High-resolution distributed ISAR imaging by OMP method

Abstract

The distributed inverse synthetic aperture radar (ISAR) technique can form multiple virtual sensors and has the potential to increase the cross-range resolution by exploiting the multi-channel echoes. In the existing imaging approaches, the echoes acquired from different virtual sensors are rearranged into an equivalent single-channel ISAR signal firstly. Then, the missing data between the observation angles of any two adjacent sensors is restored by interpolation. Thus, the echo with long observation time can be acquired. After the fast Fourier transform on this echo, the improved cross-range resolution image can be acquired. However, when the gaps are large, the recovered missing data is very inaccurate. Secondly, if the target rotates non-uniformly and the change of the observation angle is not a linear function with the slow time, the equivalent single-channel ISAR echo cannot be obtained by interpolation. Therefore, this study aims to avoid these drawbacks and get desired distributed ISAR imaging results. After sparse representation of the distributed ISAR echoes, the orthogonal matching pursuit algorithm is used to position the scatterers in every range bin and the final high-resolution ISAR image can be obtained. Simulations show the effectiveness of the proposed method to deal with aforementioned problems.

Keywords

• radar imaging
• synthetic aperture radar
• image resolution
• fast Fourier transforms
• iterative methods
• echo
• radar resolution
• multichannel echoes
• equivalent single-channel ISAR signal
• missing data
• observation angle
• adjacent sensors
• interpolation
• long observation time
• improved cross-range resolution image
• range bin
• final high-resolution ISAR image
• OMP method
• distributed inverse synthetic aperture radar technique
• multiple virtual sensors