Skip to main content
SpringerLink
Log in

Multi-component instantaneous frequency estimation in mono-sensor and multi-sensor recordings with application to source localization

  • Published:
Multidimensional Systems and Signal Processing Aims and scope Submit manuscript

Abstract

A computationally efficient method is proposed to estimate the instantaneous frequency of multi-component signals for both mono-sensor and multi-sensor recordings. The proposed scheme adopts a well known connected component linking method and extends it for signals with intersecting components. For mono-sensor recordings, the proposed method exploits the direction of ridges estimated through a gradient-based approach to estimate the IFs for crossing components. For multi-sensor recordings, the spatial diversity provided by a uniform linear array of sensors is exploited. The proposed multi-sensor IF estimation algorithm is applied for the estimation of the direction of arrival (DOA) of signal emitting sources. It is demonstrated that the DOA estimation method proposed in this paper is superior to the adaptive directional time-frequency distribution based method in terms of computational efficiency and performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Abed, M., & Belouchrani, A. (2018). Performance analysis and computational cost evaluation of high-resolution time-frequency distributions derived from compact support time-lag kernels. Digital Signal Processing, 78, 1–19.

    Article  MathSciNet  Google Scholar 

  • Akram, J., Khan, N. A., Ali, S., & Akram, A. (2020). Multi-component instantaneous frequency estimation using signal decomposition and time-frequency filtering. Signal, Image and Video Processing, 14, 1663–1670.

    Article  Google Scholar 

  • Belouchrani, A., Amin, M. G., Thirion-Moreau, N., & Zhang, Y. D. (2013). Source separation and localization using time-frequency distributions: An overview. IEEE Signal Processing Magazine, 30(6), 97–107.

    Article  Google Scholar 

  • Boashash, B. (1992). Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals. Proceedings of the IEEE, 80(4), 520–538.

    Article  Google Scholar 

  • Chen, S., Dong, X., Xing, G., Peng, Z., Zhang, W., & Meng, G. (2017). Separation of overlapped non-stationary signals by ridge path regrouping and intrinsic chirp component decomposition. IEEE Sensors Journal, 17(18), 5994–6005.

    Article  Google Scholar 

  • Chen, S., Yang, Y., Peng, Z., Dong, X., Zhang, W., & Meng, G. (2019). Adaptive chirp mode pursuit: Algorithm and applications. Mechanical Systems and Signal Processing, 116, 566–584.

    Article  Google Scholar 

  • Cohen, L. (1989). Time-frequency distributions—A review. Proceedings of the IEEE, 77(7), 941–981.

    Article  Google Scholar 

  • Djurović, I. (2018). QML-RANSAC instantaneous frequency estimator for overlapping multicomponent signals in the time-frequency plane. IEEE Signal Processing Letters, 25(3), 447–451.

    Article  Google Scholar 

  • Djurović, I., Stanković, S., Ohsumi, A., & Ijima, H. (2004). Motion parameters estimation by new propagation approach and time-frequency representations. Signal Processing: Image Communication, 19(8), 755–770.

    Google Scholar 

  • Dong, X., Chen, S., Xing, G., Peng, Z., Zhang, W., & Meng, G. (2018). Doppler frequency estimation by parameterized time-frequency transform and phase compensation technique. IEEE Sensors Journal, 18(9), 3734–3744.

    Article  Google Scholar 

  • Guo, Q., Qi, Lg., & Xiang, J. (2018). Space-time-frequency adaptive processor for multiple interference suppression in GNSS applications. International Journal of Antennas and Propagation, 2018, 2301052.

    Google Scholar 

  • Hlawatsch, F., & Boudreaux-Bartels, G. F. (1992). Linear and quadratic time-frequency signal representations. IEEE Signal Processing Magazine, 9(2), 21–67.

    Article  Google Scholar 

  • Khan, N. A., & Ali, S. (2020). A robust and efficient instantaneous frequency estimator of multi-component signals with intersecting time-frequency signatures. Signal Processing, 177, 107728. https://doi.org/10.1016/j.sigpro.2020.107728.

    Article  Google Scholar 

  • Khan, N. A., & Ali, S. (2021). Robust spatial time-frequency distributions for DOA estimation using spatial averaging and directional smoothing. Signal Processing, 180, 107897. https://doi.org/10.1016/j.sigpro.2020.107897.

    Article  Google Scholar 

  • Khan, N. A., & Sandsten, M. (2016). Time-frequency image enhancement based on interference suppression in Wigner–Ville distribution. Signal Processing, 127, 80–85.

    Article  Google Scholar 

  • Khan, N. A., Mohammadi, M., & Ali, S. (2019). Instantaneous frequency estimation of intersecting and close multi-component signals with varying amplitudes. Signal, Image and Video Processing, 13(3), 517–524.

    Article  Google Scholar 

  • Khan, N. A., Mohammadi, M., & Djurović, I. (2019). A modified viterbi algorithm-based IF estimation algorithm for adaptive directional time-frequency distributions. Circuits, Systems, and Signal Processing, 38(5), 2227–2244.

    Article  Google Scholar 

  • Khan, N. A., Ali, S., Mohammadi, M., & Akram, J. (2020a). Novel direction of arrival estimation using adaptive directional spatial time-frequency distribution. Signal Processing, 168, 107342. https://doi.org/10.1016/j.sigpro.2019.107342.

    Article  Google Scholar 

  • Khan, N. A., Ali, S., Mohammadi, M., & Haneef, M. (2020). Direction of arrival estimation of sources with intersecting signature in time-frequency domain using a combination of if estimation and music algorithm. Multidimensional Systems and Signal Processing, 31, 549–567.

    Article  MathSciNet  Google Scholar 

  • Lebaroud, A., & Clerc, G. (2008). Diagnosis of induction motor faults using instantaneous frequency signature analysis. In 2008 18th international conference on electrical machines (pp. 1–5). IEEE.

  • Lerga, J., Sucic, V., & Boashash, B. (2011). An efficient algorithm for instantaneous frequency estimation of nonstationary multicomponent signals in low SNR. EURASIP Journal on Advances in Signal Processing, 1, 725189.

    Article  Google Scholar 

  • Li, P. (2019). A viterbi algorithm-based if estimator for overlapped multicomponent signal. In Eleventh international conference on digital image processing (ICDIP 2019) (Vol. 11179, p. 1117944). International Society for Optics and Photonics.

  • Li, P., & Zhang, Q. H. (2018). An improved viterbi algorithm for if extraction of multicomponent signals. Signal, Image and Video Processing, 12(1), 171–179.

    Article  Google Scholar 

  • Malarvili, M. B., & Mesbah, M. (2009). Newborn seizure detection based on heart rate variability. IEEE Transactions on Biomedical Engineering, 56(11), 2594–2603.

    Article  Google Scholar 

  • Mohammadi, M., Pouyan, A. A., Khan, N. A., & Abolghasemi, V. (2018). Locally optimized adaptive directional time-frequency distributions. Circuits, Systems, and Signal Processing, 37(8), 3154–3174.

    Article  MathSciNet  Google Scholar 

  • Omidvarnia, A., Azemi, G., O’Toole, J. M., & Boashash, B. (2013). Robust estimation of highly-varying nonlinear instantaneous frequency of monocomponent signals using a lower-order complex-time distribution. Signal Processing, 93(11), 3251–3260.

    Article  Google Scholar 

  • Rankine, L., Mesbah, M., & Boashash, B. (2007). If estimation for multicomponent signals using image processing techniques in the time-frequency domain. Signal Processing, 87(6), 1234–1250.

    Article  Google Scholar 

  • Shao, S., Liu, A., Yu, C., Yang, H., Li, Y., & Li, B. (2019). Spatial time-frequency distribution of cross term-based direction-of-arrival estimation for weak non-stationary signal. EURASIP Journal on Wireless Communications and Networking, 1, 1–12.

    Google Scholar 

  • Shui, P. L., Bao, Z., & Su, H. T. (2008). Nonparametric detection of FM signals using time-frequency ridge energy. IEEE Transactions on Signal Processing, 56(5), 1749–1760.

    Article  MathSciNet  Google Scholar 

  • Stanković, L., Djurović, I., Stanković, S., Simeunović, M., Djukanović, S., & Daković, M. (2014). Instantaneous frequency in time-frequency analysis: Enhanced concepts and performance of estimation algorithms. Digital Signal Processing, 35, 1–13.

    Article  Google Scholar 

  • Stevenson, N. J., Toole, J. M., Rankine, L. J., Boylan, G. B., & Boashash, B. (2012). A nonparametric feature for neonatal eeg seizure detection based on a representation of pseudo-periodicity. Medical Engineering & Physics, 34(4), 437–446.

    Article  Google Scholar 

  • Sucic, V., Lerga, J., & Boashash, B. (2014). Multicomponent noisy signal adaptive instantaneous frequency estimation using components time support information. IET Signal Processing, 8(3), 277–284.

    Article  Google Scholar 

  • Zhou, P., Yang, Y., Chen, S., Peng, Z., Noman, K., & Zhang, W. (2018). Parameterized model based blind intrinsic chirp source separation. Digital Signal Processing, 83, 73–82.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Foundation University, Islamabad, Pakistan

    Nabeel Ali Khan

  2. Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Peshawar, Pakistan

    Sadiq Ali

Authors
  1. Nabeel Ali Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sadiq Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sadiq Ali.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khan, N.A., Ali, S. Multi-component instantaneous frequency estimation in mono-sensor and multi-sensor recordings with application to source localization. Multidim Syst Sign Process 32, 959–973 (2021). https://doi.org/10.1007/s11045-021-00769-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11045-021-00769-w

Keywords

Search

Navigation