Multi-frequency real signal frequency estimator based on gradually controllable frequency offset range

HUANG Xiangdong1, L Chong1, LI Yanping1, WANG Xiaolei2

Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (17) : 12-18.

PDF(1227 KB)
PDF(1227 KB)
Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (17) : 12-18.

Multi-frequency real signal frequency estimator based on gradually controllable frequency offset range

  • HUANG Xiangdong1, L Chong1, LI Yanping1, WANG Xiaolei2
Author information +
History +

Abstract

Multi-tone real signal frequency estimation is a fundamental signal processing problem with a wide range of applications. Its accuracy is limited by the difficulty of reducing the inter-spectral interference of frequency components. To fundamentally solve this problem, this paper proposes a multi-tone real signal frequency estimator that can automatically suppress inter-spectral interference. Specifically, it is based on a single-tone frequency estimator with controlling frequency offset range; two residual signals (i.e., descending residual and exclusive residual) are iteratively constructed and fed into the single-tone frequency estimator to obtain the frequency estimation results of each component. The characteristic of this estimator is that the frequency offset range parameter can be progressively set during the iteration process, ensuring that each component can steadily obtain high-precision estimation results. The numerical results demonstrate that the accuracy of the proposed multifrequency estimator is higher than that of existing methods and has broad application prospects.

Key words

Frequency estimation / multi-tone real signals / spectral leakage shrinking / controlling frequency offset range / inter-spectral interference

Cite this article

Download Citations
HUANG Xiangdong1, L Chong1, LI Yanping1, WANG Xiaolei2. Multi-frequency real signal frequency estimator based on gradually controllable frequency offset range[J]. Journal of Vibration and Shock, 2024, 43(17): 12-18

References

[1] 范保华,左乐,唐勇等. 基于最大期望算法的多时变信号DOA估计方法[J]. 系统工程与电子技术,2022, 44(02):420-426. Fan Baohua, Zuo Le, Tang Yong, et al. DOA estiamtion of multiple time-varying signals with expectation-maximization algorithm [J]. Systems Engineering and Electronics, 2022,44(02):420-426. [2] 马碧云,元达鹏,刘娇蛟. 基于似然函数的双曲调频信号参数估计快速算法[J]. 电子与信息学报,2021,43(05):1228-1234. Ma Biyun, Yuan Dapeng, Liu Jiaojiao. Fast Algorithm for Parameter Estimation of Hyperbolic Frequency Modulation Signals Based on Likelihood Function [J]. Journal of Electronics & Information Technology,2021,43(05):1228-1234. [3] 曹成虎,赵永波,庞晓娇等. 基于幅度辅助的中国余数定理多目标多普勒频率估计算法[J]. 系统工程与电子技术,2020,42(06):1261-1266. Cao Chenghu, Zhao Yongbo, Pang Xiaojiao, et al. Doppler frequencies estimation algorithm of multiple targets based on Chinese remainder theorem with amplitude aid[J]. Systems Engineering and Electronics,2020,42(06):1261-1266. [4] 李文番,张国钢,陈沐傈等. 考虑频率偏差的动态同步相量估计器[J]. 电工技术学报,2021,36(19):4060-4069. Li Wenfan, Zhang Guogang, Chen Muli, et al. Dynamic Synchrophasor Estimator Considering Frequency Deviation [J]. Transactions of China Electrotechnical Society,2021,36(19):4060-4069. [5] 杨喜,汪旭明,陈炳权等. 基于谱序列变换的高精度谐波参数估计算法[J]. 中南大学学报(自然科学版),2020,51(09):2504-2513. Yang Xi, Wang Xuming, Chen Bingquan, et al. High precision harmonic parameter estimation algorithm based on spectral sequence transformation [J]. Journal of Central South University(Science and Technology), 2020, 51(09):2504-2513. [6] 徐靖翔,孔明,许新科. 基于旋转不变技术信号参数估计的激光扫频干涉测量方法[J]. 物理学报,2021,70(03):148-155. Xu Jingxiang, Kong Ming, Xu Xinke. Laser frequency scanning interferometry based on estimating signal parameters via rotational invariance technique [J]. Acta Physica Sinica,2021,70(03):148-155. [7] Schmidt R. Multiple emitter location and signal parameter estimation[J]. IEEE transactions on antennas and propagation, 1986, 34(3): 276-280. [8] Roy R, Kailath T. ESPRIT-estimatio0n of signal parameters via rotational invariance techniques[J]. IEEE Transactions on acoustics, speech, and signal processing, 1989, 37(7): 984-995. [9] Gough P T. A fast spectral estimation algorithm based on the FFT[J]. IEEE transactions on signal processing, 1994, 42(6): 1317-1322. [10] Li J, Stoica P. Efficient mixed-spectrum estimation with applications to target feature extraction[J]. IEEE transactions on signal processing, 1996, 44(2): 281-295. [11] Aboutanios E, Mulgrew B. Iterative frequency estimation by interpolation on Fourier coefficients[J]. IEEE Transactions on signal processing, 2005, 53(4): 1237-1242. [12] Candan C. A method for fine resolution frequency estimation from three DFT samples[J]. IEEE Signal processing letters, 2011, 18(6): 351-354. [13] Fan L, Qi G. Frequency estimator of sinusoid based on interpolation of three DFT spectral lines[J]. Signal Processing, 2018, 144: 52-60. [14] Serbes A. Fast and efficient sinusoidal frequency estimation by using the DFT coefficients[J]. IEEE Transactions on Communications, 2018, 67(3): 2333-2342. [15] Tsui J B. Digital Techniques For Wideband Receivers. SciTech Publishing Inc[J]. 2004. [16] Serbes A, Qaraqe K. A fast method for estimating frequencies of multiple sinusoidals[J]. IEEE Signal Processing Letters, 2020, 27: 386-390. [17] Mou Z L, Tu Y Q, Chen P, et al. Accurate frequency estimation of multiple complex and real sinusoids based on iterative interpolation[J]. Digital Signal Processing, 2021, 117: 103173. [18] Rife D, Boorstyn R. Single tone parameter estimation from discrete-time observations[J]. IEEE Transactions on information theory, 1974, 20(5): 591-598. [19] Loparo K A. Case western reserve university bearing data center[J]. Bearings Vibration Data Sets, Case Western Reserve University, 2012: 22-28. [20] 丁锋,秦峰伟. 小波降噪及Hilbert变换在电机轴承故障诊断中的应用[J]. 电机与控制学报,2017,21(06):89-95. Ding Feng, Qin Fengwei. Application of wavelet denoising and Hilbert transform in fault diagnosis of motor bearing[J]. Electric Machines and Control, 2017,21(06):89-95. [21] 杨超,杨晓霞. 基于灰色关联度和Teager能量算子的轴承早期故障诊断[J]. 振动与冲击, 2020,39(13):224-229. Yang Chao, Yang Xiaoxia. Early fault diagnosis of rolling bearing based on GRD and TEO[J]. JOURNAL OF VIBRATION AND SHOCK, 2020,39(13):224-229. [22] A. Potamianos, P Maragos. A comparison of the energy operator and the Hilbert transform approach to signal and speech demodulation[J]. Signal Processing, 1994,37(1): 95-120.
PDF(1227 KB)

Accesses

Citation

Detail

Sections
Recommended

/