基于似然轨迹预测的空中交通复杂度评估方法

对空中交通复杂度长周期的准确预测是实现空中交通管理系统资源动态分配的一个关键因素。针对以往的空中交通复杂度评估方法中长周期预测精度不足的问题，提出了一种基于飞机似然轨迹预测的复杂度评估方法。所提方法利用随机线性混杂系统理论对飞机动态和外部扰动进行建模，并结合飞机飞行意图实现飞机轨迹的准确预测；根据一阶和二阶空中交通复杂度映射的定义，将复杂度预测问题转化为高斯随机变量的二次型求解问题，并采用劳伦级数展开计算出复杂度映射。通过对设计的场景进行仿真，证明了所提方法的有效性。

Air traffic complexity evaluation method based on probabilistic trajectory prediction

Predicting air traffic complexity accurately for a long period is the key factor for the air traffic management system to configure resources dynamically. Bring attention to the problem of insufficient accuracy of the previous complexity predicting methods for a long predicted period, an air traffic complexity evaluation method based on probabilistic trajectory prediction is proposed. The proposed method uses stochastic linear hybrid system theory to model the aircraft motion and the influence of external uncertain factors, in combination with the flight intent information, to realize the accurate prediction of the flight trajectory. According to the definition of first order and second order complexity mapping, the issue of air traffic complexity prediction is transformed into the calculation of quadratic form of Gaussian random variables, and a Laurent series expansion algorithm is adopted to calculate the air traffic complexity mapping. A numerical simulation example is provided to illustrate the proposed method.