Tim Jennings-Bramly, Defense Science Technology Laboratory (Dstl); Jonathan Maxey, Defence Science Technology Laboratory (Dstl)
Keywords: ISAR, Motion Compensation, Resolved Imagery, Characterization, Conjunction, RPO
Abstract:
The UK Ministry of Defence (MOD) is carrying out research into the design, demonstration and operational use of ground-based Inverse Synthetic Aperture Radar (ISAR) for characterising Resident Space Objects (RSOs). In support of this, Defence Science and Technology Laboratory (Dstl) has begun the development of ISAR signal processing and simulation models for use in assessing system requirements in relation to UK civilian and military Space Domain Awareness (SDA) requirements. The modelling capability developed as part of this work, along with illustrative examples, is presented in this paper.
Traditional SDA-capable sensors such as the Upgraded Early Warning Radar (UEWR) at RAF Fylingdales are typically designed to detect RSOs over long ranges within large regions of sky enabling the sensor to gather data on many RSOs simultaneously. The data gathered by such a system is usually numeric (e.g. position, velocity and reflectivity) and is primarily used for updating the state estimate of an orbiting RSO. Data of this kind can also be used to provide limited characterisation capability. For example, reflectivity time-variations can be used to infer RSO attitude, and differences between observations and expectations can be used to infer changes of state. However, as the RSO population continues to grow and the number of conjunctions increases, there is an increasing demand in both military and civil circles for complementary systems that will provide an improved characterisation capability. In particular, systems capable of providing damage assessment and monitoring of close-proximity operations such as on-orbit servicing are in especially high demand. Improved characterisation could also enhance traditional SDA sensors by informing the prioritisation of RSOs during state estimate update procedures.
One proposed solution to improve characterisation capability is to develop an SDA system capable of producing resolved imagery of a small number of high-priority RSOs. With sufficient resolution, such imagery could be used to perform RSO identification and/or identify individual features such as solar panels, antennas and payloads. Further characterisation performance can be extracted if a number of resolved images are collected over a given time period. In particular, a time-series of images could be used to infer operational status by evaluating changes to the RSO’s pattern of life.
Low Earth Orbit (LEO) Space Object Imaging (SOI) is often achieved with optical or radar sensors, however, it can be difficult to produce resolved imagery of objects using ground-based optical sensors due to atmospheric and weather effects. Furthermore, possible imaging windows are typically limited to night-time hours and to periods when the spacecraft is illuminated by the Sun. In contrast, ISAR can be used to image objects at all times of the day. High power amplification and large antennas can be used to image RSOs at orbital ranges and wideband radar technology can be used to produce centimetre-level resolutions.
While primarily limited by radar hardware, the quality of an ISAR image is inherently dependent on the signal processing chain. In particular, the choice of Translational Motion Compensation (TMC) and Rotational Motion Compensation (RMC) algorithms can impact the quality of an ISAR image significantly. This paper provides an overview of ISAR Motion Compensation (MoComp) algorithms and their suitability for SOI. A simulation of representative orbital scenarios has been created to test the signal processing methods, the results of which have then been used to formulate a complete end-to-end signal processing chain for ISAR SOI. We describe how the proposed signal processing chain can be used to characterise space objects, both by using the resolved image and also by using derived object motion parameters output by the methods themselves. We also simulate an RPO scenario and evaluate the performance of the proposed signal processing chain for producing resolved images of RSOs undergoing close-proximity manoeuvres.
© Crown copyright (2023), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@nationalarchives.gov.uk
Date of Conference: September 19-22, 2023
Track: SDA Systems & Instrumentation