High Range Resolution Profiling for Stepped-Frequency Radar with Sparse Reconstruction

The newly emerging theory of compressed sensing (CS) enables restore of a sparse signal from inadequate number of linear projections. Based on compressed sensing theory, a new strategy of high-resolution range profiling of stepped-frequency (SF) radar with missing pulses is proposed. If a certain part of received pulses are missing, we demonstrate the proposed method is capable of reconstructing target profile with high fidelity. MATLAB simulation results are presented to verify the proposed method. Furthermore, we use collected data from real SF radar to generate target high-resolution range profile (HRRP). Results are compared with traditional ’Stretch’ method to prove its applicability.