Autocorrelation method for estimation of Doppler parameters in fast-varying underwater acoustic channels

In this paper, we propose and investigate a low-complexity technique for estimating the Doppler parameters in fast-varying underwater acoustic channels. This technique can be used in communication systems with periodically transmitted spread spectrum pilot signals. The known autocorrelation techniques for Doppler estimation suffer from low accuracy in channels fast-varying over the estimation interval. The proposed technique avoids such a problem by introducing a multichannel estimator. The proposed technique not only measures the time compression over the estimation interval, but also the gradient of the time compression, thus allowing more accurate (with timevarying sampling rate) resampling the received signal to compensate for the Doppler distortions. The proposed method is compared with a known autocorrelation technique and the technique based on computing the cross-ambiguity function between the received and pilot signals. The comparison is performed using ocean experiments at short and long distances. The short-range experiment is at a distance of about 3 km with drifting transmitter and receiver (at a speed of 0.5 m/s) and a few discrete multipath components. The long-range experiment is at a distance of 80 km with a transmitter moving at a speed of 6 m/s and a large number of scattered multipath components. The transmitted signal is a pilot-added guard-free OFDM signal. The results demonstrate that, in both the experiments, the proposed technique outperforms the known autocorrelation technique and comparable in the performance with the cross-ambiguity method. The performance improvement is especially significant in the second experiment, where the known autocorrelation method is not capable of providing reliable demodulation of the transmitted data, whereas the proposed technique performs similarly to the crossambiguity method.