Title :
Compressed sensing-based centralized multiple targets localization
Author :
Ahriz, Iness ; Dziri, Ali ; Le Ruyet, Didier
Author_Institution :
LAETITIA/CEDRIC Lab., Paris, France
Abstract :
In this paper, we propose Received Signal Strength (RSS)-based localization method in WiFi network using the Compressed Sensing theory (CS). The main contributions are two-folds. First, we need no additional infrastructure more than the existing WiFi networks for targets localization. Second, in our approach, we have introduced an improvement of the Orthogonal Matching Pursuit (OMP) in order to relax the a priori knowledge of the number of targets to be located. The proposed approach offers an accurate recovery of multiple sparse targets locations using RSSI-measurements (RSS Indicator) at the Access Points (APs). Localization performance of the method was investigated by simulation in a multi target localization scenario. We have evaluated the mean localization error and its empirical Cumulative Density Function (CDF). Obtained results show a mean error about 0.5m in an area of 100m2.
Keywords :
compressed sensing; wireless LAN; CDF; OMP; RSS indicator; RSS-based localization method; RSSI-measurements; WiFi network; access point; compressed sensing theory; compressed sensing-based centralized multiple target localization; cumulative density function; multiple sparse target locations; orthogonal matching pursuit; received signal strength-based localization method; Compressed sensing; Correlation; IEEE 802.11 Standards; Matching pursuit algorithms; Mobile communication; Noise; Vectors; Compressed Sensing; Locatization; RSSI;
Conference_Titel :
Wireless Communications Systems (ISWCS), 2014 11th International Symposium on
Conference_Location :
Barcelona
DOI :
10.1109/ISWCS.2014.6933417