Fuzzy modeling, maximum likelihood estimation, and Kalman filtering for target tracking in NLOS scenarios
نویسندگان
چکیده
منابع مشابه
Collaborative target tracking in WSNs using the combination of maximum likelihood estimation and Kalman filtering
Target tracking using wireless sensor networks requires efficient collaboration among sensors to tradeoff between energy consumption and tracking accuracy. This paper presents a collaborative target tracking approach in wireless sensor networks using the combination of maximum likelihood estimation and the Kalman filter. The cluster leader converts the received nonlinear distance measurements i...
متن کاملKalman Filtering for NLOS Mitigation and Target Tracking in Indoor Wireless Environment
Kalman filter and its nonlinear extension, extended Kalman filter provide a feasible solution to mitigating non-line of sight (NLOS) propagation effects, and therefore improving accuracy of mobile target tracking in indoor wireless environments. Most wireless communication systems for indoor positioning and tracking may suffer from different error sources, including process errors, measurement ...
متن کاملAn interacting Fuzzy-Fading-Memory-based Augmented Kalman Filtering method for maneuvering target tracking
Article history: Available online 14 May 2013
متن کاملKalman tracking for mobile location in NLOS situations
:lhstr,,c/This paper deals with thc problem of non-line-of-sight (NLOS) in wireless coinniunications systems devoted to location purpnses. I t i s WEII known that NLOS biases time o f nr r iva l ('rO+\) 21nd Time Difference of Arrival (TDOA) estimates thus rcduring accuracy of positioning algorithms. I n urder to achieve positioning error reduction the Kalman filter proposed for Iorntion estima...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2014
ISSN: 1687-6180
DOI: 10.1186/1687-6180-2014-105