短脈沖非相參雷達(dá)的逆合成孔徑成像及其稀疏恢復(fù)成像技術(shù)
doi: 10.11999/JEIT180912
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西北核技術(shù)研究所高功率微波技術(shù)重點(diǎn)實(shí)驗(yàn)室 ??西安 ??710024
Inverse Synthetic Aperture Radar Imaging with Non-Coherent Short Pulse Radar and Its Sparse Recovery
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Science and Technology on High Power Microwave Laboratory, Northwest Institute of Nuclear Technology, Xi’an 710024, China
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摘要: 短脈沖非相參雷達(dá)(NCSP)的輻射源輸出微波脈沖持續(xù)時(shí)間短,針對(duì)于高速運(yùn)動(dòng)目標(biāo)而言,其脈沖持續(xù)時(shí)間內(nèi)的目標(biāo)運(yùn)動(dòng)可忽略不計(jì),對(duì)回波信號(hào)不需進(jìn)行專門(mén)的脈沖內(nèi)運(yùn)動(dòng)補(bǔ)償。為了利用短脈沖非相參雷達(dá)信號(hào)進(jìn)行逆合成孔徑雷達(dá)成像,該文應(yīng)用補(bǔ)償相參處理的方法,去除輻射信號(hào)包絡(luò)時(shí)間不確定性和初始相位的不確定性影響,在常規(guī)方法進(jìn)行包絡(luò)對(duì)齊和初相補(bǔ)償后可利用距離-多普勒(RD)方法進(jìn)行逆合成孔徑雷達(dá)成像,仿真驗(yàn)證了補(bǔ)償后信號(hào)成像的可行性。然而,短脈沖非相參雷達(dá)的載頻隨機(jī)抖動(dòng)的因素會(huì)導(dǎo)致距離-多普勒成像結(jié)果在多普勒維度產(chǎn)生隨機(jī)調(diào)制的旁瓣,影響成像的質(zhì)量。利用稀疏恢復(fù)技術(shù),在成像空間中對(duì)目標(biāo)的散射中心進(jìn)行稀疏重構(gòu),利用正交匹配追蹤(OMP)算法和稀疏貝葉斯學(xué)習(xí)(SBL)算法進(jìn)行成像,從而實(shí)現(xiàn)了抑制非相參因素引起的成像旁瓣,改進(jìn)了成像質(zhì)量,通過(guò)仿真驗(yàn)證了方法可行性。
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關(guān)鍵詞:
- 短脈沖非相參雷達(dá) /
- 逆合成孔徑成像 /
- 稀疏恢復(fù)
Abstract: The microwave source of Non-Coherent Short Pulse (NCSP) radar transmits short pulse. Thus, for high velocity targets, the motion effect in the pulse duration can be neglected, and the echo signal does not need special motion compensation. In order to use the NCSP radar signal for Inverse Synthetic Aperture Radar (ISAR) imaging, the compensation coherent processing method is applied to removing the uncertainty of the envelope time and the initial phase uncertainty. Assuming that the echo is envelope-aligned and initially compensated by conventional methods, ISAR radar imaging can be performed using the Range-Doppler (RD) method, subsequently. The simulation verifies the feasibility of the compensation signal ISAR imaging. However, the carrier-frequency random jitter factor of NCSP radar causes random-modulated sidelobes in the Doppler dimension, which affect imaging quality. In this paper, the sparse recovery technique is used to perform sparse reconstruction of the target scattering center in the imaging space. The Orthogonal Matching Pursuit (OMP) algorithm and the Sparse Bayesian Learning (SBL) algorithm are used as the recovery algorithm for imaging simulation experiments. The simulation results show that the sparse recovery technique can suppress the imaging sidelobes caused by non-coherence and improve the imaging quality. -
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