Non-cooperative underwater acoustic MFSK time-frequency representation optimization method based on sparse reconstruction

Abstract

The performance of the traditional non-cooperative underwater acoustic (UWA) multiple frequency shift key (MFSK) recognition and parameter estimation method based on time-frequency representation (TFR) is affected by TFR energy divergence. Herein, a sparse TFR estimation model for UWA MFSK is presented. The model exploits the properties of MFSK TFR element sparsity and row sparsity, which can effectively reduce the impact of the channel and does not require any a priori information. To achieve better TFR performance, we propose an inversion fitting method that can effectively improve the frequency resolution, while keeping the time resolution unchanged. Simulation and experimental results show that the Peak Signal to Noise Ratio (PSNR) of the proposed method reaches 21dB with the increase of Signal to Noise Ratio (SNR), indicating that the proposed method has high carrier frequency reconstruction and noise suppression performance. The proposed method can continuously reduce the value of Average Carrier Frequency Offset (ACFO) under inversion fitting method, indicating that inversion fitting method can further reduce the energy divergence and improve frequency resolution.