文件名称:LFM
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针对贝叶斯滤波过程中存在的目标跟踪问题，提出几种典型的贝叶斯滤波方法，如EKF, UKF, PF和UPF 等，基于这些方法所构
建的框架，对它们进行性能测试和比较，并在非线性环境下，讨论这些方法的特点，仿真实验结果表明，在非线性非高斯环境下，UPF 方
法的性能是最优的。 -According to the bayesian filtering occurred in the process of target tracking problem, this paper puts forward several kinds of typical bayesian filtering methods, such as EKF, UKF, PF and UPF, etc., based on these methods structure
The building of the framework, of their performance test and comparison, and the nonlinear environment, discussed the characteristics of these methods, the simulation results show that the nonlinear non-gaussian environment, UPF party
The performance of the method is the best.
建的框架，对它们进行性能测试和比较，并在非线性环境下，讨论这些方法的特点，仿真实验结果表明，在非线性非高斯环境下，UPF 方
法的性能是最优的。 -According to the bayesian filtering occurred in the process of target tracking problem, this paper puts forward several kinds of typical bayesian filtering methods, such as EKF, UKF, PF and UPF, etc., based on these methods structure
The building of the framework, of their performance test and comparison, and the nonlinear environment, discussed the characteristics of these methods, the simulation results show that the nonlinear non-gaussian environment, UPF party
The performance of the method is the best.
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