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An airport surface surveillance solution based on fusion algorithm

机译:基于融合算法的机场地面监视解决方案

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In this paper, we propose an airport surface surveillance solution combined with Multilateration (MLAT) and Automatic Dependent Surveillance Broadcast (ADS-B). The moving target to be monitored is regarded as a linear stochastic hybrid system moving freely and each surveillance technology is simplified as a sensor with white Gaussian noise. The dynamic model of target and the observation model of sensor are established in this paper. The measurements of sensors are filtered properly by estimators to get the estimation results for current time. Then, we analysis the characteristics of two fusion solutions proposed, and decide to use the scheme based on sensor estimation fusion for our surveillance solution. In the proposed fusion algorithm, according to the output of estimators, the estimation error is quantified, and the fusion weight of each sensor is calculated. The two estimation results are fused with weights, and the position estimation of target is computed accurately. Finally the proposed solution and algorithm are validated by an illustrative target tracking simulation.
机译:在本文中,我们提出了一种结合多点定位(MLAT)和自动相关监视广播(ADS-B)的机场地面监视解决方案。被监视的移动目标被视为自由移动的线性随机混合系统,每种监视技术都被简化为具有高斯白噪声的传感器。建立了目标的动力学模型和传感器的观测模型。估计器对传感器的测量值进行了适当的滤波,以获取当前时间的估计结果。然后,我们分析了所提出的两种融合解决方案的特征,并决定将基于传感器估计融合的方案用于我们的监视解决方案。在提出的融合算法中,根据估计器的输出,量化估计误差,并计算每个传感器的融合权重。将两个估计结果与权重相融合,准确地计算出目标的位置估计。最后,通过示例性目标跟踪仿真对提出的解决方案和算法进行了验证。

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