Development of an HF selection tool based on the Electron Density Assimilative Model near‐real‐time ionosphere

Abstract

[1] The Electron Density Assimilative Model (EDAM) has been developed to provide real-time characterization of the ionosphere. A thin-client Web-based ionospheric situational awareness tool, which relies on data from EDAM, has been developed. The tool provides the high-frequency (HF) maximum usable frequency (MUF) and the optimum working frequency (FOT) on the basis of the current ionospheric electron density grid from EDAM. Two validations are reported. First, EDAM has been tested against a set of vertical ionosondes. The results show performance comparable to that of the Utah State University Global Assimilation of Ionospheric Measurements Gauss-Markov Kalman filter model. Second, MUFs estimated from EDAM were compared with those measured on an oblique path from New Zealand to Australia. Although EDAM demonstrates better performance than a monthly median model in some days, over the whole test period EDAM performed no better than the international reference ionosphere. This can be attributed to the lack of input GPS total electron content (TEC) data near the midpoint of the path and a probable TEC bias in the background model.

The International Reference Ionosphere – Status 2013

“…The IRI team therefore strongly encouraged the development of new B 0 and B 1 models that would overcome these shortcomings and take advantage of the much increased data base. Angling et al (2009) Altadill et al (2009) find an improvement of up to 32% over the Bilitza et al (2000) model and up to 40% over the Gulyaeva (1987) model and an improvement of up to 20% for B1. Because of these significant improvements the Altadill et al (2009) option is the recommended default in IRI-2012.…”

“…Fridman et al (2006) used the Tikhonov methodology with IRI and GPS data. The Electron Density Assimilative Model (EDAM) approach of Angling et al (2009) is based on a weighted, damped least mean squares estimation (also referred to as Best Linear Unbiased Estimation (BLUE)) and assimilates mostly GPS data into IRI-2007. Good results were obtained by Xinan et al (2012) using a Kalman filter technique to assimilate GPS data, radio occultation data (CHAMP, GRACE, COSMIC, SAC-C, Metop-A, and TerraSAR-X), and Jason-1 and 2 altimeter TEC measurements into IRI-2007.…”

'Cognitive Radios' and their relevance to HF radio systems

“…The policies, also did not automatically configure a HF radio but relied on manual intervention. Even with these limitations it was used as a spring board to show the benefits of developing the critical elements needed for future systems such as real-time ionospheric models [21].…”

A short note on the assimilation of collocated and concurrent GPS and ionosonde data into the Electron Density Assimilative Model

“…Details of EDAM and of its testing are given by Angling [2008], Angling and Khattatov [2006], and Angling et al [2009].…”