An underwater target position estimation method based on the cross-correlation dictionary

For underwater active detection, the relative position relationship between a target and a sonar system is very important for identifying and tracking the target. It is difficult for the existing underwater target position estimation method based on the waveform dictionary to accurately estimate the target position under at low signal-to-noise ratios. Because the cross-correlation processing has noise immunity in target echo detection, this paper proposes a target position estimation method based on the cross-correlation dictionary. It constructs a cross-correlation dictionary and combines it with the orthogonal matching pursuit (OMP) algorithm. To construct the cross-correlation dictionary, the echo highlight model is used to generate echo signals with different horizontal position angles. The effects of different system parameters on the correlation performance of the dictionary are analysed. Pool experimental results show that the target position estimation method based on the cross-correlation dictionary outperforms the waveform dictionary at low signal-to-noise ratios (less than -12 dB) and can still carry out the accurate estimation at low signal-to-noise ratios with a small number of array elements by increasing the bandwidth. Jointly used with HFM signals, the underwater target position estimation method based on the cross-correlation dictionary can be used to estimate the position of a slow target.