Detection Of Turbulence Based On Space-time Processing

Turbulence, lightning, thunderstorm and icing are commonly referred to "four killers" which threaten the safety of civil aviation. Atmospheric turbulence is a kind of severe weather phenomena happens on the upper air, whose main features are messy, random and disorder. Spectral width of radar echo is the main standard to judgethe intensity of turbulence. Unfortunately, expect for turbulence, the azimuth and beam width of the antenna as well as scatters not involved in turbulent movement can also lead to increase in spectrum width.The impact of these factors should be considered when detecting turbulence in order to provide more effective protection for air safety.First of all, the definition and character of turbulence as well as the basic principles and traditional methods of turbulence detection is introduced. In addition, the factors that cause spectrum expansion of turbulence echo is analyzed.Secondly, the nature of meteorological echo is analyzed respectively from the time domain and frequency domain, and the reception model of echo data under the phased array system from turbulence field is established.Simulation results and analysis are given in the end.Thirdly,a space-time steering vector can describe turbulence and other distributed meteorological targets is researched, and then a method for spectral width estimation is proposed based on space-time adaptive processing. The algorithm constructs optimal processor based on the principle of space-time adaptive, suppressing the spectrum spreading influence caused by interference factors to achieve an accurate estimating result of the true turbulence spectrum width.Finally, an algorithm based on ΣΔ-STAP with airborne phased array weather radar for turbulence detection is proposed, which can simplify the multi-channel antenna to dual-channel, reducing the complexity and computation of the algorithm greatly and obtaining better detection performance at the same time.