Inversion of Oblique Ionograms Based on Hybrid Genetic Algorithm

Abstract

AbstractThe oblique sounding is a powerful tool for acquiring ionospheric information, and we can get the structural parameters related to ionosphere by inversing the oblique ionogram. Genetic algorithm (GA) is a widely used inversion method which can reduce the non‐uniqueness of the inversion problems without depending on the initial estimation, but the accuracy and reliability of GA's inversion results may be decreased due to “premature convergence” and inferior local search ability. So an improved hybrid genetic algorithm (HGA) based on simulated annealing algorithm (SA) is proposed and firstly applied to inversion of oblique ionogram. HGA combines the advantages of GA and SA together and makes full use of them, so it has a strong global search ability and local search ability. To verify the reliability and stability of HGA's inversion results, we firstly use GA, SA, and HGA to inversion of the synthetic oblique ionogram and compare the inversion results of the three algorithms, find that HGA's results are nearest to the real values and its needed iterations are also much smaller than others. The inversion results include the critical frequency, the height of maximum electron density and half‐thickness. Then, comparing the influences on inversion results by changing the population size and the total iterations, we find that the HGA effectively reduces the influences. Lastly, we use the three algorithms to invert the real ionograms and compare the inversion results with the vertical data in the midpoint of transmitting and receiving site. The results show that the stability and the searching optimal solution ability of HGA are obviously better than the GA and SA, and its inversion results are reliable, so HGA has strong referential significance and practical value for the inversion of real ionograms.