The One-dimensional Range Imaging of Linear Target Based on Compressive Sensing

In conventional radar system, the resolution is constrained by Nyquist sampling rate. A large amount of data is created under the high-resolution requirement. Compressive Sensing (CS) relieves the demand of A/D converter and the capacity of memories. Under the framework of CS, a set of bases, which is incomplete but is based on the targets' features, is given out in this paper. A method is proposed for reconstruction that is compatible with the bases. The sparseness of the issue is not necessary for the proposed approach. And the method has very good performance on dealing with linear targets, especially when the lengths of the targets are very long. Furthermore, it can also resolve the multi-target issue. The simulation results verify the efficiency of the proposed algorithm.