Method for processing non-meteorological noise in radar echoes

Abstract

The invention discloses a method for non-meteorological noise in radar echoes, which comprises the steps of: identifying noise areas existing on an 1.5 DEG elevation plane and an 0.5 DEG elevation plane by simply classifying the radar echoes, then analyzing reflectivity factor values of the echoes and then orderly referring radial velocity values and spectrum width values; performing a best noise rejection strategy on different noises after the noise areas are correctly identified; directly adopting a rejection strategy for noises under the conditions of clear sky and no precipitation echoes at peripheries; and adopting an approximate value filling mechanism for noises which are mixed in the precipitation echoes or are adjacent to the precipitation echoes so as to achieve better rejection effect.

Description

Technical field [0001] The invention relates to a method for processing radar echoes, in particular to a method for processing non-meteorological clutter in radar echoes. Background technique [0002] Doppler weather radar uses the backscattering of electromagnetic waves by cloud and rain targets to find meteorological targets, and determine the spatial position and strength distribution of meteorological targets, so as to understand the generation and disappearance, evolution, and moving speed of precipitation. But Doppler weather radar can also detect non-meteorological targets. When non-meteorological targets are processed into the radar base data, they will cause clutter pollution. Non-meteorological targets are non-meteorological clutter. Non-meteorological clutter includes ground clutter and isolated points and speckle noise clutter. Waves include common ground clutter NP and transient clutter AP caused by the abnormal propagation of radar beams when the radar beam is prop...

AI Technical Summary

Problems solved by technology

All these methods use the characteristics of non-meteorological echoes in the derived visualization products, and through the design of reasonable algorithms, real-time supplementary processing and filtering are carried out from the software. However, there are not many researches in this area in China at present. , on the other hand, whether these methods apply chaos theory or neural network, they only remove the clutter. When the clutter is mixed in the precipitation area, or the clutter is adjacent to the precipitation area, the strategy of not processing is generally adopted. , so that the clutter mixed in the precipitation area or the clutter adjacent to the precipitation area cannot be effectively removed, which will still have a great impact on the exported visualization products; in addition, for super-refractive clutter and ground clutter, due to The terrain of the lower interface in China is complex, so some existing foreign methods in China require a large number of sample statistics parameters locally

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