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该论文提出了一种改进的扩展卡尔曼滤波方法，实现对红外，雷达传感器的信息融合跟踪算法。性能优于传统EKF-This paper presents an improved extended Kalman filter method, to achieve the infrared, radar sensor information fusion tracking algorithm. Better performance than traditional EKF
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The extended Kalman filter (EKF) has been widely
used as a nonlinear filtering method for radar tracking
problems. However, it has been found that in
case cross-range measurement errors of the target position
are large, the performance of the
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A new approach to improved filter design is presented for
the radar tracking problem. An idealized version of the
extended Kalman filter, which is unrealizable in practice,
is constructed using a universal linearization concept, and
then it i
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this project describes the kalman filter and the extended kalman filter and it applay it to the car tracking problem
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卡尔曼滤波原理及应用—MATLAB仿真主要介绍数字信号处理中的卡尔曼（Kalman）滤波算法及在相关领域应用。全书共7章。第1章为绪论。第2章介绍MATLAB算法仿真的编程基础。第3章介绍线性Kalman滤波。第4章讨论扩展Kalman滤波，并介绍其在目标跟踪和制导领域的应用和算法仿真。第5章介绍UKF滤波算法，同时也给出其应用领域内的算法仿真实例。第6章介绍了交互多模型Kalman滤波算法。第7章介绍Simulink环境下，如何通过模块库和S函数构建Kalman滤波器，并给出了系统是线性和非线
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