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A Practical Fundamental Frequency Extraction Algorithm for Motion Parameters Estimation of Moving Targets

机译:一种实用的运动目标运动参数估计基础频率提取算法

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摘要

In this paper, a practical method is proposed for a moving target's fundamental frequency (MTFF) extraction from its acoustic signal. This method is developed for the application of motion parameters estimation. Starting from the analysis of the target frequency model and the acoustic Doppler model, the characteristics of moving target's signal are discussed. Based on the signatures of target's acoustic signal, a new approximate greatest common divisor (AGCD) method is developed to obtain an initial fundamental frequency (IFF). Then, the corresponding harmonic number associated with the IFF is determined by maximizing an objective function formulated as an impulse-train-weighted symmetric average magnitude sum function (SAMSF) of the observed signal. The frequency of the SAMSF is determined by target's acoustic signal, the period of the impulse train is controlled by the estimated IFF harmonic, and the maximization of the objective function is carried out through a time-domain matching of periodicity of the impulse train with that of the SAMSF. Finally, a precise fundamental frequency is achieved based on the obtained IFF and its harmonic number. In order to demonstrate the effectiveness of the proposed method, experiments are conducted on wheeled vehicles, tracked vehicles, and propeller-driven aircrafts. Evaluation of the algorithm performance in comparison with other traditional methods indicates that the proposed MTFF is practical for the fundamental frequency extraction of moving targets.
机译:本文提出了一种从声信号中提取运动目标基频(MTFF)的实用方法。该方法是为运动参数估计的应用而开发的。从目标频率模型和声学多普勒模型的分析开始,讨论了运动目标信号的特性。基于目标声信号的特征,开发了一种新的近似最大公约数(AGCD)方法以获得初始基频(IFF)。然后,通过最大化目标函数来确定与IFF相关的相应谐波数,该目标函数被公式化为观测信号的脉冲序列加权对称平均幅度和函数(SAMSF)。 SAMSF的频率由目标的声音信号确定,脉冲序列的周期由估计的IFF谐波控制,目标函数的最大化是通过脉冲序列的周期性时域匹配来实现的。 SAMSF。最后,基于获得的IFF及其谐波数,可以获得精确的基频。为了证明该方法的有效性,在轮式车辆,履带车辆和螺旋桨驱动的飞机上进行了实验。与其他传统方法相比,对算法性能的评估表明,提出的MTFF对于运动目标的基本频率提取是可行的。

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