Method for inhibiting radio frequency interference of synthetic aperture radar on basis of neural network

Abstract

The invention discloses a method for inhibiting radio frequency interference (RFI) of a synthetic aperture radar (SAR) on the basis of a neural network and belongs to the technical field of radar signal processing. Firstly, all global frequency domain characteristic values of an FRI signal are detected from frequency domain data of a SAR original echo; corresponding extended alternating projection neural network (EAPNN network) repository patterns are generated by the frequency domain characteristic values and are memoried into the EAPNN network one by one; then the RFI signal is associated from echo time domain data by utilizing an association function of the EAPNN network; and the echo time domain data is directly subtracted from the associated RFI signal so as to fulfill the aim of inhibiting the RFI. The EAPNN network combines the global characteristics and dynamic tracking characteristics, which are difficult to simultaneously consider in the existing method, and thus, on the premise of ensuring high inhibiting accuracy, a high processing speed can be obtained. The method can be widely used for the fields of the SAR, earth remote sensing and the like and is particularly suitable for places with high requirements on both the inhibiting accuracy and the processing speed and dense RFI.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, and relates to a synthetic aperture radar radio frequency interference suppression technology and a neural network application technology, in particular to a neural network-based synthetic aperture radar radio frequency interference suppression method. Background technique [0002] Synthetic Aperture Radar (SAR) is playing an increasingly important role in resource exploration, environmental monitoring, ocean and crustal observation, topographic mapping, disaster early warning assessment, and military reconnaissance. However, some studies have shown that the impact of Radio Frequency Interference (RFI) on SAR systems (especially SAR systems with lower operating frequency bands) is very serious in some areas. For details, see May 4-8, 2009 Chan S. and others published a conference paper entitled "Study on Radio Frequency Interference of SMAP Radar" at the IEEE Radar Conference held...

AI Technical Summary

Problems solved by technology

However, the methods in different domains have their own shortcomings: (1) The frequency-domain notch method will introduce artificial interference while performing filtering processing, resulting in an increase in the side lobe level, and the transient effect of the filter will cause data truncation, At the same time, there will be gaps in the spectrum of the SAR echo data, which will cause defocusing in the imaging process; (2) The image domain method needs to accurately register the two images, and the objective existence of registration errors will definitely affect the accuracy of the target signal. Distortion causes different degrees of influence. Controlling the registration error within a given range is a key to the image domain method. If the control is not good, the processed result may be poor or even unusable; (3) the algebraic space domain method is due to the current Lack of a quantitative segmentation criterion to guide

Although compared with the global static method, higher suppression accuracy can be obtained, but the implementation of the algorithm is more complicated, and the amount of calculation is large, especially in the case of highly intensive RFI, and the real-time performance of the algorithm is greatly challenged.

In addition, the adaptive filtering method based on the AR model still has edge effects.

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