Time-space processing for small ship detection in SAR

Evan Frenklak; Yi Yao; Nhon Trinh; Keith Kastella

doi:10.1117/12.2632000

27 May 2022 Time-space processing for small ship detection in SAR

Evan Frenklak, Yi Yao, Nhon Trinh, Keith Kastella

Proceedings Volume 12108, Radar Sensor Technology XXVI; 121080W (2022) https://doi.org/10.1117/12.2632000
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Conference Poster

Abstract

This paper presents a new 3D time-space detector for small ships in single look complex (SLC) synthetic aperture radar (SAR) imagery, optimized for small targets around 5-15 m long that are unfocused due to target motion induced by ocean surface waves. Imagery is decomposed into subapertures to form a time sequence of images and the 3D power spectral density (PSD) is evaluated. Within the PSD, the response due to wave clutter is concentrated near low frequency and wavenumber relative to the target response. The clutter spectrum is estimated from collected training data and used to whiten data for cells under test (CUT). The time-space extent of the target PSD is estimated using a generic small target point-scattering model obtained from simulated data using a computer-aided design (CAD) model of a 10 m target under moderate surface conditions that is noncoherently averaged over target heading and speed. The target PSD estimate is used as a template and applied to the whitened, magnitude-detected CUT, forming a test statistic. Experiments on RADARSAT2 data demonstrate improvement over a simple power detector of 2-6 dB that is robust to both clutter and target conditions.

Citation Download Citation

Evan Frenklak, Yi Yao, Nhon Trinh, and Keith Kastella "Time-space processing for small ship detection in SAR", Proc. SPIE 12108, Radar Sensor Technology XXVI, 121080W (27 May 2022); https://doi.org/10.1117/12.2632000

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