基于多普勒谱特征的飞机尾涡识别

Identification of aircraft wake vortex based on Doppler spectrum features

为解决飞机尾涡威胁飞行安全以及限制机场容量的难题,提出了一种基于多普勒谱特征的尾涡识别算法,以提高尾涡检测性能。构建了飞机尾涡回波多普勒谱模型,分析得出其多普勒谱具有对称性、展宽性以及反比性等重要特征。依据上述谱特征,给出了尾涡识别算法的设计流程,包括回波数据预处理、多普勒谱特征提取和特征门限判决。以空客A-340为例进行了算法的实例计算,结果表明,提取的尾涡回波多普勒谱特征可以用于识别飞机尾涡,其中,幅值反比特征最为严谨,展宽性特征次之,对称性特征较差;在采样数据充足的情况下,算法的综合识别率可达90%以上。

In order to solve the puzzles of threatening flight safety and limiting airport capacity caused by aircraft wake vortex,a new algorithm of wake vortex identification based on Doppler is proposed to improve the performance of wake vortex detection. The Doppler spectrum model of laser echo caused by wake vortex is built,and the analysis has shown that it has the features of symmetry,broadened wave- form and inverse amplitude. Then based on the above-mentioned spectrum features, the flowchart of wake vortex identification is given, containing echo preprocessing, Doppler spectrum features extraction and features threshold decision. Moreover, the calculation example of identification algorithm is carried by taking airbus A340 for example. The results show that the aircraft wake vortex can be identified by the extracted Doppler spectrum features, with particularly strict feature of inverse amplitude, followed by the features of waveform broadening, the symmetry at last. In the condition of sufficient sample data, the comprehensive identification rate of the algorithm can be up to 90 %.