基于時(shí)分MIMO的地基雷達(dá)高分辨率成像研究
doi: 10.11999/JEIT150905
國家自然科學(xué)基金(61561010),廣西自然科學(xué)基金項(xiàng)目(2013GXNSFAA019323),廣西科學(xué)研究與技術(shù)開發(fā)計(jì)劃項(xiàng)目(桂科攻14122006-6),廣西教育廳科研立項(xiàng)項(xiàng)目(KY2015LX096),廣西無線寬帶通信與信號(hào)處理重點(diǎn)實(shí)驗(yàn)室主任基金項(xiàng)目(GXKL061506)
Study on High-resolution Imaging of Ground-based MIMO Radar Based on Time-division Multiplexing
The National Natural Science Foundation of China (61561010), Guangxi Natural Science Foundation (2013- GXNSFAA019323), Guangxi Scientific Research and Technological Development Project (guikegong 14122006-6), Guangxi Department of Education Research Project (KY2015LX096), Project of Guangxi Key Laboratory of Wireless Broadband Communications and Signal Processing Director Foundation (GXKL061506)
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摘要: 基于時(shí)分多輸入多輸出(MIMO)的地基雷達(dá)成像有許多很好的應(yīng)用價(jià)值,比如替代合成孔徑雷達(dá)成像在山體滑坡監(jiān)測(cè)方面的應(yīng)用。針對(duì)基于時(shí)分MIMO的地基雷達(dá)高效高分辨率成像,該文提出一種基于逆傅里葉變換脈沖壓縮和波束形成的成像算法。雷達(dá)通過步進(jìn)頻連續(xù)波技術(shù)獲得高距離向分辨率,利用MIMO技術(shù)獲得高方位向分辨率。通過逆傅里葉變換法實(shí)現(xiàn)雷達(dá)數(shù)據(jù)距離向壓縮,采用波束形成算法實(shí)現(xiàn)雷達(dá)數(shù)據(jù)方位向壓縮。同時(shí)該算法還針對(duì)MIMO天線陣列所引起的回波信號(hào)相位不連續(xù)問題進(jìn)行了適當(dāng)?shù)男U诒3炙惴ǜ咝缘耐瑫r(shí)提高了成像質(zhì)量。根據(jù)真實(shí)的山體滑坡監(jiān)測(cè)成像場(chǎng)景參數(shù),通過數(shù)值仿真驗(yàn)證了該成像算法的可行性,應(yīng)用在山體滑坡監(jiān)測(cè)上理論效果良好。
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關(guān)鍵詞:
- 雷達(dá)成像 /
- 時(shí)分MIMO雷達(dá) /
- 高分辨率 /
- 波束形成 /
- 逆傅里葉變換脈沖壓縮
Abstract: Ground-based radar imaging based on time-division multiplexing MIMO can be used in many important applications, such as application to landslide monitoring in place of synthetic aperture radar imaging. For efficient high-resolution imaging of the ground-based radar based on time-division multiplexing MIMO, an imaging algorithm based on Inverse Fast Fourier Transform (IFFT) pulse compression and beamforming is proposed. High range resolution is obtained by stepped frequency continuous wave technology and high azimuth resolution is obtained by MIMO technology. The range compression of radar data is realized by IFFT and the cross-range compression of radar data is realized by beamforming algorithm. Furthermore, phase discontinuity problem of received signal caused by MIMO antenna arrays is appropriately corrected in the algorithm, both efficiency of this algorithm and imaging quality are also improved. A numerical simulation proves feasibility of this imaging algorithm according to the practical parameters in monitoring and imaging scenario of landslide, and the proposed imaging algorithm has good theoretical performance when it is applied to landslide monitoring. -
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