Session

Technical Session III: Science/Mission Payloads

Location

Utah State University, Logan, UT

Abstract

The NovaSAR and SSTL S1-4 satellites were launched into a 580 km sun-synchronous orbit on 16th September 2018. NovaSAR is an S-band Synthetic Aperture Radar (SAR) platform, and SSTL S1-4 hosts a multi-spectral (RGB, NIR) and panchromatic electro-optical (EO) high-resolution payload1. As the satellites are adjacent in orbit, with NovaSAR leading SSTL S1-4 by ~15 minutes, this provides an opportunity to demonstrate the benefits of using SAR and EO data together. The key demonstration principles are: to show the complementary nature of near-contemporaneous SAR and EO data, tipping and cueing opportunities of a tandem sensor, and to demonstrate the superiority of one technology for a specific application. The ability to undertake enhanced vessel detection using machine learning algorithms, to use bathymetry with EO and SAR imagery to get a more complete picture, and to detect oil spills in SAR imagery have been demonstrated. This proves the capability of the technologies, and their strengths as joint and separate data sources, helping to inform future mission concepts.

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Aug 1st, 12:00 AM

NovaSAR and SSTL S1-4: SAR and EO Data Fusion

Utah State University, Logan, UT

The NovaSAR and SSTL S1-4 satellites were launched into a 580 km sun-synchronous orbit on 16th September 2018. NovaSAR is an S-band Synthetic Aperture Radar (SAR) platform, and SSTL S1-4 hosts a multi-spectral (RGB, NIR) and panchromatic electro-optical (EO) high-resolution payload1. As the satellites are adjacent in orbit, with NovaSAR leading SSTL S1-4 by ~15 minutes, this provides an opportunity to demonstrate the benefits of using SAR and EO data together. The key demonstration principles are: to show the complementary nature of near-contemporaneous SAR and EO data, tipping and cueing opportunities of a tandem sensor, and to demonstrate the superiority of one technology for a specific application. The ability to undertake enhanced vessel detection using machine learning algorithms, to use bathymetry with EO and SAR imagery to get a more complete picture, and to detect oil spills in SAR imagery have been demonstrated. This proves the capability of the technologies, and their strengths as joint and separate data sources, helping to inform future mission concepts.