Radio Map Building with IEEE 802.15.4 for Indoor Localization Applications

Noise Reduction for Radio Map Crowdsourcing Building in WLAN Indoor Localization System

10.21203/rs.3.rs-518323/v1 ◽

2021 ◽

Author(s):

liye zhang ◽

Zhuang Wang ◽

Xiaoliang Meng ◽

Chao Fang ◽

Cong Liu

Keyword(s):

Indoor Localization ◽

Sensor Data ◽

Mode Switching ◽

Map Building ◽

Position Information ◽

Localization Accuracy ◽

Localization System ◽

Straight Line ◽

Indoor Positioning System ◽

Radio Map

Abstract Recent years have witnessed a growing interest in using WLAN fingerprint-based method for indoor localization system because of its cost effectiveness and availability compared to other localization systems. In order to rapidly deploy WLAN indoor positioning system, the crowdsourcing method is applied to alternate the traditional deployment method. In this paper, we proposed a fast radio map building method utilizing the sensors inside the mobile device and the Multidimensional Scaling (MDS) method. The crowdsourcing method collects RSS and sensor data while the user is walking along a straight line and computes the position information using the sensor data. In order to reduces the noise in the location space of the radio map, the Short Term Fourier Transform (STFT) method is used to detect the usage mode switching to improve the step determination accuracy. When building a radio map, much fewer RSS values are needed using the crowdsourcing method compared to conventional methods, which lends greater influence to noises and erroneous measurements in RSS values. Accordingly, an imprecise radio map is built based on these imprecise RSS values. In order to acquire a smoother radio map and improve the localization accuracy, the MDS method is used to infer an optimal RSS value at each location by exploiting the correlation of RSS values at nearby locations. Experimental results show that the expected goal is achieved by the proposed method.

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Noise reduction for radio map crowdsourcing building in WLAN indoor localization system

EURASIP Journal on Advances in Signal Processing ◽

10.1186/s13634-021-00758-y ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Liye Zhang ◽

Zhuang Wang ◽

Xiaoliang Meng ◽

Chao Fang ◽

Cong Liu

Keyword(s):

Indoor Localization ◽

Sensor Data ◽

Mode Switching ◽

Map Building ◽

Position Information ◽

Localization Accuracy ◽

Localization System ◽

Straight Line ◽

Radio Map ◽

Localization Systems

AbstractRecent years have witnessed a growing interest in using WLAN fingerprint-based method for indoor localization system because of its cost-effectiveness and availability compared to other localization systems. In order to rapidly deploy WLAN indoor localization system, the crowdsourcing method is applied to alternate the traditional deployment method. In this paper, we proposed a fast radio map building method utilizing the sensors inside the mobile device and the Multidimensional Scaling (MDS) method. The crowdsourcing method collects RSS and sensor data while the user is walking along a straight line and computes the position information using the sensor data. In order to reduce the noise in the location space of the radio map, the short-term Fourier transform (STFT) method is used to detect the usage mode switching to improve the step determination accuracy. When building a radio map, much fewer RSS values are needed using the crowdsourcing method compared to conventional methods, which lends greater influence to noises and erroneous measurements in RSS values. Accordingly, an imprecise radio map is built based on these imprecise RSS values. In order to acquire a smoother radio map and improve the localization accuracy, the MDS method is used to infer an optimal RSS value at each location by exploiting the correlation of RSS values at nearby locations. Experimental results show that the expected goal is achieved by the proposed method.

Download Full-text