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Resolution and parameters estimations for multiple maneuvering targets in the same range cell is addressed in this work.The low-resolution radar cannot distinguish multiple targets in both distance and angle,but the detection of Doppler frequency variation of the multiple maneuvering targets can be used to resolve this problem.At present,most of researches on detection of Doppler frequency variation are carried out with time-frequency analysis methods,such as Fractional Fourier transformation(FRFT),Adaptive Chirplet transformation(ACT),and Wigner-Ville distribution(WVD)and so on,which need satisfy enough time duration and sampling theorem.This paper proposes a new method of resolution and parameters estimation for multiple maneuvering targets based on Compressive Sensing(CS)and clustering technique,which samples at low rate and short time duration without sacrificing estimation performance.Simulation results validate the effectiveness of the proposed algorithm,and also show that the performance of the proposed method is superior to that of FRFT in the condition of multiple targets.
Resolution and parameters estimations for multiple maneuvering targets in the same range cell is addressed in this work. Low-resolution radar can not distinguish multiple targets in both distance and angle, but the detection of Doppler frequency variation of the multiple maneuvering targets can be used to resolve this problem. At present, most of researches on detection of Doppler frequency variations are carried out with time-frequency analysis methods such as Fractional Fourier transformation (FRFT), Adaptive Chirplet transformation (ACT), and Wigner-Ville distribution (WVD) and so on, which must satisfy enough time duration and sampling theorem. This paper proposes a new method of resolution and parameters estimation for multiple maneuvering targets based on Compressive Sensing (CS) and clustering technique, which samples at low rate and short time duration without sacrificing estimation performance.Simulation results validate the effectiveness of the proposed algorithm, and also show that the pe rformance of the proposed method is superior to that of FRFT in the condition of multiple targets.