FREQUENCY TRACKING OF NONSINUSOIDAL PERIODIC SIGNALS IN NOISE

被引:56
|
作者
PARKER, PJ
ANDERSON, BDO
机构
[1] Department of Electrical Engineering II, Kyoto University, Sakyo-Ku, Kyoto, 606, Honmachi Yosida
[2] Department of Systems Engineering, Research School of Physical Sciences, Australian National University, Canberra
关键词
extended Kalman filter; Frequency estimation; harmonic signal analysis; periodic signal analysis; phase-locked loop;
D O I
10.1016/0165-1684(90)90124-H
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
For a periodic signal measured in noise, this paper applies extended Kalman filtering to the problem of estimating the signal's frequency and the amplitudes and phases of the signal's first m harmonic components. The resultant estimator will also track the signal's frequency and its amplitudes and phases should these change over time. In this respect, it is unique among approaches to this problem. A partial theoretical analysis of the estimator appears in the paper. This analysis shows that there is some measure of decoupling in the estimator: the amplitudes are estimated as if the phase and frequency estimates are correct; the phases and frequency are estimated as if the amplitude estimates are correct. For the special case that the signal is a sinusoid and has known amplitude, the estimator becomes the well-known phase-locked loop. The paper also contains extensive simulations demonstrating both the tracking and the asymptotic behaviour of the estimator. The asymptotic behaviour is compared with the results for another known estimator, and the relative strengths of each method are examined. © 1990.
引用
收藏
页码:127 / 152
页数:26
相关论文
共 50 条
  • [21] Maximum likelihood frequency estimation of periodic signals with slowly time-varying amplitude and phase
    Logothetis, A
    Saleem, SK
    ISSPA 96 - FOURTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, PROCEEDINGS, VOLS 1 AND 2, 1996, : 314 - 315
  • [22] Closed-Form Estimator for Frequency Estimation of Complex Sinusoidal Signals in Multiplicative and Additive Noise
    Reza Ashkiani
    Alimorad Mahmoudi
    Mahmood Karimi
    Karim Ansari-Asl
    Circuits, Systems, and Signal Processing, 2020, 39 : 3595 - 3609
  • [23] Closed-Form Estimator for Frequency Estimation of Complex Sinusoidal Signals in Multiplicative and Additive Noise
    Ashkiani, Reza
    Mahmoudi, Alimorad
    Karimi, Mahmood
    Ansari-Asl, Karim
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2020, 39 (07) : 3595 - 3609
  • [24] Parameter estimation of frequency-hopping signals based on merid filter in α stable noise environment
    Zhao, Xin-Ming
    Jin, Yan
    Ji, Hong-Bing
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2014, 36 (08): : 1878 - 1883
  • [25] Adaptive Unscented Kalman Filter for Tracking GPS signals in the Case of an Unknown and Time-Varying Noise Covariance
    Kanouj M.M.
    Klokov A.V.
    Gyroscopy and Navigation, 2021, 12 (03) : 224 - 235
  • [26] Measurement of the Spectrum of Phase Noise of Harmonic Ultrahigh-Frequency Signals by the Cross-Spectrum Method
    Gorevoi, A. V.
    Lirnik, A. V.
    MEASUREMENT TECHNIQUES, 2017, 60 (09) : 939 - 944
  • [27] Measurement of the Spectrum of Phase Noise of Harmonic Ultrahigh-Frequency Signals by the Cross-Spectrum Method
    A. V. Gorevoi
    A. V. Lirnik
    Measurement Techniques, 2017, 60 : 939 - 944
  • [28] Instantaneous Frequency Estimation of FM Signals under Gaussian and Symmetric α-Stable Noise: Deep Learning versus Time-Frequency Analysis
    Razzaq, Huda Saleem
    Hussain, Zahir M.
    INFORMATION, 2023, 14 (01)
  • [29] Instantaneous Frequency Estimation-Based Order Tracking for Bearing Fault Diagnosis Under Strong Noise
    Cui, Lingli
    Yan, Long
    Zhao, Dezun
    IEEE SENSORS JOURNAL, 2023, 23 (24) : 30940 - 30949
  • [30] A comparison of PLL for online frequency tracking in power grids
    Darambazar, Gandorj
    Moukadem, Ali
    Colicchio, Bruno
    Wira, Patrice
    PROCEEDINGS OF 2021 IEEE 30TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE), 2021,