基于注意循環(huán)神經(jīng)網(wǎng)絡(luò)模型的雷達(dá)高分辨率距離像目標(biāo)識(shí)別

徐彬; 陳渤; 劉宏偉; 金林

doi:10.11999/JEIT161034

基于注意循環(huán)神經(jīng)網(wǎng)絡(luò)模型的雷達(dá)高分辨率距離像目標(biāo)識(shí)別

doi: 10.11999/JEIT161034

基金項(xiàng)目:

國(guó)家杰出青年科學(xué)基金(61525105)，國(guó)家自然科學(xué)基金(61201292, 61322103, 61372132)，全國(guó)優(yōu)秀博士學(xué)位論文作者專項(xiàng)資金(FANEDD-201156)

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出版歷程
- 收稿日期: 2016-10-08
- 修回日期: 2016-11-25
- 刊出日期: 2016-12-19

Attention-based Recurrent Neural Network Model for Radar High-resolution Range Profile Target Recognition

Funds:

The National Science Fund for Distinguished Young Scholars (61525105), The National Natural Science Foundation of China (61201292, 61322103, 61372132), The Program for New Century Excellent Talents in University (FANEDD-201156)

摘要

摘要: 針對(duì)雷達(dá)高分辨率距離像(HRRP)數(shù)據(jù)的識(shí)別問(wèn)題，該文利用HRRP生成的時(shí)序特性，提出一種基于循環(huán)神經(jīng)網(wǎng)絡(luò)的注意模型。該模型利用具有記憶功能的循環(huán)神經(jīng)網(wǎng)絡(luò)對(duì)時(shí)域數(shù)據(jù)進(jìn)行編碼，并根據(jù)HRRP中不同距離單元所映射的隱層對(duì)目標(biāo)識(shí)別的重要性，自適應(yīng)地賦予隱層不同的權(quán)值系數(shù)，并根據(jù)隱層特征編碼特征進(jìn)行HRRP目標(biāo)識(shí)別。該模型利用了隱藏在HRRP數(shù)據(jù)內(nèi)部的目標(biāo)結(jié)構(gòu)信息，提高了特征的區(qū)分度。實(shí)測(cè)數(shù)據(jù)的實(shí)驗(yàn)結(jié)果表明，該方法可以有效地進(jìn)行識(shí)別，在樣本存在一定余度數(shù)據(jù)和樣本偏移的情況下，都能準(zhǔn)確地找出目標(biāo)支撐區(qū)域。
- 雷達(dá)目標(biāo)識(shí)別 /
- 高分辨距離像 /
- 循環(huán)神經(jīng)網(wǎng)絡(luò) /
- 注意模型
Abstract: To improve the performance of radar High-Resolution Range Profile (HRRP) target recognition, a new attention-based model is proposed based on time domain feature. This architecture encodes the time domain feature which can reveal the correlation inside the target with Recurrent Neural Network (RNN). Then, this model gives a weight to each part and sums the hidden feature with each weight for the final recognition. Experiments based on measured data show that the attention-based model is effective for radar HRRP recognition. Furthermore, the proposed method can still find the support areas even with the removed test data.
- Radar Automatic Target Recognition (RATR) /
- High-Resolution Range Profile (HRRP) /
- Recurrent Neural Network (RNN) /
- Attention-based model

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參考文獻(xiàn)(18)

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