Research On Data Denoising And Fusion Technology Of Consumer Sensor For Human Inertial Navigation System

With the rapid development of science and technology and the change of lifestyle,people's request for location information is becoming higher.In the indoor environment,the Global Navigation Satellite System(GNSS)signal will be attenuated due to the obstruction of buildings and other factors,which makes it difficult for GNSS to meet the needs of indoor positioning.Therefore,numerous indoor positioning solutions emerge one after another,among which the indoor positioning and tracking technology based on Pedestrian Dead Reckoning(PDR)demonstrates a broad development prospect for it does not rely on external facilities and is completely autonomous.With the development of Micro-Electro-Mechanical System(MEMS),inertial sensors based on MEMS technology are increasingly applied to PDR-based inertial positioning systems.How to improve the accuracy and reliability of the inertial positioning system without changing the manufacturing process has become a concerned topic in the field.Based on PDR technology,this paper studies the gyro denoising technology of consumer MEMS sensor and the design and implementation of pedestrian indoor positioning system based on information fusion.This paper mainly includes the following contents:(1)Research on MEMS gyroscope signal denoising algorithm.Gyroscope is a key component that affects the accuracy of MEMS sensor.Therefore,it is of great significance to improve the accuracy of MEMS gyroscope for the research of inertial positioning and navigation.In this paper,the composition of MEMS gyro random noise is studied and verified via Allan analysis.In addition,on the basis of studying several non-stationary and nonlinear signal denoising algorithms,this paper proposes an optimized de-noising algorithm called EEMD-M,and verifies its denoising effect with test signals and measured data.(2)Research on multi-sensor information fusion technology.Based on the research of several common information fusion algorithms,this paper proposes an information fusion algorithm based on support degree and adaptive weight allocation,for the common algorithm does not take the influence of sensor observation on weight coefficient into consideration.Besides,the fusion algorithm is applied to the human indoor positioning system.(3)Research and implementation of indoor positioning and tracking system based on PDR technology.This paper designs and implements a human indoor positioning system,which combines classical inertial navigation framework and multi-sensor information fusion technology.The system is based on the platform of Matlab and a sensor platform which is integrated with multi-inertial measurement unit(IMU).The system achieves the data acquisition,information fusion and data processing of the framework proposed in this paper.Moreover,the effectiveness of the information fusion technology and the positioning performance of the system are verified through the experiment in the indoor environment,which verifies the practical value of the system presented in this paper.