In inverse synthetic aperture radar (ISAR) imaging of targets with complex motion, the azimuth echoes have to be modeled as multicomponent cubic phase signals (CPSs) after motion compensation. For the CPS model, the chirp rate and the quadratic chirp rate deteriorate the ISAR image quality due to the Doppler frequency shift; thus, an effective parameter estimation algorithm is required. This paper focuses on a parameter estimation algorithm for multicomponent CPSs based on the local polynomial ambiguity function (LPAF), which is simple and can be easily implemented via the complex multiplication and fast Fourier transform. Compared with the existing parameter estimation algorithm for CPS, the proposed algorithm can achieve a better compromise between performance and computational complexity. Then, the high-quality ISAR image can be obtained by the proposed LPAF-based ISAR imaging algorithm. The results of the simulated data demonstrate the effectiveness of the proposed algorithm.
KEYWORDS: 3D acquisition, 3D image processing, Interferometry, Antennas, Detection and tracking algorithms, Receivers, 3D modeling, Target recognition, Radar imaging, Radar
Inverse synthetic aperture radar (ISAR) can achieve high-resolution two-dimensional images of maneuvering targets. However, due to the indeterminate relative motion between radar and target, ISAR imaging does not provide the three-dimensional (3-D) position information of a target and suffers from great difficulty in target recognition. To tackle this issue, a 3-D interferometric ISAR (InISAR) imaging algorithm based on the joint cross modified Wigner-Ville distribution (MWVD) is presented to form 3-D images of maneuvering targets. First, we form two orthogonal interferometric baselines with three receiving antennas to establish an InISAR imaging system. Second, after the uniform range alignment and phase adjustment, the joint cross MWVD is used for all range cell of each antenna pair to generate the separation of the scatterer as well as preserve the phase that contains position information of the scatterer. At last, the 3-D images of the target can be directly reconstructed from the distribution. Simulation results demonstrate the validity of the proposal.
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