Near Real Time Suspect Vessel Identification System

Transcription

1 Near Real Time Suspect Vessel Identification System Sónia Pelizzari António Rocha, Paulo Carmo, Ricardo Pereira, 23 th January 2008

2 Acknowledgments The Portuguese Navy: for using and testing the system and for providing the resources needed for validation Port of Lisbon: for providing AIS/VTS Portuguese Fishery Inspection Agency: for providing VMS The European Space Agency: for all the support, in special for sample images at early stages of the development of the SVI System and for the acceptance of a CAT-1 proposal for NRT image delivery over the Portuguese coast The Joint Research Center: for have given access to ENVISAT and RADARSAT-1 data from the DECLIMS ECfunded FP5 project.

3 Contents Global Vision of the Suspect Vessel Identification (SVI) System Main SVI System components The SVI Detector and Classifier The SVI Correlator The SVI Operational Service The Data Set Main Results Detection and Classification Validation Conclusions and Future Work

4 Global Vision of the SVI System The service chain of the SVI system is composed by 4 major blocks

5 SVI Data Ingestion RADARSAT ERS-2 ENVISAT TerraSAR-X SVI System ALOS AIS VTS VMS LRIT SatAIS COSMO-Skymed Satellite Data is received in NRT per ftp from ESA Maspalomas and DLR Neustrelitz stations 5

6 SVI Data Extraction Prescreening Discrimination The data extraction step consists of several stages, in line with currently available state-of-the-art VDC algorithms

7 SVI Value Addition The SVI Correlator will be in charge of integrating the EO and non-eo data and placing the applicable information in a structured way in the SVI database.

8 SVI Dissemination Downloadable kmz and text files A supporting GIS enabled SVI web portal Phone, Fax,

9 SVI Detector and Classifier: the Detection The detector is able to run fully automatically or under the supervision of a SAR specialist, in manual mode.

10 SVI Detector and Classifier: the Detection decreasing false alarm rates Based on the methodology applied in the SUMO software a template matching procedure designed to match the appearance of ships in SAR imagery calculate mean μ and standard deviation σ and set T1 T2 and T3 heuristically: T1 = μ + 3*σ T2 = μ + 1.9*σ T1 = μ + 1.4*σ a pixel is a detection if: > T1 and > T2 and > T3

11 SVI Detector and Classifier: the Classification Ellipse Fit Size and heading estimation velocity: 7.5 ms -1 target dir: 347.5º length: 147 m width: 42.5 m

12 SVI Correlator interpolates the non-eo information available in the database to the date/time of the satellite acquisition. automatically find matches between the vessels identified in a SAR image and the available non-eo information. match is performed within a set of criteria that can be configured

13 SVI Correlator After matching, vessels are assigned different correlation types: non-suspect vessels (also called positives): vessels detected by SAR that have been matched to AIS, VTS or VMS; suspect vessels: vessels detected by SAR that have not been matched to AIS, VTS or VMS; false positives: vessels detected by SAR, that were in the range of an active VTS system but which are not matched in the VTS data. false negatives: all vessels which were not detected by SAR but which were detected by AIS, VTS or VMS. AIS and VMS data are considered to be cooperative sources VTS is considered non-cooperative

14 The SVI Operational Service The SVI system has been in use for six months, over the Portuguese coast, as part of the MARISS project operational service (July- December 2007). The Data Set: Coverage from 29 th Aug. to 21 st of Sept AIS provided by Lisbon port (blue) VMS data provided by the Portuguese Fishery Inspectorate (red) 132 SAR images ordered, 104 received and processed 30.7% with AIS, 3.8% with VMS

15 The SVI Operational Service Results: Date Acquisition Hour (UTC) # SAR detections # Vessels w/ AIS # Positive detections 29 Aug 22:55: Aug 22:55: Sep 11:20: Sep 11:20: Sep 11:17: Sep 11:17: results obtained for the period of 29 th of August to 21 st September, 2007

16 Results: The SVI Operational Service

17 Detection Validation: using AIS The SVI Operational Service In late December 2007, a supertanker, named New Vision with a length of 334 meters, had some technical problems caused by a storm in North Sea while he was carrying tons of oil between Norway and Canada. During more than two weeks it was lying off the coast of Portugal, near Sines.

18 Detection Validation: using in-situ data On 7 th of August 2007, Pereira D Eça corvette was placed inside the covered area at the acquisition time by the Portuguese Navy. This corvette has a length of 85 meters and a maximum speed of 22 knots. The corvette has been detected by the SVI system.

19 Classification Validation: using AIS ERS-2 image from 28/12/2007 acquired at 22:53:39 in front of Lisbon

20 Classification Validation: using AIS Vessel Coords. Parameters AIS Classification 38º -9.67º velocity ms -1 (21.3 knots) ms -1 target direction 347.5º º length m width m 38.14º -9.67º velocity 6.38 ms -1 (12.4 knots) 7.54 ms -1 target direction 344º 347.5º length A+B = 280 m m width C+D = 46 m 42.5 m

21 Conclusions EDISOFT has developed a pre-operational NRT system for providing value added vessel detection and classification products through a GIS enabled web portal; the service has been provided in NRT in 2007 to the Portuguese users in the scope of the GMES MARISS project; integration has been performed with AIS and VMS, with promising results; first validation activities for detection and classification methods have been undertaken; ERS-2 has proven to be a valuable data source for vessel detection in spite of its incidence angle and polarisation features that are not optimal for this task.

22 Future Work Undertake more validation campaigns (with other types of imagery, with VMS polling and with more in-situ data) focusing in ENVISAT and RADARSAT data; Enhance the correlation algorithm; Test new classification methodologies, more suitable to maritime traffic in Portuguese coast; Extend the system to other imagery sources like RADARSAT (finalising), ALOS, TerraSAR-X and COSMO-SKYMED; Consider the possibility of having a more close integration with the Navy own systems e.g.: the ship as info provider; Installation of NRT X-band reception capability in the Santa Maria ground station for ENVISAT and RADARSAT (ongoing); Incorporate meteorological data into the algorithms (ongoing conversations with the Portuguese Meteorological Institute).

23 Thank you for your attention EDISOFT company contacts: Address: Rua Quinta dos Medronheiros - Lazarim, Apartado Monte Caparica Caparica, Portugal Web site: edisoft@edisoft.pt Phone number: