Radar Micro-Doppler signatures are of great potential for target detection, classification and recognition. In the mid-course phase, warheads flying outside the atmosphere are usually accompanied by precession. Precession may induce additional frequency modulations on the returned radar signal, which can be regarded as a unique signature and provide additional information that is complementary to existing target recognition methods. The main purpose of this paper is to establish a more actual precession model of conical ballistic missile warhead and extract the precession parameters by utilizing Viterbi & Kalman algorithm, which improving the precession frequency estimation accuracy evidently , especially in low SNR.
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.