Quadrature filters for one-step randomly delayed measurements
Quadrature filters for one-step randomly delayed measurements
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DOI：
10.1016/j.apm.2016.04.016
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发表时间：
2016-10
影响因子：
5
通讯作者：
Abhinoy Kumar Singh;S. Bhaumik;P. Date
中科院分区：
文献类型：
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作者：
Abhinoy Kumar Singh;S. Bhaumik;P. Date
本文将现有的两种正交滤波器，即Gauss-Hermite滤波器(GHF)和稀疏网格Gauss-Hermite滤波器(SGHF)进行了扩展，以解决具有一步随机延迟测量的非线性滤波问题。将所设计的滤波器应用于具有一步随机延迟测量的机动目标跟踪问题。仿真结果表明，与延迟立方卡尔曼滤波和延迟无迹卡尔曼滤波相比，所提出的延迟滤波具有更高的精度。
In this paper, two existing quadrature filters,viz., the Gauss–Hermite filter (GHF) and the sparse-grid Gauss–Hermite filter (SGHF) are extended to solve nonlinear filtering problems with one step randomly delayed measurements. The developed filters are applied to solve a maneuvering target tracking problem with one step randomly delayed measurements. Simulation results demonstrate the enhanced accuracy of the proposed delayed filters compared to the delayed cubature Kalman filter and delayed unscented Kalman filter.