Development of an HF frequency section tool based on the EDAM real time 
ionosphere. 
 
M J Angling, A K Shukla, P S Cannon 
QinetiQ, UK 
 
The Electron Density Assimilative Model (EDAM) has been developed to provide 
real-time characterisation of the ionosphere. EDAM comprises a suite of 
programmes that manage ionospheric data and assimilate it into a background 
ionospheric model. The system has been designed to work under the Windows 
operating system and to run efficiently on a single PC. 
 
In order to demonstrate the use of EDAM, an ionospheric situational awareness 
tool that relies on data from EDAM is being developed that can be deployed and 
assessed in an operational context. The aims of this demonstration are therefore 
to first, assess the operational benefit that may accrue from the use of an 
assimilative model; and second investigate and implement the system architecture 
required to deliver a useful product derived from the assimilative model. 
 
For the demonstration system, the focus is on HF communications users. This 
decision has been driven by a number of factors: HF propagation tools do not 
generally require integration into larger systems; HF operators are used to 
using propagation tools; and HF propagation provides a good test of the accuracy 
of the ionospheric models. The system allows point-and-click on a map to define 
the transmitter and receiver location and the software returns the operational 
MUF and the optimum working frequency (FOT) based on the real time ionospheric 
electron density grid from EDAM. The returned values are obtained by deriving 
foF2 and M(3000)F2 from the EDAM grid and then applying the MUF estimation 
algorithm from ITU-R533. 
 
A thin client approach has been taken to provide the tool to users. This 
approach only requires a web browser on the client machine. This is advantageous 
as there is a move towards only allowing web services on some classified 
networks. The architecture uses a web server (known as the HF server) to access 
the ionospheric data produced by EDAM. This process is carried out periodically 
and asynchronously from any propagation prediction requests. The client can then 
make requests to the HF Server to run HF predictions; i.e. the client passes 
transmitter and receiver information to the HF Server and the server returns an 
MUF and FOT. 
 
In this paper we will describe the architecture developed and some the 
challenges that must be overcome to ensure that such systems can be used by 
classified users. Comments received from HF users will be summarised and the 
roadmap to further development presented.