Parameter estimation of chirp signals in random noise using Wigner distribution

Incorporating with the realizations of Wigner distribution, an effective method of estimating unknown parameters of the received noisy chirp signals is proposed. The method is tested by simulations for superimposed chirp signals to show the efficacy.

[1]  T. Abatzoglou Fast Maximnurm Likelihood Joint Estimation of Frequency and Frequency Rate , 1986, IEEE Transactions on Aerospace and Electronic Systems.

[2]  Petar M. Djuric,et al.  Parameter estimation of chirp signals , 1990, IEEE Trans. Acoust. Speech Signal Process..

[3]  Akira Ohsumi,et al.  Maximum likelihood estimation of time-delay of ultrasonic signals based on Wigner distribution , 2003, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

[4]  T. Abatzoglou,et al.  "Fast maximum likelihood joint estimation of frequency and frequency rate" , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  Igor Djurovic,et al.  Maximum likelihood estimation for signal parameters using pseudo-Wigner distribution , 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

[6]  Steven M. Kay,et al.  Maximum likelihood parameter estimation of superimposed chirps using Monte Carlo importance sampling , 2002, IEEE Trans. Signal Process..

[7]  LJubisa Stankovic,et al.  Instantaneous frequency estimation using the Wigner distribution with varying and data-driven window length , 1998, IEEE Trans. Signal Process..

[8]  H. Cramér Mathematical methods of statistics , 1947 .