Prediction and estimation to the maneuvering target in opto-electronic tracking system based on robust extend Kalman filter

机译：基于鲁棒扩展卡尔曼滤波的光电跟踪系统中机动目标的预测与估计

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With the improvement of target maneuvering performance, noises statistical character changes correspondingly in the opto-electronic tracking system. To solve this problem, robust extend Kalman filter (REKF) based on the acceleration non-zero mean value time-correlation model was given in this paper. Result of the simulation shows that, comparing with extend Kalman filter, the prediction precision of REKF is almost twice as much as that of EKF. And at the same time, REKF has good robustness to overcome the effect coursed by stochastic measurement noises.

机译：随着目标机动性能的提高，光电跟踪系统中的噪声统计特性也随之发生变化。为了解决这个问题，本文给出了基于加速度非零均值时间相关模型的鲁棒扩展卡尔曼滤波器（REKF）。仿真结果表明，与扩展卡尔曼滤波器相比，REKF的预测精度几乎是EKF的两倍。同时，REKF具有良好的鲁棒性，可以克服随机测量噪声带来的影响。

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《2011 International Conference on Electronic Mechanical Engineering and Information Technology》|2011年|p.4467-4470|共4页
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Lv Junwei; Guo Ning; Drung Cheedoong;
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中图分类计算机的应用;
关键词
extend Kalman filter; opto-electronic tracking; robust filter; state estimation;

机译：扩展卡尔曼滤波器;光电跟踪;鲁棒滤波器;状态估计;

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专利

1. Maneuvering targets state prediction based on robust H~∞ filtering in opto-electronic tracking system [J] . Wei Ji, Qi Li, Bo Xu, Signal processing . 2010,第6期

机译：基于鲁棒H〜∞滤波的光电跟踪系统机动目标状态预测
2. Robust extended Kalman filter with input estimation for maneuver tracking [J] . Yuzi JIANG, Hexi BAOYIN 中国航空学报（英文版） . 2018,第009期

机译：具有输入估计的鲁棒扩展卡尔曼滤波器，用于机动跟踪
3. A novel robust two-stage extended Kalman filter for bearings-only maneuvering target tracking [J] . Jin-long Yang, Hong-bing Ji International Journal of Physical Sciences . 2011,第5期

机译：一种新颖的鲁棒两级扩展卡尔曼滤波器，仅用于跟踪目标
4. Prediction and estimation to the maneuvering target in opto-electronic tracking system based on robust extend Kalman filter [C] . Lv Junwei, Guo Ning, Drung Cheedoong International Conference on Electronic and Mechanical Engineering and Information Technology . 2011

机译：基于鲁棒扩展Kalman滤波器的光电跟踪系统机动目标的预测与估计
5. AUTOREGRESSIVE MOVING-AVERAGE (ARMA) MODEL IDENTIFICATION FOR DEGENERATE TIME SERIES WITH APPLICATION TO MANEUVERING TARGET TRACKING (STOCHASTIC MODELING, KALMAN FILTER). [D] . SPEAKMAN, NORMAN OWEN. 1985

机译：退化时间序列的自动回归平均（ARMA）模型识别，应用于机动目标跟踪（随机建模，卡尔曼滤波器）。
6. An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking [O] . Wei Zhu, Wei Wang, Gannan Yuan 2016

机译：基于Cubature卡尔曼滤波的机动目标跟踪的交互式多模型滤波改进算法。
7. Tracking of Maneuvering Star-Convex Extended Target Using Modified Adaptive Extended Kalman Filter [O] . Tianli Ma, Qi Zhang, Chaobo Chen, 2020

机译：使用改进的自适应扩展卡尔曼滤波器跟踪机动星凸扩展目标

Prediction and estimation to the maneuvering target in opto-electronic tracking system based on robust extend Kalman filter

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