机载防撞系统ACAS X高度跟踪器目标跟踪算法

Target Tracking Algorithm of Airborne Collision Avoidance System ACAS X Height Tracker

摘要: 高度跟踪器能否有效地在新一代机载防撞系统(ACAS X)的垂直面上工作是设计的关键。在传统研究中，高度率估算不够准确是非线性跟踪器的一个弊端，线性跟踪器因报告中的“粗量化”精度使得性能劣化。为了使目标飞机状态值处理更加稳定，该研究使用量化量测状态估计算法，将飞机状态不确定性作为概率分布来描述，量化视为高斯噪声并使用Sheppard校正，通过Kalman滤波算法对飞机垂直面上的状态进行估计。实验结果显示，该算法在高度跟踪的精度上优于传统设计，可以有效做出防撞决策，为ACAS X系统提供更高的可靠性。

Abstract: Whether the height tracker can effectively work on the vertical plane of the new generation of air-borne collision avoidance system (ACAS X) is the key to the design. In traditional research, inaccurate height rate estimation is a drawback of nonlinear trackers, and linear trackers have deteriorated accuracy due to the “coarse quantization” reported in the report. In order for the tracker to process the target aircraft state more stably, the research uses quantitative measurement state estimation algorithm, which describes the aircraft state uncertainty as a probability distribution, quantizes it as Gaussian noise and uses Sheppard correction, and estimates the state of the aircraft on the vertical plane through the Kalman filter algorithm. Experimental results show that the algorithm is superior to traditional designs in high tracking accuracy, can effectively make anti-collision decisions, and provide higher reliability for ACAS X.