LAUSR

Telemonitoring and communications technologies of underwater information is inseparable from the process of sampling and transmitting of data. Conventional methods often fail in energy efficiency to obtain such a huge data in Internet of Things (IoT), compressed sensing (CS) provides a new perspective to solve the problem. Unfortunately, the underwater acoustic signal is non-sparse in the time domain and thus the current CS methods cannot be used directly. This study adopts the fast Fourier transform (FFT) based dictionary-matrix for sparse representation. Then we design an approach based on an approximated $l0$ (AL0) norm at the receiving terminal, to search the sparse solution via the filtered steepest descent method and projections. The sparse estimation is used for reconstruction of collected data, combing with the previously used measurement matrix and dictionary-matrix. Experimental results confirm the superior performances of the strategies of the proposed method than the traditional methods including matching pursuit (MP) and orthogonal matching pursuit (OMP) methods. Telemonitoring and communications technologies of underwater information is inseparable from the process of sampling and transmitting of data. Conventional methods often fail in energy efficiency to obtain such a huge data in Internet of Things (IoT), compressed sensing (CS) provides a new perspective to solve the problem. Unfortunately, the underwater acoustic signal is non-sparse in the time domain and thus the current CS methods cannot be used directly. This study adopts the fast Fourier transform (FFT) based dictionary-matrix for sparse representation. Then we design an approach based on an approximated $l0$ (AL0) norm at the receiving terminal, to search the sparse solution via the filtered steepest descent method and projections. The sparse estimation is used for reconstruction of collected data, combing with the previously used measurement matrix and dictionary-matrix. Experimental results confirm the superior performances of the strategies of the proposed method than the traditional methods includ...