An automatic ship and ship wake detection system for spaceborne SAR images is described and assessed The system is designed for coastal regions with eddies, fronts, waves and swells The system uses digital terrain models to simulate synthetic SAR images to mask out land areas Then a search for ship targets is performed followed by wake search around detected ship candidates Finally, a homogeneity test and wake behavior test are performed which reduces the number of false alarms substantially The system is demonstrated with ERS-1 SAR images and its performance is assessed using Seasat and ERS-1 images No other information about the ships was available, hence, the basis for the assessment is through comparison with human visual interpretation of the same data The number of lost ships (ship-like targets) was 7-8% for both Seasat-A and ERS-1 No false ships were detected The number of lost or false wakes (wake-like features) was higher in ERS-1 images than in Seasat-A images and was nearly 15% Taking into account the extremely strong variations in sea state in some of the selected scenes, the automatic detection performance is considered to be very good In addition, the requirement of analyzing a 3-look ERS-1 scene of 100 km/spl times/100 km in less than eight minutes has been achieved on a workstation

An automatic ship and ship wake detection system for spaceborne SAR images in coastal regions

Presents a Radon transform-based approach to the detection of ship wakes in synthetic aperture radar (SAR) images. The key element of this technique is a localization of the Radon transform, whereby the intensity integration is performed over short line segments rather than across the entire image. A linear feature detection algorithm, which utilizes this localized Radon transform, is then developed. In this algorithm, referred to as the feature space line detector algorithm, the transform space is subjected to processing which serves to isolate and locate the response of linear features and suppresses the response of false alarms. This algorithm is tested on both synthetic images corrupted by various levels of Weibull multiplicative noise and on actual SAR images of ship wakes. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions. >

Localized Radon transform-based detection of ship wakes in SAR images

RESUMENous avons utilise une approche statistique de detection de cibles ponctuelles sur fond bruite pour caracteriser la performance prevue du RSO de RADARSAT (bande C, Polarisation HH) pour la detection des navires. Cette technique sera egalement utilisee pour comparer la performance des divers modes et faisceaux du RSO de RADARSAT pour la detection des navires. La detection de navires de plus petite dimension est possible lorsque la vitesse du vent est plus faible, que l'angle d'incidence est plus fort ou que la resolution est plus fine. Le mode ScanSAR a faisceau etroit distal est pressenti comme etant le meilleur compromis entre la couverture spatiale et la probabilite de detection. Nous presentons une validation quantitative de ces modeles de prediction selon les donnees obtenues lors d'une campagne qui a eu lieu au large de Halifax N.-E. au cours des mois de mars et avril 1996. A l'aide d'instruments sur bouees, des mesures du vent et des vagues ont ete prises au moment de l'acquisition d'images RS...

Ship Detection by the RADARSAT SAR: Validation of Detection Model Predictions

RESUMENOAA/NESDIS a initie le programme “Alaska SAR Demonstration” dont l'objectif est de faire la demonstration du potentiel des images RSO en bande C de RADARSAT-1 a fournir une information utile et en temps opportun sur l'environnement et pour la gestion des ressources pour des utilisateurs en Alaska. Un des produits developpes dans le cadre du programme est une liste de localisations des navires. Cet article decrit l'algorithme developpe pour generer ce produit par le biais de la detection automatique des navires basee sur des changements dans les statistiques locales. A l'aide d'images a basse resolution (100 metres d'espacement), on demontre que l'on peut detecter des navires de dimension superieure a 35 metres (representant 105 navires sur un total de 272 dans la zone test) avec un taux de fausse alerte de 0,01% pour une seule detection. Avec des images a haute resolution (50 metres d'espacement), on peut detecter des navires d'une dimension superieure a 32 metres (representant 124 navires sur 272)...

Automatic Detection of Ships in RADARSAT-1 SAR Imagery

Synthetic aperture radar (SAR) images of ships and their wakes frequently exhibit long dark and bright streaks. Some of them can be attributed to the Kelvin wavewake and others to the turbulent and bright narrow V-wake. The wakes contain information about the ship. The present work deals with estimates of the ship beam and its velocity by processing SAR images of the Kelvin and turbulent wakes. It is assumed that the ship moves along a straight path with constant speed. For the detection of the linear features of the ship wake, the fast discrete Radon transform is employed. Once the turbulent wake is detected, the ship beam is estimated by a novel method that exploits the expansion of the turbulent wake aft a ship. A semiempirical relation between the ship beam and the width of its turbulent wake is derived and analyzed. An algorithm for estimating the width of the turbulent wake in SAR images and the ship beam is developed. The spectrum of ship-generated waves along the Kelvin cusp-lines is discussed. Processing of the lines, pertaining to the Kelvin wake bounds, and analysis of the spectral peaks enables to estimate the ship speed. Numerical examples of processing of airborne SAR images are provided.

The speed and beam of a ship from its wake's SAR images

A moving ship produces a set of waves in a characteristic linear "V" pattern. This pattern, or some of its components, can often be detected in ocean imagery produced by satellite-borne Synthetic Ap- erture Radar (SAR) sensors operating at L-band. Some wake compo- nents, notably the turbulent wake, may extend for 5-15 km behind the ship. As ship wake detection can provide information such as ship di- rection and speed, the detection of these wakes can play an important role in satellite surveillance of shipping. Described is research done on the use of the Radon transform to automatically detect ship wakes .in Seasat ocean imagery. The objective of the research was twofold: to automatically detect ship wakes and to differentiate ship wakes from other linear ocean features produced by the underwater topography and existing sea conditions. An ADA (Automatic Detection Algorithm) based on the Radon transform was developed and applied to the Seasat imagery. The basic system performs the Radon transform of the SAR image, then detects bright and dark peaks produced in the transform by wakes (or other linear features) in the image. As the Radon trans- form essentially integrates the image intensity along every straight line through an image, each integral becomes one element in transform space. This integration process averages out the intensity fluctuations due to noise, thereby increasing the signal-to-noise ratio of the feature of interest in the transform space relative to that in the original image. A number of additional processing techniques were developed and tested to improve the PD (probability of detection) and reduce the PFA (probability of false alarm). To date, the use of an ADA, which com- bines a high-pass filter followed by a normalized Radon transform and a Wiener filter, has been shown to reliably distinguish wake peaks from false alarms. Keywords-Wake, Radon, radar.

J.A. Dixon

Papers

Application Of Radon Transform Techniques To Wake Detection In Seasat-A SAR Images