Browsing by Subject "Ultra-wideband signal"
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item Open Access A Bayesian approach to respiration rate estimation via pulse-based ultra-wideband signals(IEEE, 2009) Soǧancı, Hamza; Gezici, Sinan; Arıkan, OrhanIn this paper, theoretical limits on estimation of respiration rates via pulse-based ultra-wideband (UWB) signals are studied in the presence of prior information about respiration related signal parameters. First, a generalized Cramer-Rao lower bound (G-CRLB) expression is derived, and then simplified versions of the bound are obtained for sinusoidal displacement functions. In addition to the derivation of the theoretical limits, a two-step suboptimal estimator based on matched filter (correlation) processing and maximum a posteriori probability (MAP) estimation is proposed. It is shown that the proposed estimator performs very closely to the theoretical limits under certain conditions. Simulation results are presented to investigate the theoretical results.Item Open Access Enhancements to threshold based range estimation for ultra-wideband systems(IEEE, 2014-09) Soğancı, Hamza; Gezici, Sinan; Güldoğan, M. B.Ultra-wideband (UWB) signals have very high time resolution, which makes them a very good candidate for range estimation based wireless positioning. Although the accuracy is the major concern for range estimation, it is also important to have low-complexity algorithms that can be employed in real time. In this study, two low-complexity range estimation algorithms are proposed for UWB signals, which achieve improved performance compared to the state-of-the-art low-complexity ranging algorithms. The proposed algorithms are inspired from two well-known algorithms; 'serial backward search' (SBS) and 'jump back and search forward' (JBSF). Performances of the proposed algorithms are compared with those of the SBS and JBSF algorithms based on real measurements. In addition, theoretical bounds are calculated in order to quantify the statistical performance of the algorithms. © 2014 IEEE.