Employment of Arbitrary Rigid Object Motion Autofocus to Conduct Moving Target Detection in Maritime Environments
Abstract
Synthetic aperture radar (SAR) imagery is a valuable tool used to conduct maritime surveillance. Ship movement induces azimuthal smearing in acquired radar images that can be exploited by autofocusing algorithms to perform moving target detection (MTD). Traditional autofocusing algorithms, such as phase gradient autofocus (PGA), assume linear movement of targets within a radar scene. The pitch and roll of surface vessels may be better modeled using arbitrary rigid object motion autofocus (AROMA), which employs a physical signal model designed to account for nonlinear translational and rotational target motion. AROMA uses this model to estimate and compensate for phase errors induced by non-linear target motion and generates an autofocused image as if the target were stationary. Analyzing autofocused imagery of a moving target compared to the original image results in a significant sharpness increase. Patches within an input radar image can be evaluated by sliding an interrogating window across the scene in a raster pattern.Autofocusing algorithms are used on each patch with the sharpness ratios of the pre- and post-autofocused images measured against a threshold to indicate the presence of a moving target. The detection and false alarm rates of the AROMA-based MTD algorithm are evaluated against traditional MTD autofocusing methods in both measured and simulated datasets to observe if the 3D modeling of AROMA exhibits improved detection performance over the traditional PGA.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2023
- Accession Number
- AD1213131
Entities
People
- Evan S Campbell
Organizations
- Naval Postgraduate School