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A new nonlinear smooth variable structure filter algorithm applied to air traffic control tracking

机译:一种新的非线性光滑可变结构滤波算法应用于空中交通管制跟踪

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A target-tracking problem based on Air Traffic Control (ATC) Scenario is a typical estimation problem. The target-tracking process that provides good estimation accuracy and robustness to disturbances is often quite important. In order to refine the target-tracking performance, a new nonlinear smooth variable structure filter algorithm is proposed to handle the ATC tracking problem with erroneous measurements. The new estimation algorithm is developed from a fifth-degree cubature Kalman filter, smooth variable structure filter and a time-varying boundary layer. The whole estimation process mainly relies on acquisition of the cubature point, the gain matrices and the time-varying boundary layer rather than updating the error covariance matrix. Simulation results show that the correctness and efficacy of the new algorithm used in the ATC tracking process is superior to other estimation methods. Moreover, the new algorithm provides an alternative fault detection function for the estimation process.
机译:基于空中流量控制(ATC)方案的目标跟踪问题是典型的估计问题。提供良好估计准确性和鲁棒性对干扰的目标跟踪过程通常非常重要。为了优化目标跟踪性能,提出了一种新的非线性平滑变量结构滤波算法来处理错误的测量ATC跟踪问题。新的估计算法是从第五级Cubature Kalman滤波器,平滑变量结构滤波器和时变边界层开发的。整个估计过程主要依赖于获取Cubature点,增益矩阵和时变边界层,而不是更新错误协方差矩阵。仿真结果表明,ATC跟踪过程中使用的新算法的正确性和功效优于其他估计方法。此外,新算法为估计过程提供了替代故障检测功能。

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