the diversit y and complexity of inertial device errors,it is impossible to accurately model and process the errors one time.At the same time,the existing error correction technology has the problems of poor stability and low direction accuracy,which leads to the existing inertial navigation devices still unable to be widely used in indoor positioning.In this paper,the velocity,position and attitude formula of Inertial Navigatio n System(INS)are derived,and the inertial navigation error is analyzed,then the error is corrected.Combining with the characteristics of Ultra Wide Band(UWB)location and known map information,an indoor location system based on UWB/MEMS-INS and electronic map is proposed.The location system adopts zoning design: In the UWB range of sight,the extended kalman filter is used to combine UWB/MEMS-INS;In UWB non line of sight region,an indoor map matching algorithm model based on conditional random field is constructed,and Indoor 3D positioning is realized.The main contents of this paper include the following points:1.Inertial error analysis and suppression: The main errors of inertial navigatio n system are analyzed and summarized.According to the different characteristics of these errors,the corresponding error correction algorithm is designed.Gyroscopic drift and zero speed correction technology are used to correct the errors and verify the error correction algorithm,which proves the effectiveness of the algorithm.2.Indoor Navigation Based on UWB/MEMS-INS: Combined with different indoor environment,an indoor location system based on UWB/MEMS-INS is proposed.Firstly,the indoor map is analyzed,and the location of the base station and the range of sight are determined.Secondly,a partition based method to judge the effective ness of the UWB signal is studied,and the design scheme of the sight distance region system is determined: the information of the two is fused by the extended Kalman filter.The experimental results show that the integrated navigation system fits the trajectory of pedestrians very wel,and the system performs well in different regions.3.Two-dimensional map matching algorithm based on conditional random field: In the UWB non-visual range,in order to improve the positioning accuracy of inertial navigation system,a map matching algorithm based on conditional random fields is designed.Firstly,according to the design of electronic map,the state point should be evenly distributed in the indoor area.Secondly,the two-dimensional location observation point is extracted by threshold method,and the characteristic equation is established by combining the location information of the observation points and the position information of the corresponding state points.Then,the characteristic equation is replaced by the conditional random field model,and the location of the maximum probability of pedestrians is solved.Finally,the algorithm is verified based on the measured data.The experimental results show that the map matching algorithm based on conditional random fields is highly applicable and stable.4.Three-dimensional map matching algorithm based on conditional random field: In the UWB non-visual range,high information divergence is serious.In order to achieve high-precision Indoor 3D positioning,a 3D map matching method based on conditional random fields is proposed.First,according to step information,the height state point is designed,so that each step has its corresponding state point.Secondly,the zero velocity detection algorithm is used to extract the height observation points and match the heights.Then,the height and two-dimensional position information can be acquired,and the location information can be fused by the time distance between them.Finally,the algorithm model is applied to the indoor 3D navigation system.The experimental results show that the 3D map matching algorithm based on conditiona l random field is a good method to estimate the three-dimensional path of pedestrian walking. |
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