Research On Ionospheric Contamination Mitigation Algorithm For High Frequency Sky-wave Radar

Nowadays, with explosive growth of productivity, many technologies have rapid development, particularly computer science, communication science and so on. In the process, propagation of electromagnetic waves in the ionosphere was used more and more for over-the-horizon detection, long-distance communications, wide range of navigation and other activities. Research of above work through the ionosphere have a lot of advantage, for example, its monitoring range is very wide, it can get an early warning for a long time, it can prevent the low altitude and very low altitude penetration, it has the ability of anti-stealth and so on. Therefore, the ionospheric effects on production and life of human are increasingly prominent. However, due to the complexity and variability of its structure, wave propagation in it will be subject to interference, for example, the ionospheric phase contamination will bring broadening and shifting the spectrum, a great impact on the target detection. Therefore, in order to enhance the ability to adapt to the ionospheric propagation environment of high-frequency horizon radar system and improve the performance of radar, study various characteristics of the ionosphere and develop ionospheric phase contamination correction algorithm is extremely important.The thesis consists of the following parts:1. We do an overview of the ionosphere. At the same time, we describe the impact of radar signals which propagate through the ionosphere. In accordance the characteristics of ionosphere we support that, in a short time, a small area, the ionosphere is relatively stable and have the same trend. At last we model the mathematical expression of ionospheric phase contamination and indicate the characteristics of ionospheric phase contamination.2. Analysis of the algorithms which used to mitigate the ionospheric contamination of the wave. In my paper, the phase gradient method, the minimum entropy search algorithm, and the autocorrelation algorithm were simulated and done some sample performance analysis. And we propose a novel phase distortion correction method based on temporal correlation matrix. Strong point echoes, such as target, clutter, transponder and so on, which are highly temporal correlated, can be used to structure temporal correlation matrix. And the matrix contains angles of echoes and phase distortions information. In this paper, we use two-dimension FFT to estimate angle of strong point echo, and then obtain the corrections. Computer simulations are conducted to show the validity of the new method, and some of performances of PGA were compared.3. We do a brief study of BURG algorithm and MUSIC algorithm which used in the frequency domain super-resolution commonly. For the study of the algorithms which used to mitigate the ionospheric contamination of the wave, we need to identify the location of special points to significant further signal processing in general, at the same time, the final result of signal processing also need a higher resolution to get better, so we need to study the effective super-resolution algorithms to improve the phase measurement accuracy of contamination correction as well as the overall upgrading the radar on the measurement accuracy. Therefore, in this article we will discuss and compare two commonly used frequency domain super-resolution algorithms, the Burg algorithm and the Multiple Signal Classification (Music) algorithm.4. Finally, we do real data experiment. Through these experiments, we do further analysis and concluded for temporal correlation algorithm and the super-resolution algorithms. At the same time, we verify the conjecture that adjacent beam and adjacent range unit suffered from similar phase contamination.