Modified Prominent Point Processing in ISAR Imaging Based on Minimum Entropy Method

In this paper, the modified prominent point processing (MPPP) approach for the phase compensation in inverse synthetic aperture radar (ISAR) imaging is proposed. It applies the minimum entropy method (MEM) to find the prominent point cell used for the phase calibration. After minusing the measured phase value of prominent point range cell from all the range bins belonged to the same echo, a well-focused ISAR image can be obtained by combining all the range bins. Compared to the PPP algorithm, the MPPP method can find the better prominent point unit utilized for the phase correction, which will lead to a more focused ISAR image after the phase compensation. The simulation result proves that the proposed approach can enhance the clarity and focusing of the ISAR image.