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A novel adaptive resampling for sequential Bayesian filtering to improve frequency estimation of time-varying signals

机译：一种用于顺序贝叶斯滤波的新型自适应重采样提高时变信号的频率估计

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This paper presents a new algorithm for adaptive resampling, called percentile-based resampling (PBR) in a sequential Bayesian filtering, i.e., particle filter (PF) in particular, to improve tracking quality of the frequency trajectories under noisy environments. Since the conventional resampling scheme used in the PF suffers from computational burden, resulting in less efficiency in terms of computation time and complexity as well as the real time applications of the PF. The strategy to remedy this issue is proposed in this work. After state updating, important high particle weights are used to formulate the pre-set percentile in each sequential iteration to create a new set of high quality particles for the next filtering stage. The number of particles after PBR remains the same as the original. To verify the effectiveness of the proposed method, we first evaluated the performance of the method via numerical examples to a complex and highly nonlinear benchmark system. Then, the proposed method was implemented for frequency estimation for two time-varying signals. From the experimental results, via three measurement metrics, our approach delivered better performance than the others. Frequency estimates obtained by our method were excellent as compared to the conventional resampling method when number of particles were identical. In addition, the computation time of the proposed work was faster than those recent adaptive resampling schemes in literature, emphasizing the superior performance to the existing ones.
机译：本文介绍了一种新的自适应重采样算法，称为顺序贝叶斯滤波中的百分位数重采样（PBR），即，特别是粒子滤波器（PF），以提高噪声环境下的频率轨迹的跟踪质量。由于PF中使用的传统重采样方案遭受计算负担，因此在计算时间和复杂性方面的效率较低，以及PF的实时应用。在这项工作中提出了解决此问题的策略。在状态更新之后，重要的高粒子重量用于在每个连续迭代中制定预设百分位，以为下一个过滤阶段创建一组新的高质量粒子。 PBR后的颗粒数保持与原始相同。为了验证所提出的方法的有效性，我们首先通过数值例子对复杂和高度非线性基准系统进行评估方法的性能。然后，为两个时变信号实现了所提出的方法，用于频率估计。从实验结果，通过三个测量指标，我们的方法提供比其他指标更好的性能。与常规重采样方法相比，我们的方法获得的频率估计是优异的，当颗粒的数量相同时。此外，所提出的工作的计算时间比文献中的最近自适应重采样方案的计算时间更快，强调了现有的卓越性能。

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