Localization of Sensors in Indoor Wireless Networks: An Observation Model Using WiFi RSS

Abstract

Indoor localization has become an important issue for wireless sensor networks. This paper presents a zoningbased localization technique that works efficiently in indoor environments. The targeted area is composed of several zones, the objective being to determine the zone of the sensor using an observation model. The observation model is constructed based on fingerprints collected as WiFi signals strengths received from surrounding Access Points. The method creates a belief functions framework that uses all available information to assign evidence to each zone. A hierarchical clustering technique is then applied to create a two-level hierarchy composed of clusters and of original zones in each cluster. At each level of the hierarchy, an Access Point selection approach is proposed to choose the best subset of Access Points in terms of discriminative capacity and redundancy. Real experiments demonstrate the effectiveness of this approach and its competence compared to state-of-the-art methods.

An Evidential Framework for Localization of Sensors in Indoor Environments

“…Generally, localization techniques are split into two categories, geometrical and non-geometrical techniques. In geometric techniques, the position of the MN is estimated by compiling one or more channel characteristics, such as angle of arrival (AoA) [10], time difference of arrival (TDoA) [11], time of arrival (ToA) [12], or received signal strength indicator (RSSI) [13][14][15] into a geometric output. Equations relating the unknown position of the MN with the known positions of the ANs are derived and solved to estimate the MN position.…”

A Capacitively-Fed Inverted-F Antenna for Displacement Detection in Structural Health Monitoring

“…As for wireless sensors, they utilize technologize, such as WIFI [ 9 ], the general packet radio service (GPRS), ZigBee [ 10 , 11 ], Bluetooth [ 12 ] and other telecommunication technologies [ 13 ], to realize wireless communication. However, they still need energy from on-board batteries or other methods to function, which will result in reduced reliability, increased installation complexity and cost of wireless sensors, and eventually pose a long-term environmental risk with disposal of billions of batteries [ 14 ].…”

A Device-Free Indoor Localization Method Using CSI with Wi-Fi Signals

“…According to different acquisition signals, Wi-Fi-based indoor positioning technology can be divided into indoor positioning technology based on RSSI signal and indoor positioning technology based on Channel State Information (CSI) [10,11]. However, in the indoor environment, the Received Signal Strength Indication (RSSI) signal, as a kind of coarse-grained information, is highly susceptible to interference from other signals and the indoor multipath effect, so it cannot provide sufficient accuracy and reliability [12,13,14,15]. For Wi-Fi signals using IEEE 802.11n communications protocol, it can obtain CSI in Orthogonal Frequency Division Multiplexing (OFDM) subcarriers by modifying the wireless network card driver.…”