A novel cognitive ISAR imaging method with random stepped frequency chirp signal
The random stepped frequency chirp signal (RSFCS) has better performance in anti-jamming than that of conventional stepped frequency chirp signal (SFCS). In combination with the theory of compressing sensing (CS), a novel ISAR imaging method is proposed based on RSFCS, in which the high resolution range profile (HRRP) is reconstructed by using the conventional OMP algorithm, whereas the cognitive approach is introduced to further reduce the number of sub-pulse in RSFCS. In the proposed method, via cognizing the characteristics of moving targets, the number of sub-pulse in each burst can be adjusted adaptively. Finally, in the cross-range direction, the accurate reconstruction of ISAR image by using CS theory is implemented, which can effectively accomplish unwrapping. With the proposed method, high quality HRRP and ISAR image can be achieved with fewer sub-pulses of RSFCS and lower burst repetition frequency (BRF). Some simulation results are given to validate the effectiveness and robustness of the proposed algorithm.
isar imaging random stepped frequency chirp signal compressed sensing high resolution range profile cognitive approach