Change detection in UWB VHF SAR images exploiting flight heading diversity through robust principal component analysis

• Change detection methods are frequently associated with wavelength-resolution synthetic aperture radar (SAR) images for foliage-penetrating (FOPEN) applications (e.g., the detection of concealed targets in forestry areas), being a research topic of interest over the last decades. The challenge associated with the design of automated change detection techniques goes beyond performing the target detection. It is also related to clutter suppression aiming at a low false alarm rate (FAR). The problem of detecting targets and removing content in SAR data can be treated as an unsupervised signal separation problem, usually referred to as blind source separation (BSS). Additionally, low frequency wavelength-resolution SAR images can be considered to follow an additive separation model due to their backscatter characteristics. In this context, it is possible to explore robust principal component analysis (RPCA) as a source-separation method for problems in which the mixing model is additive and two-dimensional, as the interest SAR images. This paper presents a change detection method for wavelengthresolution SAR images based on the RPCA via principal component pursuit (PCP), considering the use of small image stacks to explore the data diversity from measurements of different flight headings. The proposed method is evaluated using real data obtained from measurements of the ultrawideband (UWB) very high frequency (VHF) SAR system CARABAS II. The experimental results show that the proposed method can achieve a high probability of detection (PD) values for a low FAR (i.e., PD of 0.98 for a FAR of 0.41 objects per square kilometer). Finally, discussions regarding the use of the RPCA in change detection methods and the diversity gains are provided in the paper. © SPIE. Downloading of the abstract is permitted for personal use only.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

Blind source separation

Change detection

Robust principal component analysis

Synthetic aperture radar

Additives

Echo suppression

Image analysis

Remote sensing

Ultra-wideband (UWB)

Clutter suppression

Detecting target

Principal Components

Signal separation problems

Synthetic aperture radar (SAR) images

Very high frequency

Wavelength resolution

Radar imaging

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