Adaptive Mobility Mapping for People Tracking Using Unlabelled Wi-Fi Shotgun Reads

Qiu

et al. 2015

Entropy

Self Cite

Abstract:In this paper, we proposed a novel information-based approach to precision analysis of indoor wireless local area network (WLAN) localization using location fingerprint. First of all, by using the Fisher information matrix (FIM), we derive the fundamental limit of WLAN fingerprint-based localization precision considering different signal distributions in characterizing the variation of received signal strengths (RSSs) in the target environment. After that, we explore the relationship between the localization precision and access point (AP) placement, which can provide valuable suggestions for the design of the highly-precise localization system. Second, we adopt the heuristic simulated annealing (SA) algorithm to optimize the AP locations for the sake of approaching the fundamental limit of localization precision. Finally, the extensive simulations and experiments are conducted in both regular line-of-sight (LOS) and irregular non-line-of-sight (NLOS) environments to demonstrate that the proposed approach can not only effectively improve the WLAN fingerprint-based localization precision, but also reduce the time overhead.

Section: Introductionmentioning

confidence: 99%

An Information-Based Approach to Precision Analysis of Indoor WLAN Localization Using Location Fingerprint

Qiu

et al. 2015

Entropy

Self Cite

“…Nowadays, people spend much of the time in the indoor environment, where the Global Positioning System (GPS) signal is difficult to be received. In the meantime, with the rapid development of Wireless Local Area Network (WLAN) technique, the WLAN Received Signal Strength (RSS) based indoor localization has attracted serious attention [1][2][3][4][5]. There are generally two phases involved in RSS based WLAN indoor localization, namely the off-line phase and on-line phase.…”

Section: Introductionmentioning

confidence: 99%

IMLours: Indoor mapping and localization using time-stamped WLAN received signal strength

Zhang

2015 IEEE Wireless Communications and Networking Conference (WCNC)

et al. 2015

Self Cite

In the area of Wireless Local Area Network (WLAN) based indoor localization, the Received Signal Strength (RSS) fingerprinting based localization technique has been studied extensively. Site survey phase in RSS fingerprinting is always considered to be time-consuming and labor intensive. To solve this problem, we propose a novel Indoor Mapping and Localization !Ising RSS~olely (IMLours) approach, which utilizes the spectral clustered time-stamped WLAN RSS data to characterize environmental layout, as well as conduct target localization. First of all, we use the off-the-shelf smartphones to sporadically record a batch of WLAN RSS data in indoor environment. Second, spectral clustering is applied to classify the RSS data in each sequence into different clusters. The clusters are then used to construct the logic graphs. Third, we do the mapping from logic graphs into ground-truth graph. Finally, based on the extensive experiments conducted in a real WLAN indoor environment, our proposed IMLours approach is proved to achieve satisfactory localization accuracy.

“…Location tracking in wireless mobile environments plays an important role in recent development of Location-based services (LBSs), such as visitor navigation, elderly health care, facility management, transportation, and emergency rescue [1][2][3]. With the significant growing interests in Wi-Fi technology and the ubiquitous deployment of Wi-Fi infrastructures, intense attention has been paid to various approaches of Wi-Fi network aided location tracking [4]. Location tracking using Wi-Fi received signal strength (RSS) fingerprints presents many challenges due to less predictable variations of RSSs with respect to the distances from the access points (APs) to the receiver.…”

Section: Introductionmentioning

confidence: 99%

Crowd-Sourced Mobility Mapping for Location Tracking Using Unlabeled Wi-Fi Simultaneous Localization and Mapping

Mobile Information Systems

et al. 2015

Self Cite

Due to the increasing requirements of the seamless and round-the-clock Location-based services (LBSs), a growing interest in Wi-Fi network aided location tracking is witnessed in the past decade. One of the significant problems of the conventional Wi-Fi location tracking approaches based on received signal strength (RSS) fingerprinting is the time-consuming and labor intensive work involved in location fingerprint calibration. To solve this problem, a novel unlabeled Wi-Fi simultaneous localization and mapping (SLAM) approach is developed to avoid the location fingerprinting and additional inertial or vision sensors. In this approach, an unlabeled mobility map of the coverage area is first constructed by using the crowd-sourcing from a batch of sporadically recorded Wi-Fi RSS sequences based on the spectral cluster assembling. Then, the sequence alignment algorithm is applied to conduct location tracking and mobility map updating. Finally, the effectiveness of this approach is verified by the extensive experiments carried out in a campus-wide area.