Data association techniques for near-contemporaneous SAR and AIS datasets from NovaSAR-1

In this research the best techniques of fusion for near-contemporaneous Synthetic Aperture Radar (SAR) and Automatic Identification System (AIS) datasets are studied to simulate the expected performance from NovaSAR-1. Specifically, data association techniques are quantitatively compared by performing a series of Monte Carlo tests. The evaluation has been carried out using a satellite-based AIS dataset acquired from the English Channel on 07 June 2016, and SAR ship detections are simulated by reckoning the AIS dataset forward in time along a geodesic on a WGS84 reference ellipsoid. Accurate data association is achieved using an m-best multidimensional assignment technique, which is consistent with being used in an operational environment, especially in high-density shipping areas

Data association techniques for near-contemporaneous SAR and AIS datasets from NovaSAR-1

In this research the best techniques of fusion for near-contemporaneous Synthetic Aperture Radar (SAR) and Automatic Identification System (AIS) datasets are studied to simulate the expected performance from NovaSAR-1. Specifically , data association techniques are quantitatively compared by performing a series of Monte Carlo tests. The evaluation has been carried out using a satellite-based AIS dataset acquired from the English Channel on 07 June 2016, and SAR ship detections are simulated by reckoning the AIS dataset forward in time along a geodesic on a WGS84 reference el-lipsoid. Accurate data association is achieved using an m-best multidimensional assignment technique, which is consistent with being used in an operational environment, especially in high-density shipping areas