Real-time characterization of the ionosphere using diverse data and models


  • Suman Ganguly,

  • Andrew Brown


Complete descriptions of spatial and temporal distributions of the ionospheric plasma are necessary for scientific understanding and for several practical applications involving communication, radar, navigation, etc. Ionospheric diagnostic techniques, on the other hand, provide spatially and temporally incomplete information. A framework for data fusion is needed which would be self-consistent in terms of various input data and would also provide spatial-temporal extrapolations. Incorporation of a physical ionospheric model as a framework for assimilation of ionospheric (ionosonde) data was demonstrated by Ganguly [1990, 1991]. The free parameters of the physical model were adjusted using the observational data, and then the adjusted model was used to predict the state of the ionosphere at a different place and time. Most recently, the approach has been extended to incorporate total electron content (TEC) observation from ground and/or satellite-borne receivers and beacons, as well as data from a variety of other sources such as oblique and vertical sounders, radar, radio propagation, incoherent scatter, optical observations, in situ measurements, etc. This TEC-based reconstruction utilizes novel tomographic techniques and allows integration of any satellite constellation including GPS. Data from other sensors are integrated into the complete system, and the fusion is performed in conjunction with some physical/empirical ionospheric model. This provides a self-consistent four-dimensional ionosphere. The system can accept any reasonable ionospheric model and any amount of diverse input data covering a wide range of space, time, and observational methods.