Variable Parameter Estimation of SAR Signal Based on Compression Sensing

The linear frequency modulation (LFM) signal is widely used in the radar field because of its large time-bandwidth product and low intercept rate. It is very valuable to estimate the parameters of the LFM signal in the practical applications. With the increasing requirements for radar system, the radar signal parameters are no longer constant, and may change in accordance with a certain law. Then the traditional parameter estimation methods cannot attain an accurate result for a radar signal with variable parameters. In this paper, an estimation of variable parameter SAR signal based on compression sensing (CS) is proposed. The parameter value of every pulse is obtained with the existed parameter estimation method firstly. The law of parameter change with time is supposed to be a polynomial, then we take into account the sparsity of polynomial coefficients and use the compression sensing theory to reconstruct the polynomial coefficient vector denoting the change of the parameter. After introducing the theory of compression sensing, the timing characteristics of SAR signal are analyzed. The validity of the proposed method is verified by theoretical analysis and simulation. Especially for SAR signal with few pulses, this method can be used in the absence of a priori information and restore the variable parameters of the SAR signal with higher accuracy.