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Frequency-stepped chirp signal can simplify the designation of radar system.However,it has a shortcoming of Doppler ambiguity for high-speed moving targets.Therefore,it is of great significance to study how to increase its equivalent pulse repeat frequency.The back scattering field of the ISAR target has strong sparsity;that is to say,most energy is contributed merely by a few scattering centers.Hence,based on the theory of the sparse signal representation,a novel method for ISAR imaging via sparse frequency-stepped chirp signals is proposed by analyzing the signal model of the target.In the proposed method,part of sub-pulses of the frequency-stepped chirp signal is randomly selected to transmit,and then the 2D high-resolution image of the target can be constructed by sparse signal decomposition.At the cost of computational resources,the method can effectively resolve the problem of Doppler ambiguity,decrease the sidelobes and obtain a super-resolution image.Furthermore,the validity of the proposed approach is confirmed by the results of numerical simulations and real data.
Frequency-stepped chirp signal can simplify the designation of the radar system. However, it has a shortcoming of Doppler ambiguity for high-speed moving targets. Before, it is of great significance to study how to increase its equivalent pulse repeat frequency. The back scattering field of the ISAR target has strong sparsity; that is to say, most energy is contributed merely by a few scattering centers .ence, based on the theory of the sparse signal representation, a novel method for ISAR imaging via sparse frequency-stepped chirp signals is proposed by analyzing the signal model of the target. In the proposed method, part of sub-pulses of the frequency-stepped chirp signal is randomly selected to transmit, and then the 2D high-resolution image of the target can be constructed by sparse signal decomposition. At the cost of computational resources, the method can effectively resolve the problem of Doppler ambiguity, decrease the sidelobes and obtain a super-resolution image. Future, the validity of the proposed approach is confirmed by the results of numerical simulations and real data.