Abstract

The radio map construction is usually time-consuming and labor-sensitive in indoor fingerprinting localization. We propose a fast construction method by using an adaptive path loss model interpolation. Received signal strength (RSS) fingerprints are collected at sparse reference points by using multiple smartphones based on crowdsourcing. Then, the path loss model of an access point (AP) can be built with several reference points by the least squares method in a small area. Afterwards, the RSS value can be calculated based on the constructed model and corresponding AP’s location. In the small area, all models of detectable APs can be built. The corresponding RSS values can be estimated at each interpolated point for forming the interpolated fingerprints considering RSS loss, RSS noise and RSS threshold. Through combining all interpolated and sparse reference fingerprints, the radio map of the whole area can be obtained. Experiments are conducted in corridors with a length of 211 m. To evaluate the performance of RSS estimation and positioning accuracy, inverse distance weighted and Kriging interpolation methods are introduced for comparing with the proposed method. Experimental results show that our proposed method can achieve the same positioning accuracy as complete manual radio map even with the interval of 9.6 m, reducing 85% efforts and time of construction.

Highlights

  • The indoor positioning technology attracts extensive attentions of researchers to carry out immense amounts of studies and develop corresponding localization systems, such as Wi-Fi, Bluetooth, pedestrian dead reckoning (PDR/DR), radio frequency identity (RFID), infrared, ultrasonic, Zigbee, magnetic field, visible light, computer vision, and pseudolites [1]

  • The fingerprinting method based on received signal strength (RSS) may be the most widely used technique, which is suitable for both Wi-Fi and Bluetooth with low-cost and highly accessible devices

  • We propose a method of radio map construction by using crowdsourcing, path loss model and interpolation methods, which can greatly reduce the workload and time of radio map construction and ensure the same positioning accuracy as the complete manual radio map

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Summary

Introduction

The indoor positioning technology attracts extensive attentions of researchers to carry out immense amounts of studies and develop corresponding localization systems, such as Wi-Fi, Bluetooth, pedestrian dead reckoning (PDR/DR), radio frequency identity (RFID), infrared, ultrasonic, Zigbee, magnetic field, visible light, computer vision, and pseudolites [1]. The fingerprinting method based on received signal strength (RSS) may be the most widely used technique, which is suitable for both Wi-Fi and Bluetooth with low-cost and highly accessible devices. It is applied with cellular, RFID or ZigBee signals [2]. The main work is to collect RSS fingerprints for constructing a radio map (RM) and yield the mapping relationship between signal fingerprints and spatial positions. The basic idea of the tracking step is to estimate pending location by matching RSS collection with the aforementioned radio map.

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