High-resolution range profile target robust identification method for radar carrier frequency transformation

Abstract

The invention provides a high-resolution range profile target robust recognition method for radar carrier frequency conversion, and mainly solves the problem that the radar target recognition rate is reduced due to mismatching of a test sample and a training sample under the carrier frequency conversion in the prior art. According to the implementation scheme, the method comprises the following steps: preprocessing radar high-resolution range profile data to obtain high-resolution range profile time-frequency domain feature data; establishing a time-frequency domain characteristic radar target database of the high-resolution range profile and setting a label value; selecting a training sample set and a test sample set before and after carrier frequency conversion from the radar target database; constructing a residual network; training the residual network under the original carrier frequency, and obtaining the residual network under the new carrier frequency through fine tuning; and inputting the test sample set under the new carrier frequency into the fine-tuned residual network under the new carrier frequency to obtain a target identification result. According to the method, the target identification performance under the radar carrier frequency conversion condition is improved, and the method can be used for robust identification of high-resolution range profile data of radar carrier frequency conversion.

Description

technical field [0001] The invention belongs to the technical field of radar, and further relates to a target recognition method, which can be used for robust recognition of high-resolution range image data transformed by radar carrier frequency. Background technique [0002] The echoes of broadband radar targets are called high-resolution range profiles. The high-resolution range image contains rich structural information such as the scattering point distribution and radial size of the target, and has the advantages of being easy to obtain and process, so it has become a research hotspot in the field of radar automatic target recognition. [0003] Convolutional neural network is a kind of neural network with the characteristics of local connection and weight sharing. Due to its strong nonlinear extraction ability, it is widely used in radar high-resolution range image target recognition tasks. [0004] Xidian University disclosed a radar based on two-dimensional convolutio...

AI Technical Summary

Problems solved by technology

At this time, there is a mismatch between the test data and the training data, which will eventually lead to a serious decline in recognition accuracy or even loss of recognition ability.

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