Peter (Joonghyun) Ryu, SPACEMAP Inc.; Shawn Seunghwan Choi, SPACEMAP Inc.; Jaedong Seong, Korea Aerospace Research Institute; Misoon Mah, M&K Research & Development; Douglas Deok-Soo Kim, SPACEMAP Inc.
Keywords: Radio Frequency Interference, Voronoi Diagram, Spatiotemporal Solution
Abstract:
Geo-space is already busy by space objects and will be busier. More satellites are being deployed and spectrum space is also becoming more congested by their radio frequency (RF) for communications to/from both ground stations and other satellites. One of the critical consequences of the congested spectrum space and busy geo-space is radio frequency interference (RFI) which may cause serious communication disruption. For example, satellite operators occasionally experience failure to download images due to RFI. This phenomenon will be outstanding as more constellations will be in orbits, e.g., Stralink, Oneweb, Planet, etc. Therefore, the prediction of RFI, and hopefully followed by its mitigation, is crucial for smooth communication. However, the prediction and mitigation are computational challenges for the satellites orbiting at extreme speeds, particularly in the forthcoming constellations of from hundreds to thousands, if not tens of thousands, of satellites. This is because an RFI occurs under specific geometric conditions involving (i) three or (ii) four objects at least, depending on conditions. The first obvious case consists of two orbiting satellites, own-sat O and adversarial-sat A, and a ground station G. In this case, A enters the communication field-of-view (FoV) of O with respect to G. So, it is necessary to explore the combinatorial space of (N, 3) where N represents the number of satellites plus ground stations, for each moment in timeline. The second case consists of two orbiting satellites, O and A, and two ground stations, G(O) and G(A) for O and A, respectively. In this case, O enters the FoV of A with respect to G(A) while it maintains communication with G(O). So, the size of the combinatorial space is of (N, 4) for each moment in timeline. The cases of higher combinatorial space may not be ignorable. Here we introduce the SPACEMAP feature which can efficiently and accurately predict the RFI of own satellites against all known radio-frequency emitting objects in space catalogue. We aim to present the best-possible solutions in near real-time. This challenging objective is being materialized by the Voronoi diagram which is the most compact and concise data structure of particles in 3D space, in particular, the dynamic Voronoi diagram of fast-moving space objects to define the extreme spatiotemporal proximity. Assuming a preprocessing operation to construct the Voronoi diagram over timeline, the SPACEMAP method can solve many challenging spatiotemporal problems very fast, i.e., near real-time if not truly real-time. This study makes the following additional contributions. First, the method used for the RFI prediction can be similarly used to find a way for RFI avoidance. Second, the RFI prediction provides a mitigate scheme to avoid corrupted communication due to noise. Third, the SPACEMAP function can be used for retrospective analysis for either known or unknown past RFIs of own satellites. It is also important to note that the Voronoi diagram database by the preprocessing can be used to solve a variety of problems because it is application neutral.
Date of Conference: September 19-22, 2023
Track: Space Domain Awareness