A novel parameter estimation algorithm and its iterative extension for chirp signals

The chirp signal is a nonstationary signal that is often met in applications including radar and sonar etc. The parameter estimation of the unknown parameters in chirp signals by traditional maximum likelihood method or the open-loop optimum method bear some problems, such as the excessive computational complexity. We propose a novel fast and robust method. The method is robust in the sense that it can be well suitable for the case of low signal to noise ratio (SNR). For example, in the case of -10 dB of SNR, the new method achieves a good performance quite close to that of the maximum likelihood method, and the computational complexity is reduced to only 1/40 of the original. We present the motivation of the new algorithm and the performance analysis. Also some simulation results are presented to illustrate its effectiveness.