本文關(guān)鍵詞：機(jī)場跑道異物檢測技術(shù)研究與實(shí)現(xiàn)　出處：《電子科技大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： FOD監(jiān)測雷達(dá) 探測范圍 多目標(biāo) 單元平均CFAR 雜波圖CFAR

【摘要】：機(jī)場跑道異物指的是不屬于飛機(jī)跑道工作區(qū)域但又會因各種原因而出現(xiàn)在跑道上的一切“小物體”,一般簡稱為FOD。FOD會帶來嚴(yán)重的安全隱患和經(jīng)濟(jì)損失,因此對FOD的檢測具有重要的研究意義和使用價值。國外已成功研制出幾款不同的檢測設(shè)備,主要采用雷達(dá)檢測、視頻圖像、可見光等技術(shù),國內(nèi)雖未研制出成品,但也在積極參與探究。本文以機(jī)場跑道異物檢測為研究背景,首先,基于特定的雷達(dá)體制和系統(tǒng)參數(shù)仔細(xì)分析了雷達(dá)監(jiān)測系統(tǒng)的架構(gòu)和布局方式,計(jì)算了探測范圍;其次,根據(jù)回波信號模型和雜波模型,討論了檢測前的兩種預(yù)處理技術(shù),以盡可能降低信雜比,提高檢測概率;最后,提出了多目標(biāo)背景下和非高斯雜波背景下的恒虛警檢測技術(shù),實(shí)現(xiàn)自動檢測。主要工作和創(chuàng)新如下:(1)結(jié)合機(jī)場工作環(huán)境,提出了雙側(cè)線性部署的雷達(dá)網(wǎng)結(jié)構(gòu);根據(jù)特定的俯仰角度、雷達(dá)架設(shè)高度、信號帶寬等參數(shù),詳細(xì)分析了雷達(dá)網(wǎng)的探測范圍和檢測精度等;(2)采用毫米波線性調(diào)頻連續(xù)波雷達(dá)體制,合理建立回波信號模型;去斜處理是將部分耦合的發(fā)射信號作為本振信號,與接收信號混頻后取差拍信號,從而獲取目標(biāo)信息;基于維納濾波的自適應(yīng)雜波抑制技術(shù)是以本地雜波采集數(shù)據(jù)作為參考信號以預(yù)測雜波信號,并與實(shí)際采集數(shù)據(jù)作差值處理,從而提高了信雜比,增大了檢測概率;(3)傳統(tǒng)的空域恒虛警檢測技術(shù)已難以在雜波隨空域劇烈變化的雜波環(huán)境中有效檢測到目標(biāo),本文提出了基于雜波圖恒虛警處理的自動檢測算法。剔除平均類雜波圖CFAR將已被剔除掉若干個較大樣本值后的參考滑窗樣本作為雜波功率估計(jì)值,從而可以克服多目標(biāo)的干擾,在強(qiáng)目標(biāo)干擾下有效地檢測到弱目標(biāo)信號;雙參數(shù)雜波圖CFAR技術(shù)根據(jù)參考滑窗中的樣本均值和樣本方差估計(jì)背景雜波功率,以實(shí)現(xiàn)在韋布爾、對數(shù)正態(tài)雜波等非高斯背景下檢測到目標(biāo)。通過理論分析和仿真結(jié)果驗(yàn)證,所提出的算法均有較好的檢測性能。
[Abstract]:A foreign body on an airport runway refers to all "small objects" that do not belong to the runway working area but will appear on the runway for a variety of reasons. Generally referred to as FOD.FOD will bring serious security risks and economic losses, so the detection of FOD has important research significance and use value. Foreign countries have successfully developed several different testing equipment. Radar detection, video images, visible light and other technologies are mainly used. Although no finished products have been developed in China, they are also actively participating in the research. This paper takes the detection of foreign bodies on the airport runway as the research background, first of all. Based on the specific radar system and system parameters, the structure and layout of radar monitoring system are analyzed carefully, and the detection range is calculated. Secondly, according to the echo signal model and the clutter model, two pre-processing techniques are discussed in order to reduce the signal-to-clutter ratio and improve the detection probability as much as possible. Finally, the CFAR detection technology in multi-target background and non-#china_person0# clutter background is proposed to realize automatic detection. The main work and innovation are as follows: 1) combined with airport working environment. A radar network structure with bilaterally linear deployment is proposed. According to the specific pitch angle, radar elevation, signal bandwidth and other parameters, the detection range and detection accuracy of radar network are analyzed in detail. (2) adopting the millimeter-wave linear frequency modulation continuous wave radar system, establishing the echo signal model reasonably; The de-skew processing takes the partial coupling transmission signal as the local oscillator signal, and takes the beat signal after mixing with the received signal, so as to obtain the target information. Adaptive clutter suppression technology based on Wiener filter uses local clutter acquisition data as reference signal to predict clutter signal, and makes difference processing from actual acquisition data, thus improving the signal-to-clutter ratio. The detection probability is increased; 3) the traditional spatial CFAR detection technique has been difficult to detect the target effectively in the clutter environment where the clutter changes sharply with the spatial domain. In this paper, an automatic detection algorithm based on CFAR processing of clutter graph is proposed. The reference sliding window sample which has been removed from several large sample values is taken as the estimated value of clutter power by removing the average clutter graph CFAR. Therefore, the multi-target jamming can be overcome and weak target signal can be detected effectively under strong target jamming. Two-parameter clutter graph CFAR technique estimates background clutter power according to the sample mean and sample variance in the reference sliding window to realize in Weibull. The target is detected under the background of non-#china_person0# such as logarithmic normal clutter. The theoretical analysis and simulation results show that the proposed algorithm has good detection performance.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：V351;TN957.51

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本文編號：1416523