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Online radar target recognition method based on ewc

A radar target and recognition method technology, applied in the radar field, can solve problems such as the decline of data recognition ability, achieve the effect of maintaining memory and recognition ability, and improving computing efficiency

Active Publication Date: 2022-07-15
XIDIAN UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, due to the particularity of the radar, it is necessary to identify the continuously acquired data online; with the increase of data, many algorithms will forget the characteristics of the previous data during the training and identification process of the new data, resulting in the identification of the previous data rapid decline in capacity

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  • Online radar target recognition method based on ewc
  • Online radar target recognition method based on ewc
  • Online radar target recognition method based on ewc

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Experimental program
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Embodiment Construction

[0027] refer to figure 1 , is an implementation flow chart of an EWC-based online radar target identification method of the present invention; wherein the EWC-based online radar target identification method includes the following steps:

[0028] Step 1: Obtain training samples and test samples, and initialize the data.

[0029] Determine a high-resolution radar, the high-resolution radar receives target echo data within its detection range, and then randomly extracts N data from the target echo data as the p-th batch of original radar high-resolution range image training data S p , in the target echo data, except the extracted N data, and then randomly extract N' data, as the p-th batch of original radar high-resolution range image test data T p , p=1,2,...,P, P represents the total number of batches for obtaining the original radar high-resolution range image training data and the original radar high-resolution range image test data.

[0030] (1a) The p-th batch of original...

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Abstract

The invention discloses an EWC-based online radar target recognition method, belonging to the technical field of radar. The main idea is to determine the p-th batch of original radar high-resolution range image training data S. p the target class l p and the p-th batch of original radar high-resolution range image test data T p target class T1 p ;p=1,2,...,P,P>1; build a convolutional neural network model to get a trained convolutional neural network; then get S p Fisher information matrix of m data; determine the first batch of original radar high-resolution range image test data T 1 target class T1 1 To the P-th batch of original radar high-resolution range image test data T P target class T1 P , and the predicted target category l′ of the first batch of original radar high-resolution range profile test data 1 Predicted target category l′ to the P-th batch of original radar high-resolution range profile test data P ; and then get the first category to identify the correct target to the first category to identify the correct target, and take the category-identified correct target obtained at this time as an EWC-based online radar target identification result.

Description

technical field [0001] The invention belongs to the technical field of radar, in particular to an online radar target identification method based on EWC, namely an online radar target identification method based on Elastic Weight Consolidation (EWC), which is suitable for online learning radar target identification tasks. Background technique [0002] With the development of advanced technology in modern warfare, the demand for radar target recognition technology is becoming more and more intense. Radar High Resolution Range Profile (HRRP) is the projection vector of target scattering point sub-echoes obtained by broadband radar signals on radar rays. The high-resolution range profile HRRP samples reflect the radar cross-sectional area (RCS) of scatterers (such as nose, wing, tail rudder, air intake, engine, etc.) on the target at a certain radar viewing angle. ) along the radar line-of-sight (RLOS) distribution, which reflects the relative geometric relationship of scatteri...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/41
CPCG01S7/417
Inventor 陈渤刘应祺
Owner XIDIAN UNIV