Detection of Wind Turbines in Intertidal Areas Using SAR Polarimetry

The detection of wind turbines in a strong clutter background is analyzed at variance of polarimetric synthetic-aperture radar (SAR) configurations. The area of interest is the intertidal zone near Jiangsu, China and two detectors are used, the polarimetric notch filter (PNF) and a change detector that optimizes the ratio between covariance matrices. The detection performance is quantitatively analyzed using the receiver operating characteristic (ROC) curve, while the scattering mechanisms that characterize wind turbines are analyzed using the Yamaguchi decomposition. Experimental analysis shows that: 1) wind turbines result in a nontrivial scattering mechanism and 2) full-polarimetric measurements achieve the best detection performance independently of the two detectors

Offshore Metallic Platforms Observation Using Dual-Polarimetric TS-X/TD-X Satellite Imagery: A Case Study in the Gulf of Mexico

Satellite-based synthetic aperture radar (SAR) has been proven to be an effective tool for ship monitoring. Offshore platforms monitoring is a key topic for both safety and security of the maritime domain. However, the scientific literature oriented to the observation of offshore platforms using SAR imagery is very limited. This study is mostly focused on the analysis and understanding of the multipolarization behavior of platforms’ backscattering using dual-polarization X-band SAR imagery. This study is motivated by the fact that under low incidence angle and moderate wind conditions, copolarized channels may fail in detecting offshore platforms even when fine-resolution imagery is considered. This behavior has been observed on both medium- and high-resolution TerraSAR-X/TanDEM-X SAR imagery, despite the fact that platforms consist of large metallic structures. Hence, a simple multipolarization model is proposed to analyze the platform backscattering. Model predictions are verified on TerraSAR-X/TanDEM-X SAR imagery, showing that for acquisitions under low incidence angle, the platforms result in a reduced copolarized backscattered intensity even when fine resolution imagery is considered. Finally, several solutions to tackle this issue are proposed with concluding remark that the performance of offshore observation

Change detection in SAR time-series based on the coefficient of variation

This paper discusses change detection in SAR time-series. Firstly, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Then several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Then other criteria based on ratios of coefficients of variations are proposed to detect long events such as construction test sites, or point-event such as vehicles. These detection methods are evaluated first on theoretical statistical simulations to determine the scenarios where they can deliver the best results. Then detection performance is assessed on real data for different types of scenes and sensors (Sentinel-1, UAVSAR). In particular, a quantitative evaluation is performed with a comparison of our solutions with state-of-the-art methods

Polarization Decomposition Algorithm for Detection Efficiency Enhancement

In the paper, a new polarization decomposition of the optimal detection algorithm in the partially homogeneous environment is presented. Firstly, the detectors Matched Subspace Detector (MSD) and Adaptive Subspace Detector (ASD) are adopted to deal with detection problems in the partially homogeneous environment. Secondly, the fitness function with polarization parameters is equivalently decomposed to enhance time detection efficiency in the algorithm. It makes the multiplication number of the fitness function from square to a linear increase along with the increase in parameters. Simulation results indicate that the proposed decomposition is much more efficient than direct use of the fitness function

Auto-regressive model based polarimetric adaptive detection scheme part I: Theoretical derivation and performance analysis

This paper deals with the problem of target detection in coherent radar systems exploiting polarimetric diversity. We resort to a parametric approach and we model the disturbance affecting the data as a multi-channel autoregressive (AR) process. Following this model, a new polarimetric adaptive detector is derived, which aims at improving the target detection capability while relaxing the requirements on the training data size and the computational burden with respect to existing solutions. A complete theoretical characterization of the asymptotic performance of the derived detector is provided, using two different target fluctuation models. The effectiveness of the proposed approach is shown against simulated data, in comparison with alternative existing solutions

Ship detection with spectral analysis of synthetic aperture radar: a comparison of new and well-known algorithms

The surveillance of maritime areas with remote sensing is vital for security reasons, as well as for the protection of the environment. Satellite-borne synthetic aperture radar (SAR) offers large-scale surveillance, which is not reliant on solar illumination and is rather independent of weather conditions. The main feature of vessels in SAR images is a higher backscattering compared to the sea background. This peculiarity has led to the development of several ship detectors focused on identifying anomalies in the intensity of SAR images. More recently, different approaches relying on the information kept in the spectrum of a single-look complex (SLC) SAR image were proposed. This paper is focused on two main issues. Firstly, two recently developed sub-look detectors are applied for the first time to ship detection. Secondly, new and well-known ship detection algorithms are compared in order to understand which has the best performance under certain circumstances and if the sub-look analysis improves ship detection. The comparison is done on real SAR data exploiting diversity in frequency and polarization. Specifically, the employed data consist of six RADARSAT-2 fine quad-polacquisitions over the North Sea, five TerraSAR-X HH/VV dual-polarimetric data-takes, also over the North Sea, and one ALOS-PALSAR quad-polarimetric dataset over Tokyo Bay. Simultaneously to the SAR images, validation data were collected, which include the automatic identification system (AIS) position of ships and wind speeds. The results of the analysis show that the performance of the different sub-look algorithms considered here is strongly dependent on polarization, frequency and resolution. Interestingly, these sub-look detectors are able to outperform the classical SAR intensity detector when the sea state is particularly high, leading to a strong clutter contribution. It was also observed that there are situations where the performance improvement thanks to the sub-look analysis is not so noticeable

Validating a notch filter for detection of targets at sea with ALOS-PALSAR data: Tokyo Bay

The surveillance of maritime areas is a major topic for security aimed at fighting issues as illegal trafficking, illegal fishing, piracy, etc. In this context, Synthetic Aperture Radar (SAR) has proven to be particularly beneficial due to its all-weather and night time acquisition capabilities. Moreover, the recent generation of satellites can provide high quality images with high resolution and polarimetric capabilities. This paper is devoted to the validation of a recently developed ship detector, the Geometrical Perturbations Polarimetric Notch Filter (GP-PNF) exploiting L-band polarimetric data. The algorithm is able to isolate the return coming from the sea background and trigger a detection if a target with different polarimetric behavior is present. Moreover, the algorithm is adaptive and is able to account for changes of sea clutter both in polarimetry and intensity. In this work, the GP-PNF is tested and validated for the first time ever with L-band data, exploiting one ALOS-PALSAR quad-pol dataset acquired on the 9th of October 2008 in Tokyo Bay. One of the motivations of the analysis is also the attempt of testing the suitability of GP-PNF to be used with the new generations of L-band satellites (e.g. ALOS-2). The acquisitions are accompanied by a ground truth performed with a video survey. A comparison with two other detectors is presented, one exploiting a single polarimetric channel and the other considering quad-polarimetric data. Moreover, a test exploiting dual-polarimetric modes (HH/VV and HH/HV) is performed. The GP-PNF shows the capability to detect targets presenting pixel intensity smaller than the surrounding sea clutter in some polarimetric channels. Finally, the quad-polarimetric GP-PNF outperformed in some situations the other two detectors