Localization via TDOA in a UWB Sensor Network using Neural Networks

In an Ultra-wide band (UWB) sensor network signal reflections from objects can be used to accurately determine the location. UWB signals are preferred in these types of sensor networks since they provide a very good resolution due to their fine time granularity. We propose an artificial neural network based localization to detect single object in a sensor network and compare its performance to Cramer-Rao bound and least squares estimator. Then we propose a two phase algorithm for multiple object detection and evaluate the algorithm for the case when there are two objects in a sensor network with three nodes. ICC 2008 (May) This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laborat...

• Type: Conference
• Year: 2008
• Where: ICC
• Authors: Salih Ergüt, Ramesh R. Rao, Özgür Dural, Zafer Sahinoglu
• Keywords: Communications, Electric Research Laboratories, ICC 2008, Mitsubishi Electric Research, Sensor Network