Research On Underwater Acoustic Doppler Factor Estimation Based On Autocorrelation Objective Function

Doppler frequency shift is unavoidable in the communication system generally, which makes Doppler estimation become an integral part of the communication system. After years of research, achievements of Doppler frequency shift estimation have been made in land wireless communication systems. In underwater communication, acoustic wave is the main information carrier in ocean development and research due to the good propagation performance of acoustic wave in seawater. However, the propagation speed of the acoustic wave is much slower than that of electromagnetic wave and it is influenced by the velocity of the water. Hence, acoustic wave underwater is more vulnerable to the Doppler frequency shift compared to land communication system. Therefore, the estimation and compensation of Doppler shift becomes an important part of underwater acoustic communication. So the Doppler frequency shift in underwater is studied specifically, mainly includes:Firstly, this paper introduces the effect of the ocean acoustic environment. In the process of propagation in the sea, the acoustic wave is affected by the transmission loss of sound absorption and scattering, multipath delay, all kinds of noise and Doppler effect. At the same time, some classical Doppler estimation algorithms are also described, and the applicability of those algorithms in underwater acoustic communication is analyzed in this paper as well.Secondly, in view of the problem of low accuracy in low SNR and large computation cost in existing Doppler estimation algorithm, a fast Doppler estimation method based on autocorrelation objective function is proposed in this paper. In proposed algorithm, the autocorrelation function of a single frequency signal is derived to constructed the objective function and solve the Doppler frequency shift factor.Thirdly, the theoretical performance bound, i.e. Cramer-Rao Lower Bound(CRLB) of estimation is derived according to the knowledge of parameter estimation. The simulation experiment shows that the new algorithm is more accurate than the existing Doppler estimation method with low complexity, and it is gets close to the CRLB in low SNR case.