本文選題：低速目標(biāo)　切入點(diǎn)：Kalmus　出處：《西安電子科技大學(xué)》2014年碩士論文

【摘要】：現(xiàn)代的空中威脅除了傳統(tǒng)的各類轟炸機(jī)、殲擊機(jī)、彈道導(dǎo)彈等高速或高機(jī)動(dòng)目標(biāo)外,還增加了無(wú)人機(jī)、武裝直升機(jī)等低速目標(biāo),形成了新一輪的空中威脅,對(duì)雷達(dá)提出了低速目標(biāo)探測(cè)的要求。由于低速目標(biāo)一般在低空飛行,必須考慮雜波對(duì)檢測(cè)的影響。雜波強(qiáng)度一般都很大,所以雷達(dá)在檢測(cè)目標(biāo)之前必須先抑制雜波。由于低速目標(biāo)在多普勒域與雜波存在嚴(yán)重的交疊,傳統(tǒng)的頻域?yàn)V波處理在抑制雜波的同時(shí)也抑制目標(biāo)信號(hào)從而難以提高信雜比,這就是低速目標(biāo)難以檢測(cè)的原因。針對(duì)這一問題,本文對(duì)各種低速目標(biāo)檢測(cè)方法進(jìn)行了研究和分析。本文首先介紹了傳統(tǒng)的低速目標(biāo)檢測(cè)方法,即Kalmus濾波器和雜波圖檢測(cè)方法。Kalmus濾波器能抑制雜波的同時(shí)盡可能的保留低頻分量,有效提高低速目標(biāo)的信雜比。本文通過比較它與FIR濾波器的性能,通過仿真驗(yàn)證了Kalmus濾波器確實(shí)更加適合低速目標(biāo)檢測(cè)。雜波圖檢測(cè)技術(shù)是利用了雜波在時(shí)間上滿足準(zhǔn)平穩(wěn)性通過所謂的時(shí)域CFAR來(lái)檢測(cè)目標(biāo),本文分析了其檢測(cè)性能,并結(jié)合Kalmus濾波器給出了一種雷達(dá)低速目標(biāo)檢測(cè)方案。接著本文研究了一些現(xiàn)代信號(hào)處理方法,包括AR譜估計(jì)、Capon譜估計(jì)、超分辨方法和經(jīng)驗(yàn)?zāi)B(tài)分解方法,并通過仿真分析了它們的性能和缺陷。與基于傅氏變換的經(jīng)典譜分析方法相比,現(xiàn)代譜估計(jì)方法有望獲得更高頻率分辨率,另外經(jīng)驗(yàn)?zāi)B(tài)分解是一種數(shù)據(jù)自適應(yīng)的信號(hào)分析方法。接著本文重點(diǎn)研究了懸停直升機(jī)的檢測(cè)方法,懸停直升機(jī)是一種典型的低速目標(biāo),它的主旋翼回波具有特殊性質(zhì)。通過分析主旋翼回波信號(hào)模型,討論了直升機(jī)主旋翼回波檢測(cè)對(duì)雷達(dá)性能的要求,同時(shí)給出了時(shí)域雙門限檢測(cè)方法并分析了該方法的檢測(cè)性能。最后介紹了直升機(jī)主旋翼回波的長(zhǎng)時(shí)間積累方法并分析了其性能。
[Abstract]:Modern air threats, in addition to traditional high-speed or high-mobility targets such as bombers, fighter planes, ballistic missiles, and so on, have also increased the number of low-speed targets such as drones and helicopter gunships, thus forming a new round of air threats. The requirement of low speed target detection is put forward for radar. Since the low speed target usually flies at low altitude, the influence of clutter on detection must be considered. Therefore, radar must suppress clutter before detecting target. Because there is a serious overlap between low speed target and clutter in Doppler domain, the traditional frequency domain filter can suppress clutter and suppress target signal at the same time, so it is difficult to improve the signal-to-clutter ratio. This is the reason why it is difficult to detect low speed target. In order to solve this problem, various low speed target detection methods are studied and analyzed in this paper. Firstly, the traditional low speed target detection method is introduced in this paper. That is, Kalmus filter and clutter detection method. Kalmus filter can suppress clutter while keeping low frequency component as much as possible, and effectively improve the signal-to-clutter ratio of low speed target. This paper compares its performance with that of FIR filter. The simulation results show that the Kalmus filter is more suitable for low speed target detection. The clutter detection technique uses the clutter to satisfy the quasi-stationarity in time and uses the so-called time domain CFAR to detect the target. In this paper, the detection performance is analyzed. A low speed target detection scheme based on Kalmus filter is presented. Then some modern signal processing methods are studied, including AR spectrum estimation, superresolution method and empirical mode decomposition method. Compared with the classical spectrum analysis method based on Fourier transform, the modern spectrum estimation method is expected to obtain higher frequency resolution. In addition, empirical mode decomposition (EMD) is a data adaptive signal analysis method. Secondly, the detection method of hovering helicopter is studied, which is a typical low-speed target. Its main rotor echo has special properties. By analyzing the main rotor echo signal model, the radar performance requirements of helicopter main rotor echo detection are discussed. At the same time, the time domain double threshold detection method is presented and its detection performance is analyzed. Finally, the long time accumulation method of helicopter main rotor echo is introduced and its performance is analyzed.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.51

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本文編號(hào)：1688318