A Bayesian approach to respiration rate estimation via pulse-based ultra-wideband signals
Date
2009Source Title
Proceedings of the 2009 IEEE International Conference on Ultra-Wideband, ICUWB 2009
Publisher
IEEE
Pages
630 - 634
Language
English
Type
Conference PaperItem Usage Stats
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Abstract
In 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.
Keywords
Generalized Cramer-Rao lower bound (G-CRLB)Maximum a posteriori probability (MAP) estimation
Ultra-wideband (UWB)
Bayesian approaches
Cramer Rao lower bound
Displacement function
Matched filters
Prior information
Respiration rate
Signal parameters
Simulation result
Theoretical limits
Theoretical result
Ultra-wideband signal
Bayesian networks
Wireless telecommunication systems