Permuted&Filtered Spectrum Compressive Sensing

A permuted&filtered spectrum compressive sensing (PFSCS) method is developed for spectrum sparse signals. Using the permutation function and the flat window function, PFSCS first constructs the permuted&filtered measurement matrix and acquires the measurements vector. Then PFSCS locates and estimates fourier coefficients using the two samples method which has been used in orthogonal frequency division multiplexing (OFDM). Experimental results show that PFSCS runs much faster and performs better than standard compressive sensing methods, especially when the sparsity K is high.