Learn More
This work discuses a novel algorithm for joint sparse estimation of superimposed signals and their parameters. The proposed method is based on two concepts: a variational Bayesian version of the incremental sparse Bayesian learning (SBL)– fast variational SBL – and a variational Bayesian approach for parameter estimation of superimposed signal models. Both(More)
Time Based (TB) localization in terrestrial cellular mobile radio as a complementation to Global Navigation Satellite Systems (GNSSs) has gained plenty of focuses. Due to absence of the Line-of Sight (LOS), Time of Arrival (ToA) of the First Path (FP) and/or corresponding Time Difference of Arrival (TDoA) are drifted from their true values. However, there(More)
REGULAR PAPERS Algorithms, Artificial Intelligence, SOFT Computing and Informatics Probabilistic Fuzzy System for Uncertain Localization and Map Building of Mobile Robots . . . S. Chen and C. Chen xxx Acoustics and Ultrasonics Instrumentation and Measurements High-Accuracy Reference-Free Ultrasonic Location Estimation . . .M. M. Saad, C. J. Bleakley, T.(More)
Time Based (TB) localization in terrestrial communications mobile radio as a complementation to global navigation satellite systems has gained recently plenty of interests. As an essential tool to develop suitable algorithms for joint communications and localizations in mobile radio networks, the wireless channel model has a growing significance. For both(More)
Time Based (TB) localization by terrestrial cellular communications mobile radio as a complementation to Global Navigation Satellite Systems (GNSSs) has gained plenty of interests. Apart from multipath considered in standard communication channel models, the Non Line-of-Sight (NLoS) error due to an undetectable Line-of-Sight (LoS) path, defined as the(More)
Recently the fusion of positioning andwireless communication has gainedmany interests due to themerits of location information for future communication systems. Both positioning and wireless communication are highly dependent on the air channel. Current channel models are well suited for communication applications but less for positioning. Therefore, we(More)
Range based positioning by estimating the time of arrival (ToA) of the line-of-sight (LoS) path using orthogonal frequency division multiplexing (OFDM) signals has gained remarkable attention. Multipath propagation significantly influences the ToA estimate resulting in position errors. To mitigate these errors, the multipath channel needs to be accurately(More)
We develop a linear mixed regression model where both the response and the predictor are functions. Model parameters are estimated by maximizing the log likelihood via the ECME algorithm. The estimated variance parameters or covariance matrices are shown to be positive or positive definite at each iteration. In simulation studies, the approach outperforms(More)