Polarimeric SAR Ship Detection Based on Sub-Look the Decomposition Technology

Tao Zhang, Nishang Xie, Sinong Quan, Wei Wang, Feiming Wei, Wenxian Yu

2025IEEE Transactions on Radar Systems8 citationsDOI

Abstract

In the past few years, polarimetric synthetic aperture radar (PolSAR) as an advanced technology has been widely exploited to Earth observation, among which ship detection is an active research topic. Taking the sub-look decomposition technology as the basic, this paper proposes a new ship detection method abbreviated to ASM. In brief, two single-look complex (SLC) images <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I1 and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I2 are first obtained from the original PolSAR image <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O for forming the data group {<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I1, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I2}. Then, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H/A/α decomposition is performed on {<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I1, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I2} so as to yield the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H/α plane group {<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P1, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P0, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P2}, which is subsequently used to suppress sea clutter and generate another filtered data group {F1, F0, F2} that respectively corresponds to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I1, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I2. Thereafter, a new 3×3 spatial-spectral coherence difference matrix [<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ST] is further constructed by {<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F1, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F0, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F2}, wherein the spatial and spectral information are simultaneously used. Therefore, [<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ST] can effectively highlight ships from sea clutter. To verify this point, an amplitude-based ship detection metric (ASM) is finally built through multiplying the amplitude values of the terms <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ST13, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ST23, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ST33 together. Extensive experiments demonstrate that, i) [<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ST] is more appropriate for ship detection than [<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T]; ii) ASM has a better ability to improve ships’ target-to-clutter ratio (TCR) in comparison with other state-of-the-art (SOTA) methods. Last but not least, experimental results also show that, the detection performance of ASM<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R (i.e., calculating ASM along the range direction) is similar to that of ASM<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A (i.e., calculating ASM along the azimuth direction). For example, the average TCR values of ASM<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A and ASM<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R are respectively 7.5 dB and 7.06 dB higher than the second place. So, this means the frequency characteristics of ships should be considered into the practical detection process as well.

Topics & Concepts

Synthetic aperture radarClutterRemote sensingCoherence (philosophical gambling strategy)Computer scienceComputer visionInverse synthetic aperture radarArtificial intelligenceMetric (unit)Radar imagingRadarSide looking airborne radarSpeckle patternMatrix decompositionDecompositionSpeckle noiseGeologyPolarimetrySimilarity (geometry)Matrix (chemical analysis)Decomposition method (queueing theory)Interferometric synthetic aperture radarPlane (geometry)Early-warning radarTensor decompositionImage resolutionSpatial coherenceSynthetic Aperture Radar (SAR) Applications and TechniquesRemote-Sensing Image ClassificationAdvanced SAR Imaging Techniques