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  本文關(guān)鍵詞： 4D航跡預測 飛行剖面 改進K均值算法 無沖突航跡規(guī)劃 World Wind　出處：《南京航空航天大學》2016年碩士論文　論文類型：學位論文

【摘要】：隨著全球航空業(yè)的飛速發(fā)展,空域資源緊缺與交通流堵塞現(xiàn)象已日趨顯現(xiàn)。為能有效地實施對高密度、小間隔、大流量條件下的空域管理,將無沖突4D航跡預測與規(guī)劃作為國內(nèi)新一代空管自動化系統(tǒng)最核心的一項技術(shù)。因此,本文針對該項核心技術(shù),提出了基于多源數(shù)據(jù)融合的4D航跡預測與規(guī)劃算法,為管制員提前預知航空器動向并及時處理航空器沖突提供必要的依據(jù)。該算法主要針對初始標稱飛行剖面的生成、通過融合空速擬合與航路氣象修正模型提高航跡精度以及多航空器無沖突航跡規(guī)劃展開了一系列的研究。首先,為有效提高標稱飛行剖面的精度,提出一種混合改進K均值和BADA模型的飛行剖面生成方法。其中,根據(jù)航跡數(shù)據(jù)的特點及傳統(tǒng)K均值的缺陷,提出SWED算法來度量高度剖面間的相似性;為獲得更精確的標稱速度剖面,通過速度三角關(guān)系將地速和IDW插值航路風轉(zhuǎn)換成真空速,再結(jié)合BADA模型得到以轉(zhuǎn)換高度為分界點的不同階段的校正空速/真空速剖面。其次,針對如何提高4D航跡預測精度問題,考慮了空速曲線擬合與航路氣象修正模型,提出了基于連續(xù)自動分段最小二乘法的空速擬合算法和基于Gressman插值的預報GRIB修正算法。一方面,通過空速曲線擬合算法,實現(xiàn)了航跡中任意點的狀態(tài)信息可知;另一方面,通過融合GRIB和AMDAR氣象數(shù)據(jù),提升了航路氣象預報的精度。接著,針對預測的4D航跡間存在的飛行沖突問題,給出了一種多航空器無沖突的4D航跡規(guī)劃方法,通過4D網(wǎng)格和幾何模型算法實施飛行沖突探測,再針對沖突航跡運用動態(tài)分組策略,進行初始放行時刻調(diào)整的無沖突4D航跡規(guī)劃,提前降低潛在飛行沖突率,減輕管制員的工作負荷。最終,運用World Wind搭建了多航空器無沖突4D航跡推測系統(tǒng)的仿真驗證平臺,總結(jié)并展示了本文的研究內(nèi)容和成果。
[Abstract]:With the rapid development of the global aviation industry, the shortage of airspace resources and traffic congestion have become increasingly apparent. In order to effectively implement the airspace management under the condition of high density, small interval and large flow, The conflict-free 4D track prediction and planning is regarded as one of the most important technologies in the new generation automatic air traffic control system in China. Therefore, a 4D track prediction and planning algorithm based on multi-source data fusion is proposed in this paper. It provides the necessary basis for the controller to predict the movement of the aircraft in advance and to deal with the collision of the aircraft in time. The algorithm is mainly aimed at the generation of initial nominal flight profiles. A series of studies have been carried out to improve track accuracy by combining airspeed fitting with route weather correction model and non-conflict track planning for multi-aircraft. Firstly, in order to effectively improve the accuracy of nominal flight profile, A flight profile generation method based on improved K-means and BADA models is proposed. According to the characteristics of track data and the defects of traditional K-means, a SWED algorithm is proposed to measure the similarity between altitude profiles. In order to obtain a more accurate nominal velocity profile, the ground velocity and IDW interpolation wind are converted into vacuum velocity by means of the velocity triangle relationship, and the corrected airspeed / vacuum velocity profiles at different stages with the converted height as the boundary point are obtained by combining the BADA model. Secondly, In order to improve the accuracy of 4D track prediction, the space velocity curve fitting and route weather correction model are considered, and the space velocity fitting algorithm based on continuous automatic piecewise least square method and the prediction GRIB correction algorithm based on Gressman interpolation are proposed. By using the space-velocity curve fitting algorithm, the state information of any point in the track is realized. On the other hand, by combining the GRIB and AMDAR meteorological data, the accuracy of the route weather forecast is improved. In order to solve the problem of flight conflict between predicted 4D tracks, a 4D path planning method without collision for multi-aircraft is presented. The 4D mesh and geometric model algorithm are used to detect the flight conflict, and then dynamic grouping strategy is applied to the collision track. In order to reduce the potential flight collision rate in advance and lighten the workload of the controller, the collision free 4D track planning with the initial release time adjustment is carried out. Finally, the simulation verification platform of the multi-aircraft conflict-free 4D track prediction system is built by using World Wind. The research contents and achievements of this paper are summarized and displayed.
【學位授予單位】：南京航空航天大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：V355

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本文編號：1514204