基于ADS-B技術(shù)的通航飛行器避險(xiǎn)方法研究
[Abstract]:General Aviation as a high-tech aviation industry, has a huge role in promoting the national economic growth. Although general aviation of our country takes shape initially, but with the development of the times, it will put forward broader request to general aviation. Among them, the increasing transportation demand leads to the increase of flight flow, so the problem of flight conflict is significant, which threatens flight safety. In order to improve aviation safety, there are many auxiliary surveillance systems, among which ADS-B is a new monitoring technology, which can provide flight data comprehensively. Compared with other monitoring techniques, ADS-B has the advantages of high accuracy, fast data updating and low construction cost. The flight avoidance problem can be divided into two parts: collision detection and conflict resolution. In this paper, ADS-B technology is used to study the problem of risk avoidance. Firstly, by analyzing the technical characteristics of ADS-B, including data structure and refresh frequency, the performance index of ADS-B technology is determined, and the superiority of ADS-B technology in general aviation is analyzed. Secondly, by analyzing the airspace structure, the protected area model of aircraft is established. On the basis of this model, the motion equations of the aircraft are given, and the conflict detection model and conflict resolution model are established. In this paper, the method of conflict detection is introduced in detail, and the method of collision resolution for aircraft is expounded, and three kinds of extrication methods are given: adjusting heading angle, adjusting navigation speed and dynamic conflict resolution. Then, the particle swarm optimization (PSO) algorithm is improved because the dynamic conflict resolution strategy requires a fast optimization algorithm to solve the key problems. Because the accuracy of aircraft trajectory prediction is affected by some uncertainties, such as radar, missiles, climate, etc., It is important to consider the influence of uncertain factors such as real environment obstacles in the proposed dynamic adaptive machine particle swarm optimization (DARPSO). DARPSO can adjust the balance between particle exploration and searching ability in solving the conflict resolution problem. In the conflict resolution problem, the parameters of the algorithm are modified while maintaining the diversity of particles. The simulation results show that the proposed algorithm can improve the convergence accuracy and convergence speed greatly. When the proposed DARPSO is applied to the simulation experiment of conflict resolution, it can show good relief effect and greatly shorten the extrication time. Finally, the experimental equipment for building the experimental platform is introduced, including ADS-B airborne equipment, earth station, monitoring software and so on. The experiment was carried out with the support of Shijiazhuang aircraft Industry Co., Ltd., the ADS-B airborne equipment was installed on Y5B aircraft, and the flight test was carried out. The test results show that the work done in this paper is of great help to solve the problem of navigable dense flight avoiding danger.
【學(xué)位授予單位】:河北科技大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類(lèi)號(hào)】:V355.1;TP18
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