Turbulence target velocity spectrum width estimation method based on space-time covariance matrix fitting

Abstract

A turbulence target velocity spectrum width estimation method based on space-time covariance matrix fitting comprises the steps of 1) initializing radar echo data of a to-be-detected distance unit, estimating the covariance matrix ( R <^>) of a radar echo signal based on the radar echo data of the to-be-detected distance unit received by an array, constructing a covariance matrix model RS (fo, sigma f) of a turbulence target signal of the distance unit according to the spatial taper angle of the to-be-detected distance unit, constructing a cost function, carrying out two-dimensional search ina target parameter range to find the parameter combination {f<^>o, sigma<^> f } with the maximum value of the cost function, obtaining the turbulence target velocity spectrum width estimation value ofthe distance unit by a doppler spectrum width; and 4) repeating the previous steps to process the echo data received by the radar for each distance unit one by one, and finally obtaining the turbulence target velocity spectrum width estimation result of the whole distance unit. Simulation results show that under the condition of low signal-to-noise ratio, a relatively accurate turbulence target speed spectrum width estimation result can be obtained through the method.

Description

technical field [0001] The invention belongs to the technical field of airborne meteorological radar meteorological target detection, in particular to a turbulent target velocity spectrum width estimation method based on space-time covariance matrix fitting. technical background [0002] Atmospheric turbulence is a dangerous meteorological object often encountered by aircraft during operation, which is caused by the rapidly changing airflow in the atmosphere. Because the velocity vector of the airflow in the turbulent area is very different and the changes are quite sharp, once the aircraft flies into the turbulent area, it will cause turbulence at light level. In severe cases, the aircraft may lose control for a short time, resulting in unimaginable consequences. Atmospheric turbulence is highly hazardous and has a wide range of action (ranging from a few kilometers to a dozen kilometers). Airborne Weather Radar (AWR) is used to detect turbulence in dangerous weather areas ...

AI Technical Summary

Problems solved by technology

The pulse pair method has low complexity and can meet the real-time performance of airborne weather radar, but it is only suitable for high signal-to-noise ratio

The biggest difference between the fast Fourier transform method and the pulse pair method is that the former transforms the echo signal into the frequency domain for Doppler processing, and obtains the second-order moment of the echo power spectrum to obtain the spectral width of the turbulent flow. The Liye variation method is a little more complicated, and the estimation performance is not ideal under low signal-to-noise ratio

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