Doppler pre-filtering based dimension-reduced STAP (Space-Time Adaptive Processing) microburst center wind speed estimation method

Abstract

The invention relates to a Doppler pre-filtering based dimension-reduced STAP (Space-Time Adaptive Processing) microburst center wind speed estimation method, which comprises the steps of 1) processing radar receiving data by using a clutter spectrum registration method one distance unit by one distance unit, and solving an IID sample required by clutter covariance matrix estimation of a distance unit to be detected; 2) selecting a certain Doppler frequency to be a central Doppler frequency, building a time domain dimension-reduced matrix at the frequency, and processing data in the IID sample; 3) solving a dimension-reduced optimal weight vector by using a space domain secondary covariance matrix at the central Doppler frequency estimated by dimension-reduced data estimation; and 4) processing dimension-reduced data by using the dimension-reduced optimal weight vector to acquire a center wind speed estimated value and a distribution condition. It is proved by a simulation result that an accurate wind field speed estimation result can be acquired according to the method under the background of strong clutters, and the method is obviously reduced in computation amount compared with an optimal processor due to adoption of the dimension-reduced structure.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a method for estimating wind speed at the center of a micro-downstream cascade based on Doppler pre-filtering. Background technique [0002] Downfall is a strong downdraft that can generate a divergent wind above 17.9m / s on the ground. Strong air convection or relatively closed geographical environment may induce the downfall. With the continuous development of the city, the terrain environment near the terminal airport is becoming more and more complex, and it is more likely to induce micro-downfalls and threaten the safety of aircraft take-off and landing. Among them, the flat-divergence scale is less than 4km, and the micro-downward cascade with a duration of no more than 10 minutes is a particularly serious threat to civil aviation flight safety. When the aircraft enters the micro-downfall area during take-off and landing, the pilot often does no...

AI Technical Summary

Problems solved by technology

However, the traditional STAP technology is mainly aimed at the detection and estimation of point targets, and cannot be directly applied to distributed target detection such as wind shear.

Moreover, the airborne weather radar works in the forward-looking state, and the clutter spectrum of the forward-looking array is not stable in distance, which leads to the fact that the traditional space-time optimal processor cannot be directly applied to the airborne weather radar

At the same time, due to the high dimensionality of the covariance matrix required to construct a space-time optimal processor, the calculations for its estimation and inversion are huge, so it is difficult to realize real-time processing

In summary, the above reasons restrict the application and promotion of STAP technology in airborne weather radar

Images