The compressive signal processing provides an effective approach for efficient spectral image data collecting and processing.An improved compressive sampling detection method based on prior sparse model of signal is proposed to solve the problems of low detection rate and weak robustness in traditional compressive sampling detection algorithm.To enhance the capability of information collection,the sparse representation subspace of signal to be measured is used to design compressive sampling matrix.The orthogonal subspace projection method is used to project the compressive sampling signal into the local orthogonal subspace of the interfering signal for background suppression.The experimental and analytical results show that the method can effectively improve the performance of the compressive sampling detection compared with the traditional algorithm,and enhance the robustness for different sample matrix.