本文選題：低速目標　切入點：Kalmus　出處：《西安電子科技大學》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、殲擊機、彈道導彈等高速或高機動目標外,還增加了無人機、武裝直升機等低速目標,形成了新一輪的空中威脅,對雷達提出了低速目標探測的要求。由于低速目標一般在低空飛行,必須考慮雜波對檢測的影響。雜波強度一般都很大,所以雷達在檢測目標之前必須先抑制雜波。由于低速目標在多普勒域與雜波存在嚴重的交疊,傳統(tǒng)的頻域濾波處理在抑制雜波的同時也抑制目標信號從而難以提高信雜比,這就是低速目標難以檢測的原因。針對這一問題,本文對各種低速目標檢測方法進行了研究和分析。本文首先介紹了傳統(tǒng)的低速目標檢測方法,即Kalmus濾波器和雜波圖檢測方法。Kalmus濾波器能抑制雜波的同時盡可能的保留低頻分量,有效提高低速目標的信雜比。本文通過比較它與FIR濾波器的性能,通過仿真驗證了Kalmus濾波器確實更加適合低速目標檢測。雜波圖檢測技術是利用了雜波在時間上滿足準平穩(wěn)性通過所謂的時域CFAR來檢測目標,本文分析了其檢測性能,并結合Kalmus濾波器給出了一種雷達低速目標檢測方案。接著本文研究了一些現(xiàn)代信號處理方法,包括AR譜估計、Capon譜估計、超分辨方法和經驗模態(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典譜分析方法相比,現(xiàn)代譜估計方法有望獲得更高頻率分辨率,另外經驗模態(tài)分解是一種數據自適應的信號分析方法。接著本文重點研究了懸停直升機的檢測方法,懸停直升機是一種典型的低速目標,它的主旋翼回波具有特殊性質。通過分析主旋翼回波信號模型,討論了直升機主旋翼回波檢測對雷達性能的要求,同時給出了時域雙門限檢測方法并分析了該方法的檢測性能。最后介紹了直升機主旋翼回波的長時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.
【學位授予單位】：西安電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN957.51

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本文編號：1688318