Research And Implemention Of Indoor Location System Based On Information Flexible Fusion

With the rapid development of the mobile Internet industry,people demand for indoor location increasingly urgent,as the most important part of Location Based Service,indoor location technology gradually more and more business concerns.Due to the progress of technology,people especially need accurate indoor location.However,due to the reflection and multipath propagation of indoor environment,high-precision indoor location problem has been the biggest problem in the field of positioning.Based on information flexible fusion technology,the paper mainly studies how to get good indoor location results in complex indoor environment.The main work of this paper is as follows:(1)This paper summarizes the research status and analyzes the advantages and disadvantages of various indoor positioning technology and technical difficulties.Based on the Cramer-Rao Low Bound(CRLB),the limit of TOA algorithm is analyzed,and the CRLB when the noise characteristics of the base station are inconsistent is deduced.To solve the bottleneck of improving indoor positioning accuracy,the framework and structure of indoor positioning system based on information flexible fusion are designed.(2)For the data fusion algorithm of information flexible fusion,the problem of location parameter estimation and multi-location parameter fusion is studied respectively under single/multi-sensor condition.Based on this,a new type of indoor accurate positioning method based on RSSI/AOA is proposed.The simulation and test results show that the proposed algorithm can effectively filter out the noise of the positioning result caused by the measurement fluctuation and effectively improve the target's location accuracy in the complicated environment.(3)A decision layer fusion algorithm based on strong tracking Kalman filter is established.The al algorithm solved the Kalman filter's shortcomings in moving target positioning and tracking: the ability of tracking the mutation state is poor,and the large noise filtering ability is weak.It improved the suboptimal fading factor of strong tracking algorithm,based on the previous results of strong tracking results,then feedback the strong tracking results,thus forming the fusion tracking algorithm based on strong tracking filter based on exponent fading factor(EFF-STF).The realization of the algorithm is presented,and through test we verified the algorithm's performance.The tracking performance of the algorithm under random noise is verified by comparing with Kalman filter.Through the CDF figure of the position error of before and after tracking,the good tracking performance of the algorithm for correction positioning error is confirmed.(4)In this paper,the indoor positioning system based on low energy Bluetooth is realized by MATLAB and VS2010.The positioning results are visualized and the performance of the algorithm is verified.The experimental results show that after information flexible fusion,over eighty-five percent of the positioning error constraints within 1m.This algorithm achieves the aim that we can obtain indoor real-time precise positioning.