An ionospheric propagation prediction method for low latitudes and mid-latitudes


  • Harry L. F. Houpis,

  • L. J. Nickisch


An ionospheric propagation prediction method is proposed that is more responsive than current methods to the actual propagation channel of a radio wave. These other methods typically use an “average” propagation channel. The range of conditions that comprise this “average,” when considered separately, can potentially lead to quite different predictions of the propagation channel relative to the “average” alone. Thus, to the extent that a real-time trend in the propagation channel can be established, better predictions can be obtained. The proposed method obtains a real-time trend by employing a nonlinear regression analysis technique coupled together with an appropriately parameterized (empircal) ionosphere model and a ray-tracing algorithm. To test the effectiveness of this approach, we utilize measurements of group path length and elevation to several orbiting satellites from a dual-frequency (UHF/VHF) pulsed radar located near the magnetic equator. These data provide the needed statistics for the regression analysis. We then obtain satellite altitude estimations employing our method and compare these estimates to predictions obtained with a standard method. The result is an improved altitude prediction. The proposed method may also be used to obtain a better understanding of ionosphere-magnetosphere coupling, and in particular, to investigate the influence of geomagnetic activity on the low- and mid-latitude ionosphere. This is accomplished by generating parameter indices from our method and comparing these indices to solar and geomagnetic indices to see if correlations exist. To the extent that such a correlation does exist, a more accurate wave propagation prediction will result, which in turn will provide a more reliable radar tracking performance. We present comparisons between geomagnetic activity (as measured by the Kp three-hourly range index) and the parameter indices that show a weak correlation.