Improving the Estimation of Ship Length via ISAR

TL;DR

This paper introduces the ISAR AutoTrack (IAT) algorithm, which improves ship length estimation from synthetic aperture radar by accurately estimating aspect angles and reducing resource use.

Contribution

The paper presents a novel IAT algorithm that enhances ship length estimation accuracy and efficiency using adaptive motion compensation and autofocus methods.

Findings

IAT achieves ship length estimation within 10% accuracy across all azimuth angles.

The algorithm reduces radar resource requirements for ship tracking.

IAT remains effective despite ship maneuvers and environmental noise.

Abstract

A method for estimating the aspect angle of ships at sea from an ISAR is developed. The ISAR AutoTrack (IAT) algorithm uses the information from the adaptive motion compensation velocity to improve the tracker estimation of the ship aspect angle and thus to improve the estimation of ship length. The IAT is based on classical methods of autofocus for synthetic aperture radar. The average mocomp velocity yields the error in the in-range component of the ship velocity; the linear time trend of the velocity determines the cross-range component of the ship velocity. The IAT has two methods for implementing the algorithm, the Search and Analytical methods. Both methods benefit from an intelligent smoothing process that removes system errors, random noise, and ocean waves. The goal of the IAT is to measure ship length to within 10 percent over all azimuth angles and ranges relative to the aircraft and for (unsigned) aspect angles from 5 to 85 degrees. Using the IAT allows a major reduction in the radar resources dedicated to tracking; and since the IAT creates its estimates during the ISAR time window it is unaffected by ship maneuvers. Recommendations for further development and testing of the IAT are presented.