PhD Thesis: Yunus Abdul Gaffar


Adobe-PDF-downloadAbdul Gaffar, Yunus. Ground-based ISAR imaging of cooperative and non-cooperative sea vessels with 3-D rotational motion. PhD Thesis. Department of Electrical Engineering, University of Cape Town, 2009.



Inverse Synthetic Aperture Radar (ISAR) images of sea vessels are a rich source of information for radar cross section (RCS) measurement and ship classification. However, ISAR imaging of sea vessels is a challenging task because the 3-D rotational motion of such vessels often gives rise to blurring. Blurry ISAR images are not desirable because they lead to inaccurate parameter estimation, which reduces the probability of correct classification. The objective of this thesis is to explain how 3-D rotational motion  causes blurring in ISAR imagery and to develop effective techniques for imaging cooperative and non-cooperative sea vessels for RCS measurement and ship-classification
purposes respectively.

Much research has been done to investigate the effect of 3-D rotational motion on an ISAR image under the assumption that an object’s axis of rotation is constant over the coherent processing interval (CPI). In this thesis, a new quaternion-based system model is proposed to characterise the amount of blurring in an ISAR image when a sea vessel possesses 3-D rotational motion over a CPI. Simulations were done to characterise the migration of a scatterer through Doppler cells due to the time-varying nature of the Doppler generating axis of rotation. Simulation results with realistic 3-D rotational motion show substantial blurring in the cross-range dimension of the resulting ISAR image, and this blurring is attributed to the time-varying nature of the angle of the Doppler generating axis of rotation and the object’s rotation rate over the CPI.

Sea vessels naturally possess 3-D rotational motion, even in low sea states. However, it is only a component of this motion, referred to as the image-generating Doppler component, that is useful to the ISAR imaging process. The image generating Doppler components consist of the Doppler generating axis and the effective angle of rotation. This thesis presents a new quaternion-based transformation that converts the measured attitude and position data of a sea vessel into the vessel’s Doppler generating axis and effective angular rotation rate. The proposed transformation was thus applied to the measured attitude and GPS position data of a yacht, and the results show that the quaternion-based transformation isolates the component of the 3-D rotational motion that directly influences the ISAR images. Thus, the transformation provides an alternative approach for understanding the blurring caused by 3-D rotational motion in measured ISAR images, as well as for identifying good imaging intervals for applications such as cooperative ISAR for RCS purposes.

In cooperative ISAR applications, the value of the coherent processing time window length (CPTWL) is critical because it should be short enough to limit the blurring caused by the 3-D rotational motion but at the same time long enough to ensure that the desired cross-range resolution is obtained. In this thesis, the motion-aided CPTWL selector (MACS) algorithm is proposed for selecting suitable CPTWLs for ISAR imaging of cooperative sea vessels. The suggested CPTWLs may be used to obtain motion- compensated ISAR images that have the desired medium cross-range resolution and limited blurring due to 3-D rotational motion. The proposed algorithm is applied to the measured motion data of three different classes of sea vessels: a yacht, a fishing trawler, and a survey vessel. Results show that longer CPTWLs are needed for larger vessels in order to obtain ISAR images with the desired cross-range resolution. Experimental results obtained using measured radar data show the effectiveness of the proposed algorithm. Furthermore, the suggested CPTWLs may be used to select an effective initial CPTWL for the maximum-contrast-based automatic time window selection (MC-ATWS) algorithm, proposed by Martorella and Berizzi, when it is applied to measured radar data of small vessels.

In non-cooperative ISAR applications, however, the vessel’s motion is unknown and it is a challenging task to isolate focused side-view ISAR images from a long radar recording. This thesis proposes the extended maximum-contrast based automatic time window selection (EMC-ATWS) algorithm, which is an extension of the MC-ATWS algorithm, to estimate the parameters of multiple optimum imaging intervals that produce focused side-view ISAR images of small non-cooperative vessels. The MC-ATWS algorithm and the proposed EMCATWS algorithm were therefore applied to measured radar recordings of two non-cooperative yachts. Results showed that the MC-ATWS estimated the parameters of a single optimum imaging interval that produced a highly focused ISAR image with little Doppler information, which is not desirable for ship classification. Results from the EMC-ATWS algorithm showed that the proposed technique was effective in estimating multiple optimum imaging intervals that generated highly focused side-view ISAR images, which contain useful discriminant information for ship classification.




Leave a Reply