Improved Pedestrian Dead Reckoning Based on a Robust Adaptive Kalman Filter for Indoor Inertial Location System.

Qigao Fan,Pengsong Zhang,Hai Zhang,Xiangpeng Zhuang,Peng Pan,Jie Jia,Zhengqing Zhao,Yuanyuan Tang,Gaowen Zhu

doi:10.3390/s19020294

Qigao Fan, Pengsong Zhang + Show 7 more

Open Access

https://doi.org/10.3390/s19020294

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Abstract

Pedestrian dead reckoning (PDR) systems based on a microelectromechanical-inertial measurement unit (MEMS-IMU) providing advantages of full autonomy and strong anti-jamming performance are becoming a feasible choice for pedestrian indoor positioning. In order to realize the accurate positioning of pedestrians in a closed environment, an improved pedestrian dead reckoning algorithm, mainly including improved step estimation and heading estimation, is proposed in this paper. Firstly, the original signal is preprocessed using the wavelet denoising algorithm. Then, the multi-threshold method is proposed to ameliorate the step estimation algorithm. For heading estimation suffering from accumulated error and outliers, robust adaptive Kalman filter (RAKF) algorithm is proposed in this paper, and combined with complementary filter to improve positioning accuracy. Finally, an experimental platform with inertial sensors as the core is constructed. Experimental results show that positioning error is less than 2.5% of the total distance, which is ideal for accurate positioning of pedestrians in enclosed environment.

Highlights

Indoor positioning is a technology for positioning in an indoor environment, which shows great prospects in industries such as emergency rescue, logistics, wireless games and shopping malls [1,2,3].The Global Navigation Satellite System, such as the Global Positioning System (GPS), BeiDouNavigation Satellite System (BDS), and Global Navigation Satellite System (GLONASS), can provide absolute accurate positioning, but its performance in some enclosed environments, such as tunnels and mines, is not satisfied; as the Global Navigation Satellite System may suffer heavily from satellite signal blockage [4]
The Mti series Mechanical Systems (MEMS)-Inertial measurement unit (IMU) from Xsens is used in the experiment, which is fixed on the instep
The MEMS-IMU is mainly composed of a triaxle orthogonal accelerometer, a triaxle orthogonal magnetometer and a triaxle orthogonal gyroscope

Summary

Introduction

Indoor positioning is a technology for positioning in an indoor environment, which shows great prospects in industries such as emergency rescue, logistics, wireless games and shopping malls [1,2,3].The Global Navigation Satellite System, such as the Global Positioning System (GPS), BeiDouNavigation Satellite System (BDS), and Global Navigation Satellite System (GLONASS), can provide absolute accurate positioning, but its performance in some enclosed environments, such as tunnels and mines, is not satisfied; as the Global Navigation Satellite System may suffer heavily from satellite signal blockage [4]. How to obtain accurate position information of indoor objects has attracted wide attention. Indoor positioning methods have been proposed, including Ultra. Wideband (UWB) [5], ZigBee [6], Wi-Fi [7], Bluetooth [8], Radio Frequency Identification (RFID) [9], and visual positioning [10]. Performances of these positioning methods are affected by external environment. UWB positioning is susceptible to non-line-of-sight interference such as occlusion, external collision and strong magnetic field interference [11].

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