Abstract
The detection of ship and estimation of its characteristics has its significance in tracking these sea vessels for surveillance. It also has its importance as an ancillary information for marine applications like oil spill detection and its source tracking. This paper is an aspiration towards exploring the strength of RISAT-1 data retrieved in circular transmit linear receive mode. We propose a method to select the detected ship and get the dimension estimation of the segmented ship for further decision making. The proposed method has been implemented in python and tested for various inputs. The verification of the same is done as a de-facto measure based on location or by supporting measurements obtained through Google Maps.
Highlights
Knowledge of vessel positions and types aid many applications like maritime traffic regulation, fisheries and surveillance
Ship detection can be considered as a primary problem for ocean surveillance or maritime traffic regulation
Synthetic Aperture Radar (SAR) comes out as the best tool for the said purpose according to its capabilities of all weather, day and night sensing in broad expanses
Summary
Knowledge of vessel positions and types aid many applications like maritime traffic regulation, fisheries and surveillance. Ship detection can be considered as a primary problem for ocean surveillance or maritime traffic regulation. Maritime traffic monitoring aids the fishing activities and any relevant emergency situations It may help as deciding factor for oil spill detection and classification and/or to identify illegally operating ships. Double reflection is generated by if there is correct orientation with of ocean with the radar beam and the hull. This phenomena results in returning a significant energy towards SAR receiver[2]. The problem of ship detection is simplified with polarimetric SAR, there are certain factors that impact the ship detection process significantly. The research contributions of this study are as follows: 1) Empirical analysis of polarimetric decomposition/classification for ship detection. 2) Ship Detection and Size Estimation 3) Performance analysis of RISAT-1 SAR for ship detection
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