Resilient Small Satellite Navigation Using Pulsars
About the Project
How can the regular, precise timing of pulsar stars be exploited to enable resilient positioning and timing in small satellites?
The ability of a spacecraft to determine its own position in space and manage its own clock is highly dependent on global navigation satellite systems (GNSS) such as GPS, GLONASS and Galileo. As Earth orbit becomes an increasingly contested environment, there is a growing threat of intentional disruption to and interference with GNSS satellites and signals. This threat has been created by a collision of malicious intention – with the global political climate at its most turbulent in decades – and capability, as the state-of-the-art in jamming, spoofing and spacecraft cyberattacks reaches its greatest potency to date.
The key to ensuring resilience of a single spacecraft or network of spacecraft to the loss or compromise of critical PNT sources is in the development of autonomous navigation systems, using natural sources such as local or remote features for relative positioning and timing. One autonomous navigation method with great potential is pulsar-based navigation, in which powerful electromagnetic signals emitted on a regular frequency from certain types of neutron stars are exploited to perform positioning and timing calculations. Pulsar-based position and timing is inherently more robust to interference and misidentification than man-made and local PNT sources. Properly exploited, it thus has the potential to provide receiver hosts with position, navigation and timing capabilities more resilient than current solutions. Pulsars generally emit across most of the electromagnetic spectrum, with the highest-energy emissions occurring at higher frequencies, in the X-ray and gamma ray bands. While emissions in these bands are absorbed by the Earth’s atmosphere and therefore cannot be used for positioning on the ground, they can be exploited by spacecraft or other systems operating in exo-atmospheric conditions. With recent advances in detector miniaturisation and the smaller detector size requirements for high-frequency emissions, spacecraft can now host detectors capable of measuring X-ray and gamma pulses. Such detectors have been demonstrated in-orbit, including NASA’s SEXTANT experiment on the ISS, which used a receiver with effective area of 1,800 cm2, and China’s XPNAV-1 spacecraft, which used two receivers of effective areas 2.4 cm2 and 1,200 cm2 respectively. These detectors are on scales approaching those compatible with nano- and microsatellite buses, unlocking new opportunities in autonomous navigation for small satellites.
Existing research into practical application of pulsar-based spacecraft navigation has used orbital platforms such as the ISS and minisatellites and has focussed exclusively on X-ray band experiments, neglecting the higher-energy emissions of gamma rays. Since gamma rays have a smaller-still wavelength than X-rays, gamma ray detectors can theoretically be smaller than those required for X-rays. This presents an opportunity to explore applications on sub-minisatellite platforms, covering both use of both X-ray and gamma ray pulsars for PNT. Meanwhile, X-ray pulsars, for example, have the potential to enable calculation of not just position and timing but also attitude and velocity.
The development of practical small satellite pulsar-based navigation systems is not without its challenges. Acquiring and processing sufficient data for PNT calculations can take a considerable amount of time. This can be addressed with state-of-the-art processing techniques such as machine learning (ML) inference, physics-informed neural networks (PINNs) and sensor fusion techniques. These methods will be considered in the context of edge deployment, which brings its own challenges. Algorithm development will consider tasks for both the initial detection and resolving of pulsar emissions and the subsequent calculation of PNT, attitude and velocity estimates from the pulsar data. Fusion with other sources complementary to strategic goals will be considered, such as other signals of opportunity and autonomous navigation sources. Semi- and non-autonomous sources will be considered for baseline and comparison purposes.
The developed algorithms will be deployed on flight-representative embedded hardware, leading towards integration with actual flight computers. The hardware-deployed solutions will be demonstrated within a simulation environment which will also be developed under the project. Key performance metrics identified during initial literature survey and trade-off analyses will be considered during this test campaign, such that the performance and benefits of the developed solutions can be quantified and asserted.
Due to funding for this PhD, we can only consider applicants who are eligible for "home fee" status
