A wavelength-resolution sar change detection method based on image stack through robust principal component analysis

• Recently, it was demonstrated that low-frequency wavelength-resolution synthetic aperture radar (SAR) images could be considered to follow an additive mixing model due to their backscatter characteristics. This simplification allows for the use of source separation methods, such as robust principal component analysis (RPCA) via principal component pursuit (PCP), for detecting changes in those images. In this manuscript, a change detection method for wavelength-resolution SAR images based on image stack through RPCA is proposed. The method aims to explore both the temporal and flight heading diversity of a set of wavelength-resolution multitemporal SAR images in order to detect concealed targets in forestry areas. A heuristic based on three rules for better exploring the RPCA results is introduced, and a new configurable parameter for false alarm reduction based on the analysis of image windows is proposed. The method is evaluated using real data obtained from measurements of the ultrawideband (UWB) very high-frequency (VHF) SAR system CARABAS-II. Experiments for stacks of four and seven reference images are conducted, and the use of reference images acquired with different flight headings is explored. The results indicate that a gain in performance can be achieved by using large image stacks containing, at least, one image of each possible flight heading of the data set, which can result in a probability of detection (PD) above 99% for a false alarm rate (FAR) as low as one false alarm per three square kilometers. Furthermore, it is demonstrated that high PD and low FAR can be achieved, also considering images from similar flight headings as reference images. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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

CARABAS-II

Change detection

Robust principal component analysis

Synthetic aperture radar

Alarm systems

Errors

Image analysis

Source separation

Ultra-wideband (UWB)

Configurable parameter

False alarm reductions

Multi-temporal SAR images

Principal Components

Probability of detection

Synthetic aperture radar (SAR) images

Wavelength resolution

Radar imaging

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