Single radar echo quality control method, system and terminal for removing signal interference clutter

Abstract

The invention belongs to the technical field of radar echo quality control, and discloses a single radar echo quality control method, system and terminal for removing signal interference clutter. All the observed polarizations at the location are backed up and stored; based on the manual observation summary, a signal interference clutter identification model is constructed based on the polarization characteristics, and the suspected signal interference clutter is identified; the polarization characteristic analysis is used to ensure the maximum convective cloud echo. Under the premise of protection, identify the ground object clutter and the signal interference clutter mixed with the ground object clutter, and remove the clutter marked as ground object clutter and suspected signal interference. The present invention can more accurately identify and process signal interference clutter. In the presence of mixed clutter and strong convection, the technology can still perform accurate identification, can greatly improve the quality of single radar echo data, and provide a basis for radar networking Technical Support.

Description

technical field [0001] The invention belongs to the technical field of radar echo quality control, and in particular relates to a single radar echo quality control method, system and terminal for removing signal interference clutter. Background technique [0002] At present, the traditional radar echo quality control methods usually include: reference slice algorithm, fuzzy logic method, neural network algorithm, etc. These methods are suitable for removing general ground clutter, ocean wave clutter, and super-refractive clutter. and many more. The fuzzy logic-based step-by-step hyperrefractive ground object echo identification method (Liu Liping, 2007) can better identify ground object echoes and precipitation echoes, but because the radial velocity and spectral width values ​​are used in the method ( The effective range of the numerical value is generally less than 150km), which results in the quality control range being smaller than the effective reflectivity detection r...

AI Technical Summary

Problems solved by technology

Signal interference clutter is somewhat similar to general solar ray clutter in terms of reflectivity, most of which present local ray-like features, but the obvious differences are: 1) Although its overall intensity is not too strong, the local The intensity will be stronger, close to 40dBZ, which is close to the edge intensity of strong convective echo; when it is mixed with real rainfall cloud echo, especially when mixed with strong convective cloud, it is extremely difficult to accurately identify of

2) The time and location of its occurrence are affected by signal interference sources (from a business point of view, many fixed signal interference sources around radars will exist for a long time due to some objective factors and cannot be completely removed), and there are extremely large randomness

3) When the signal interference clutter exists, its clutter shape and local intensity characteristics will also show irregular changes over time. Therefore, this further increases the difficulty of building a clutter identification model

[0005] (1) The traditional radar echo quality control method has great uncertainty in the removal of signal interference clutter

[0006] (2) When signal interference clutter and real rainfall cloud echoes are mixed, especially when mixed with strong convective clouds, accurate identification is extremely difficult

[0007] (3) The time and location of the signal interference clutter are affected by the signal interference source, and there is great randomness; the signal interference clutter exists for a period of time, and its clutter shape and local intensity characteristics will also appear over time. irregular change features, which increase the difficulty of constructing the clutter recognition model

[0008] The difficulty in solving the above problems and defects is: the traditional method has great uncertainty in the ability to remove signal interference clutter

The signal interference clutter is somewhat similar to the general solar ray clutter in terms of reflectivity, most of which present local ray-like features, but the obvious differences are: 1) Although its overall intensity is not too strong, but The local intensity will be stronger, close to 40dBZ, which is close to the edge intensity of strong convective echo; when it is mixed with real rainfall cloud echo, especially when mixed with strong convective cloud, accurate identification is extremely important difficult

2) The time and location of its occurrence are all affected by signal interference sources (from a business point of view, some fixed signal interference sources around radars will exist for a long time due to some objective factors and cannot be completely removed), and there are extremely large randomness

3) When the signal interference clutter exists, its clutter shape and local intensity characteristics will also show irregular changes over time. Therefore, this further increases the difficulty of building a clutter identification model

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