本文選題：脈沖壓縮 + 距離旁瓣抑制　； 參考：《國防科學(xué)技術(shù)大學(xué)》2014年碩士論文

【摘要】：現(xiàn)代隱身技術(shù)的飛速發(fā)展和超低空突防技術(shù)的大量運用,使得目標(biāo)的RCS降低或者信雜比降低,高分辨技術(shù)是檢測低RCS或者低信雜比目標(biāo)的有效途徑。脈沖壓縮和合成寬帶為兩種主要的形成高分辨距離像的技術(shù),由于不能獲得較為理想的低距離旁瓣,可能會出現(xiàn)弱小目標(biāo)被強目標(biāo)的高距離旁瓣掩蓋的情況。本文研究利用自適應(yīng)脈沖壓縮技術(shù)(APC)減少高分辨成像過程中的距離旁瓣,以提高弱小目標(biāo)的檢測能力。論文工作如下:第二章首先介紹了傳統(tǒng)的脈沖壓縮和匹配濾波器原理,并分析了匹配濾波器常用的幾種窗函數(shù)旁瓣抑制性能;然后針對LFM信號波形,介紹了基于最小均方誤差(MMSE)準(zhǔn)則的自適應(yīng)脈沖壓縮(APC)算法的基本原理和步驟。仿真結(jié)果表明,相比于傳統(tǒng)的加窗抑制旁瓣方法,APC算法旁瓣抑制能力更強,能夠提高信號的距離分辨率,更好地檢測強目標(biāo)旁瓣掩蓋下的弱小目標(biāo)。第三章構(gòu)建了頻率步進(jìn)(SF)雷達(dá)的APC算法的模型,并推導(dǎo)了基于RMMSE準(zhǔn)則的SF的APC算法和步驟。仿真試驗表明,APC算法能夠有效抑制IFFT成像處理的高距離旁瓣,比加窗處理的距離旁瓣抑制效果更好,且避免了主瓣展寬的缺點,提高了在鄰近多目標(biāo)場景中弱小目標(biāo)的檢測性能;針對運動目標(biāo)場景,分析了目標(biāo)運動的速度補償精度要求,推導(dǎo)了運動目標(biāo)的頻率步進(jìn)雷達(dá)APC算法。仿真試驗表明,APC算法對于運動目標(biāo)的成像效果同樣優(yōu)于IFFT變換和加窗處理。第四章根據(jù)空時自適應(yīng)處理(STAP)的方法,將距離像上的APC算法擴(kuò)展到空間-距離域(Space-Range),介紹了空間-距離域二維的自適應(yīng)脈沖壓縮算法(SR-APC),來同時抑制方位像和距離像上的旁瓣,通過仿真實驗表明,SR-APC算法能夠較好地抑制方位像旁瓣和距離像旁瓣,在鄰近多目標(biāo)的二維成像中,更好地分辨出弱小目標(biāo)。在此基礎(chǔ)上,提出一種降維的SR-APC算法,在旁瓣抑制能力有限下降的前提下,減少算法的計算量。
[Abstract]:With the rapid development of modern stealth technology and the extensive application of ultra-low altitude penetration technology, the RCS or signal-to-clutter ratio of target is reduced. High resolution technology is an effective way to detect low RCS or low signal-to-clutter ratio targets. Pulse compression and synthetic wideband are two main techniques to form high resolution range profile. Because we can not obtain ideal low range sidelobe, the dim target may be masked by high range sidelobe of strong target. In this paper, the adaptive pulse compression technique (APC) is used to reduce the range sidelobes in high resolution imaging to improve the detection ability of small and weak targets. The main work of this paper is as follows: in chapter 2, the traditional pulse compression and matched filter principle are introduced, and several kinds of window function sidelobe suppression performance of matched filter are analyzed, and then the waveform of LFM signal is analyzed. The basic principle and steps of adaptive pulse compression (APC) algorithm based on minimum mean square error (MMSE) criterion are introduced. The simulation results show that compared with the traditional windowed sidelobe suppression method, the sidelobe suppression ability of the APC algorithm is stronger, the range resolution of the signal can be improved, and the weak target under the sidelobe masking can be better detected. In chapter 3, the APC algorithm model of frequency stepping SF) radar is built, and the APC algorithm and steps of SF based on RMMSE criterion are deduced. The simulation results show that the proposed algorithm can effectively suppress the high range sidelobe of IFFT imaging, which is more effective than the windowed sidelobe suppression, and avoids the shortcoming of the main lobe broadening. The detection performance of small and weak targets in adjacent multi-target scenes is improved, and the accuracy requirement of velocity compensation for moving targets is analyzed, and the frequency stepping radar APC algorithm of moving targets is deduced. The simulation results show that the algorithm is better than IFFT transform and windowing. In chapter 4, according to the method of space-time adaptive processing (STAP), the APC algorithm on range profile is extended to Space-Rangen in space-distance domain. An adaptive pulse compression algorithm in space-range domain is introduced, which can suppress both azimuth image and sidelobe in range image. The simulation results show that the SR-APC algorithm can suppress the sidelobe of azimuth image and the sidelobe of range image, and can better distinguish small and weak targets in the 2-D imaging of adjacent multi-targets. On this basis, a dimensionally reduced SR-APC algorithm is proposed to reduce the computational complexity of the algorithm under the condition that the sidelobe suppression capacity is limited.
【學(xué)位授予單位】：國防科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN957.51

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