Accurate and simple source localization using differential received signal strength

Accurate and simple source localization using differential received signal strength

Locating an unknown-position source using received signal strength (RSS) measurements in an accurate and low-complexity manner is addressed in this paper. Given that the source transmit power is unknown, we employ the differential RSS information to devise two computationally attractive localization methods based on the weighted least squares (WLS) approach. The main ingredients in the first al...

Emitter localization using received-strength-signal data

This paper considers a scenario in which signals from an emitter at an unknown location are received at a number of different collinear locations. The receiver can determine the received signal strength, but no other parameters of the signal. Postulating a log-normal transmission model with a constant but unknown path loss exponent and, also, an unknown transmit power and known noise variance, ...

Learning Indoor Localization using Radio Received Signal Strength

Maritime Management Using Received Signal Strength Indicator

For location finding through Wireless Sensor Networks (WSNs), the RSSI is regularly assumed to have a linear signal strength by the whole of the logarithm of the communication distance. However, this is not true in certain cases because there are uncertainties in RSSI readings to obstacles, receiver interferences etc. In this complimentary, we specifically ask for the hand of a new RSSI-based c...

PRIMAL: Page Rank-Based Indoor Mapping and Localization Using Gene-Sequenced Unlabeled WLAN Received Signal Strength

Due to the wide deployment of wireless local area networks (WLAN), received signal strength (RSS)-based indoor WLAN localization has attracted considerable attention in both academia and industry. In this paper, we propose a novel page rank-based indoor mapping and localization (PRIMAL) by using the gene-sequenced unlabeled WLAN RSS for simultaneous localization and mapping (SLAM). Specifically...