Improved 3D radio wave field modeling

Advances long-distance radar and radio communications

Communications Software & Information Technology

Ionosphere image by NASA

Because of their unique interaction with the ionosphere, high-frequency radio waves–3 to 30 MHz–can propagate around the globe.

The ionosphere is formed by a balance of ionizing solar radiation and energetic particles and the collision/recombination of oppositely charged constituents. As such, the ionosphere is an extremely dynamic medium whose properties including free electron densities, temperature, and shear vary on a wide range of both temporal and spatial scales.

The HF band coincides with the critical plasma frequency of the peak free electron densities in the ionosphere, thus it marks the transition between RF signals that are completely trapped due to refraction from the conductive ionosphere and higher frequencies that completely penetrate and are far less affected by the presence of free electrons. As such, HF waves can propagate immense distances around the globe but are sensitive to variability in the Earth’s atmosphere.

Given the complexity of the interaction between HF radio waves and the ionosphere, as shown above, RF engineers require sophisticated modeling tools in order to design HF radio systems. To date, such tools have been missing

Now, scientists from the Navy have developed a wave field estimation method with the ability to estimate properties of transverse electromagnetic waves in 3D, including complex polarization, vector intensity, phase- and group-path lengths, angles of arrival, and hop count. The method can compute the above quantities, even in cases where propagation is such that incident rays are sparse. It consists of:

  1. Using a 3D ray trace model to estimate RF wavefront paths as they propagate through the atmosphere from a transmitter to points within a geographical area of interest (while also estimating each point’s phase path, group path, apogee, and hop count).
  2. Constructing a ray bundle for each point.
  3. Sorting the points into mode constellations according to the points’ hop count and apogee characteristics.
  4. Constructing a Delaunay triangulation of each mode constellation.
  5. Computing a covariance estimation for each triangle in each mode constellation.
  6. Estimating the wave field characteristics over the entire geographical area of interest based on a summation of constituent ray bundles’ characteristics within each mode constellation.

This wave field estimation method can be used for a number of applications such as channel response estimation and point-to-point estimates for communications applications, and wide-area illumination problems in radar and point-to-area communication applications

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