A Space-time-frequency Joint Detection Method of Line-spectrum Components in Underwater Acoustic Signals

The information such as the azimuth, frequency and the number of the line-spectrum signals is usually unknown in the passive detection of underwater target. And the performance of line-spectrum detection is greatly affected by broadband interferences and background noise under the condition of low signal-to-noise ratio (SNR). For this issue, a space-time-frequency joint detection method of detecting the unknown line-spectrum target based on Hidden Markov Models (HMM) is proposed. Each line-spectrum in multi-beam lofargram is modelled as a first order Markov chain. Firstly, the background noise is balanced and the approximate direction and frequency range of the target are determined by preprocessing on multi-beam lofargram. Then, the existing target line-spectrum are extracted in proper order using Viterbi algorithm. Finally, the extraction results of line-spectrum in different direction and frequency ranges are analyzed and integrated to obtain the orientation, frequency and other information of target line-spectrum. The processing results of simulation data and measured data show that the proposed method can adapt to the complex situation such as multi-target, multi-line-spectrum, and has good detection performance in low SNR.