A SAMI3-based High Latitude Particle Filter for Ionospheric Data Assimilation
Abstract
The ionosphere, a layer of plasma in the Earth#s upper atmosphere between 80km and 2000km altitude, is a critical environment for radio propagation. Through its ability to bend, slow, and reflect radio signals, depending on their frequency, it is both a nuisance and convenient for several applications; for example, it causes large errors in Global Navigation Satellite System (GNSS) positioning but also facilitates Over-The-Horizon Radar (OTHR), a robust early warning technology that can detect targets several thousand kilometers away. These technologies are thus critically reliant on the user#s ability to properly model the ionosphere through which their signals are propagating. At midlatitudes, the ionosphere is relatively stable and observations are plentiful; however, at high latitudes, the system is far more dynamic, drifting at speeds in excess of a kilometer per second, and is highly under-observed. In order to make use of these technologies, particularly OTHR, at high latitudes, unconventional approaches are necessary in order to represent the ionosphere. To this end, the Empirical- and Assimilation Canadian High Arctic Ionospheric Models (E-/A-CHAIM) were developed, providing climatological and real-time operational specification of the ionosphere, respectively.A-CHAIM in particular, represents a novel advance in ionospheric modeling, using a unique particle filter approach that is robust against the extreme data sparsity and highly dynamic nature of the high latitude ionospheric environment. Particle filters, however, are conventionally considered incredibly computationally expensive and their application in A-CHAIM is only enabled through the use of a highly computationally efficient empirical ionospheric model for its background. Empirical models, however, lack the ability to provide forecast information.To better propagate information across timesteps and improve forecast performance, we must explore alternative background model options in order to achieve tangible performance improvements over the existing A-CHAIM system.To that end, we here make use of a smallset of runs of the, comparably computationally expensive, Naval Research Laboratory (NRL)#s SAMI3 physics-based ionospheric model to help guide a high latitude particle filter data assimilation system, first as a hybrid between empirical and physics-based models and finally through a wholly-SAMI3 solution. The resulting system should provide all of the advantages of a particle filter that areseen in the existing A-CHAIM system, while also providing improved performance, particularly in terms of forecast.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 24, 2023
- Source ID
- N000142312099
Entities
People
- David R. Themens
Organizations
- Office of Naval Research
- United States Navy
- University of Birmingham