Data fusion using subbands, which can obtain a higher range resolution without altering the bandwidth, hardware, and sampling rate of the radar system, has attracted more and more attention in recent years. A method of ISAR imaging based on subbands fusion and high precision parameter estimation of geometrical theory of diffraction (GTD) model is presented in this paper. To resolve the incoherence problem in subbands data, a coherent processing method is adopted. Based on an all-pole model, the phase difference of pole and scattering coefficient between each sub-band is used to effectively estimate the incoherent components. After coherent processing, the high and low frequency sub-band data can be expressed as a uniform all-pole model. The gapped-data amplitude and phase estimation (GAPES) algorithm is used to fill up the gapped band. Finally, fusion data is gained by high precision parameter estimation of GTD-all-pole model with full-band data, such as scattering center number, scattering center type and amplitude. The experimental results of simulated data show the validity of the algorithm.
In this paper the effects of orbits motion makes for scattering centers trajectory is analyzed, and introduced to scattering
centers association, as a constraint. A screening method of feature points is presented to analysis the false points of
reconstructed result, and the wrong association which lead these false points. The loop iteration between 3D
reconstruction and association result makes the precision of final reconstructed result have a further improvement. The
simulation data shows the validity of the algorithm.
An improved method of three-dimensional (3D) reconstruction from Inverse Synthetic Aperture Radar (ISAR) sequences
based on factorization are proposed in this paper, which can improve the accuracy of reconstruction, and increase the
number of reconstructed 3D features. A segmentation method of feature points based on clustering analysis is applied,
which can remove some false points from reconstructed 3D features to enhance the precision of three-dimensional
reconstruction. The result of simulation images and real images show the validity of the algorithm.
In order to extract precession frequency, an crucial parameter in ballistic target recognition, which reflected the kinematical characteristics as well as structural and mass distribution features, we developed a dynamic RCS signal model for a conical ballistic missile warhead, with a log-norm multiplicative noise, substituting the familiar additive noise, derived formulas of micro-Doppler induced by precession motion, and analyzed
time-varying micro-Doppler features utilizing time-frequency transforms, extracted precession frequency by measuring the spectrogram’s texture, verified them by computer simulation studies. Simulation demonstrates the excellent performance of the method proposed in extracting the precession frequency, especially in the case of low SNR.
ISAR (inverse synthetic aperture radar) can generate 2D image of a non-cooperative moving target and be used for military and civilian purpose. For moving target，well-focused ISAR images can be achieved using appropriate motion compensation and image reconstruction algorithm. The ISAR image will be difficultly when the echo is at a low signal-to-noise level. For polarimetric ISAR system which transmits and receives different polarisation signal in both two channels, the fusion of HRRP (high range resolution profile) from different channels will improve significantly the SNR of the signal. The method proposed in this paper firstly fuses the different channels HRRP to get a higher SNR signal. Then the target region is extracted in fused HRRP. Finally, the motion compensation for ISAR imaging is carried out only on the extracted target region data in the sense of using image reconstruction method to gain a focused ISAR image. The real measured data shows the validity of the algorithm.