Brendan Quine, Thoth Technology, Inc.; Lauchie Scott, Defence R&D Canada; Caroline Roberts, THOTH Technology, Inc.
Keywords: Space Situational Awareness, Geostationary Spacecraft, Pulse Compression Radar
Abstract:
Earthfence is a software defined digital radar system specifically designed to surveil GEO Resident Space Objects (RSOs). The system comprises a large aperture fully-steerable antenna equipped with a digital radar and supercomputer cluster for data analysis. A Data Acquisition system comprises FPGA’s that generate customisable pulses that are amplified and transmitted. Radar return signals are digitised in complex quadrature at the feed on reception and transmitted over secure fiber networks to a Xeon processor cluster that performs pulse decompression and object identification. The radar is operates in all illumination and weather conditions reporting targets typically within 30 seconds of observation. The system operates seven modes that may be tasked autonomously and streamed live using interfaces including the Air Force’s Unified Data Library developed by Bluestaq LLC.
The first Earthfence system is in operation at the Algonquin Radio Observatory where it is deployed on the facilities 46m (150 foot) antenna. Operating in C-band the radar detects RSOs with RCS greater than three square meters (32 square feet) and exceeds 25 meter (80 foot) range accuracy at ranges up to 42,000 km (26,000 miles) using an approach that is virtually undetectable.
The system was developed to TRL-9 by Thoth Technology Inc. in collaboration with Analytical Graphics Inc., The Canadian Space Operations Centre (CANSpOC), the Build in Canada Innovation program, and, Defence Research and Development Canada.
In this talk we provide introduce Earthfence and describe development and deployment timelines towards our technical goals to advance our sensitivity to sub-square meter RCS and to extend Earthfence coverage to Low Earth Orbit (LEO). We describe the results of joint operations with other Ground and Space based sensors including the Near Earth Object Surveillance Satellite (NEOSat). We present accuracy comparisons with space-track.org and discuss our recent experiences participating in the Civil-Commercial Operations Cells in Sprint Advanced Concept Training (SACT). Our recent development work on Space Object Identification (SOI) where we utilise additional parameters such as RCS and RF emission in a Bayesian inference model to reduce miss-tagging is discussed. Our work on Non-resolved Object Characterisation using Doppler and Inverse Synthetic Aperture Radar (ISAR) is described.
Date of Conference: September 15-18, 2020
Track: SSA/SDA