Title :
Estimation of chirp signals by MCMC
Author :
Lin, Chung-Chieh ; Djuric, P.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., State Univ. of New York, Stony Brook, NY, USA
Abstract :
This paper considers the problem of parameter estimation of chirp signals by using the Bayesian methodology. The concept of “mirror points” for constant-amplitude chirp signals is introduced, and its effect on the overall multicomponent chirp parameter estimation performance assessed. By combining the chirpogram with a Markov chain Monte Carlo (MCMC) technique, it is shown that accurate estimates can be obtained for signals comprising many chirps. Simulation results demonstrate that the parameter estimates are in agreement with the CRLB for SNRs as low as 2 dB
Keywords :
Bayes methods; Markov processes; Monte Carlo methods; parameter estimation; signal representation; Bayesian methodology; MCMC; Markov chain Monte Carlo technique; chirp signals; chirpogram; constant-amplitude chirp signals; mirror points; multicomponent chirp parameter estimation performance; parameter estimation; Bayesian methods; Chirp; Doppler radar; Frequency estimation; Gaussian noise; Monte Carlo methods; Parameter estimation; Physics; Radar applications; Sonar applications;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
0-7803-6293-4
DOI :
10.1109/ICASSP.2000.861938
