Journal ArticleDOI
Ship detection based on morphological component analysis of high-frequency surface wave radar images
TLDR
The issue of ship detection from HFSWR images is introduced and an overview of the MCA approach is given, the algorithm used for target detection is depicted, and comparisons with a classical constant false-alarm rate (CFAR) detection method are given.Abstract:
In this study, high-frequency surface wave radar (HFSWR) is considered for target detection. These systems, commonly used for oceanographic purposes, are of interest in maritime surveillance because of their long range detection capabilities compared with conventional microwave radar. Unfortunately, the received signals are strongly polluted by different noises. In this contribution a target detection method based on morphological component analysis (MCA) is investigated. Basically, MCA is a source separation technique based on multiscale transforms and the sparsity representation. The authors goal is to extract the target signatures from the range-Doppler image and then to take the final decision through a simple rule. This study introduces the issue of ship detection from HFSWR images and gives an overview of the MCA approach. Then, the algorithm used for target detection is depicted. Comparisons with a classical constant false-alarm rate (CFAR) detection method, the so-called greatest of cell averaging-CFAR, are given through receiver operating characteristic curves computed from simulated data.read more
Citations
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Journal ArticleDOI
Clutter Removal in Ground-Penetrating Radar Images Using Morphological Component Analysis
Eyyup Temlioglu,Isin Erer +1 more
TL;DR: This letter proposes a sparse model for differentiating the target and the clutter using appropriate dictionaries based on morphological component analysis (MCA), and calculated sparse coefficients and corresponding dictionaries are used to reconstruct the clutter and the target components.
Journal ArticleDOI
Automatic Detection of Ship Targets Based on Wavelet Transform for HF Surface Wavelet Radar
TL;DR: Experimental results show that the proposed approach can automatically extract ship targets effectively for range Doppler images with complex background, and has a better target detection performance than the previous wavelet-based algorithm, thereby providing a new reliable image processing-based method of ship target detection for HFSWR.
Journal ArticleDOI
Parametric detector in the situation of mismatched signals
TL;DR: In this paper, an effective parametric detector is proposed, which encompasses Kelly's generalised likelihood ratio test (GLRT), adaptive matched filter (AMF) and adaptive beamformer orthogonal rejection test (ABORT) as its three special cases.
Journal ArticleDOI
Simulation and Ship Detection Using Surface Radial Current Observing Compact HF Radar
TL;DR: This paper proposes an effective method of improving ship detection performance of a compact high-frequency (HF) radar system which has been primarily optimized for observing surface radial current velocities and bearings.
Journal ArticleDOI
A Novel Ship Target Detection Algorithm Based on Error Self-adjustment Extreme Learning Machine and Cascade Classifier
TL;DR: This paper presents a ship target detection algorithm to overcome the problems above by using a two-stage cascade classification structure based on ES-ELM, which outperforms most of the state-of-the-art methods for detection accuracy and computational efficiency.
References
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Journal ArticleDOI
Fast Discrete Curvelet Transforms
TL;DR: This paper describes two digital implementations of a new mathematical transform, namely, the second generation curvelet transform in two and three dimensions, based on unequally spaced fast Fourier transforms, while the second is based on the wrapping of specially selected Fourier samples.
Journal ArticleDOI
Radar CFAR Thresholding in Clutter and Multiple Target Situations
TL;DR: A CFAR method is discussed using as the CFAR threshold one single value selected from the so-called ordered statistic, which has some advantages over cell averaging CFAR, especially in cases where more than one target is present within the reference window on which estimation of the local clutter situation is based.
Book ChapterDOI
Redundant Multiscale Transforms and Their Application for Morphological Component Separation
TL;DR: This chapter presents an alternative deterministic methodology, based on sparsity, toward the problem of morphological component analysis (MCA) and anchors this method with some conclusive theoretical results, essentially guaranteeing successful separation under some conditions.
Journal ArticleDOI
Wellen Radar (WERA): a new ground-wave HF radar for ocean remote sensing
TL;DR: The Wellen Radar (WERA) as discussed by the authors was developed at the University of Hamburg to measure surface currents and wave spectra by transmitting frequency-modulated continuous wave chirps instead of continuous wave (CW) pulses.
Book
Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity
TL;DR: This book presents the state of the art in sparse and multiscales image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multISCale transforms based on the median and mathematical morphology operators.