ISAR imaging of sea vessels with complex 3-D motion and varying sea states
ISAR is a radar signal processing technique that produces a radar down range and cross-range image of a object of interest. Challenges in forming an ISAR image include motion compensation [Wehner 1995], blurring of the image due to 3D motion [Abdul Gaffar and Nel 2007], non-uniform rotation motion [Wong et al. 2003], range walk due to rotation motion [Lipps & Kerr 1998] and optimum imaging time [Rihaczek and Hershkowitz 1999], [Gibbins et al. 1999], and system effects such as range side lobes, Doppler side lobes and antenna aberrations [Wehner 1995]. In a previous CSIR ISAR measurement trial (2006) substantial blurring was seen in motion compensated [based on Li et al. 2001] ISAR images suspectedly due to the complex 3-D motion of small boats in rough seas [Abdul Gaffar and Nel 2006], leaving a question of how to predict the optimum time during target track to generate an image with minimum blur, leading to situation where ISAR movie sequences generated using conventional motion compensation techniques only contain a few images of high quality. It is believed that a Persistent Maritime Area Surveillance (PMAS) system with its long dwell time and high revisit rate could enable the generation of high quality, correctly posed ISAR imagery by properly selecting the imaging instant [Pastina 2003] when the target axis of rotation is orthogonal to the radar line of sight.
The research work that will be carried out involves the development, evaluation and comparison of Inverse Synthetic Aperture Radar (ISAR) algorithms and their motion compensation aspects that are suited to the various conditions of sea state and vessel sizes. This includes approaches to estimate optimal time intervals for ISAR image formation. The object of this research can be achieved by breaking up the problem into the following tasks:
-Research, understand and implement existing algorithms that estimate the optimal time intervals for ISAR image formation
-Development and evaluation of a proposed algorithm to estimate the optimum interval to form the ISAR image with minimum blurring due to complex motion
-Compare performance of proposed algorithm with existing algorithms in the literature in order to understand differences and limitations.
[Abdul Gaffar and Nel 2007] Abdul Gaffar, M.Y., Nel, W. (2007), Investigating the effect of target's time-varying axis of rotation on ISAR image distortion, submitted to IEE Radar Conference 2007.
[Abdul Gaffar & Nel 2006] Abdul Gaffar, M.Y., Nel, W. (2006), Towards Inverse Synthetic Aperture Radar (ISAR) for Small Sea Vessels, 2nd Ledger Conference, Cape Town.
[Gibbins et. al. 1999] Gibbins, D., Symons, J., Haywood, R. (1999), Ship motion estimation from ISAR data, In Proceedings of ISSPA, Brisbane, Australia, pp. 333-336.
[Lipps & Kerr 1998] Lipps, R., Kerr, D. (1998), Polar reformatting for ISAR imaging, in Proceedings of IEEE National Radar Conference, Texas, Dallas, pp. 275-280.
[Li et. al. 2001] Li, J., Wu, R., Chen, V. C. (2001), Robust autofocus algorithm for ISAR imaging of moving targets, IEEE Transactions on Aerospace and Electronic Systems, vol 37, pp. 1056-1069.
[Pastina et. al. 2003] Pastina, D., Montanari, A., Aprile, A., (2003), Motion estimation and optimum time selection for ship ISAR imaging, In Proceedings of the IEEE Radar Conference, pp. 7-14.
[Rihaczek & Hershkowitz 1999] Rihaczek, A.W., Hershkowitz, S.J. (1999), Choosing imaging intervals for identification of small ships, SPIE Proceeding on Radar Processing, Technology and Applications VI, Vol. 810, pp. 139-148.
[Wehner 1995] Wehner, D.R. (1995), High-Resolution Radar, second edition, Norwood, MA, Artech House.
[Wong et. al. 2003] Wong, S. K., Duff, G., Riseborough, E. (2003), ISAR Image Distortion due to Small Perturbed Motion and Restoration of Distorted Images by Time-Frequency Analysis, Proceedings of SPIE, Vol. 5102, Florida, USA, pp. 200-212.