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TOA Estimation of Unknown Chirp Signal Based on Short Time FRFT and Hough Transform

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Wireless and Satellite Systems (WiSATS 2019)

Abstract

This paper studies the time-of-arrival (TOA) estimation problem for unknown chirp signals. The signal envelope is assumed to be trapezoidal, and TOA is defined as the arrival time for envelope to rise to the half-platform value. The current state-of-the-art technique is based on short time fractional Fourier transform (STFRFT). It utilizes STFRFT to obtain the time-profile of time-frequency spectrum, and proves that the profile can be used to estimate TOA. However, this method uses only the peak of profile, which induces information losses and thus degrades the estimation accuracy. To alleviate this, in this paper, Hough Transform is combined with STFRFT to make better use of the time-frequency spectrum. On the other hand, the chirp rate of signal is conventionally assumed to be accurately detected by a previous FRFT step. But the accuracy is actually limited by the computational complexity of FRFT. Hence, a dechirp technique is also involved to make improvements on this aspect. Numerical results show that the dechirp technique brings advantages in detecting chirp rate; and combining Hough Transform with STFRFT is beneficial for TOA estimation.

Supported by National Natural Science Foundation of China 61671490.

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References

  1. Hara, S., Anzai, D., Yabu, T., Lee, K., Derham, T., Zemek, R.: A perturbation analysis on the performance of TOA and TDOA localization in mixed LOS/NLOS environments. IEEE Trans. Commun. 2(5), 99–110 (2013)

    Google Scholar 

  2. Wang, Z.L., Zhang, D.F., Bi, D.Y., Wang, S.Q.: Multiple-parameter radar signal sorting using support vector clustering and similitude entropy index. Circ. Syst. Sig. Process. 33(6), 1985–1996 (2014)

    Article  Google Scholar 

  3. Guvenc, I., Sahinoglu, Z.: Threshold selection for UWB TOA estimation based on kurtosis analysis. IEEE Commun. Lett. 9(12), 1025–1027 (2005)

    Article  Google Scholar 

  4. Chan, Y.T., Lee, B., Inkol, H.R., Chan, F.: Estimation of pulse parameters by convolution. In: Canadian Conference on Electrical and Computer Engineering, CCECE 2006, vol. 2, no. 5, pp. 99–110. IEEE (2016)

    Google Scholar 

  5. Almeida, L.B.: The fractional Fourier transform and time-frequency representations. IEEE Trans. Signal Process. 42(11), 3084–3091 (1994)

    Article  Google Scholar 

  6. Ozaktas, H.M., Aytr, O.: Fractional Fourier domains. Sig. Process. 46(1), 119–124 (1995)

    Article  Google Scholar 

  7. Tao, R., Li, Y.-L., Wang, Y.: Short-time fractional Fourier transform and its applications. IEEE Trans. Signal Process. 58(5), 2568–2580 (2009)

    Article  MathSciNet  Google Scholar 

  8. Awal, M.A., Ouelha, S., Dong, S.Y., Boashash, B.: A robust high-resolution time-frequency representation based on the local optimization of the short-time fractional Fourier transform. Digit. Sig. Process. 70, 125–144 (2017)

    Article  Google Scholar 

  9. Duda, R.O., Hart, P.E.: Use of the Hough transformation to detect lines and curves in pictures. Commun. ACM 15, 11–15 (1972)

    Article  Google Scholar 

  10. Jiankui, Z., Zishu, H., Sellathurai, M., Hongming, L.: Modified Hough transform for searching radar detection. IEEE Geosci. Remote Sens. Lett. 5(4), 683–686 (2008)

    Article  Google Scholar 

  11. Illingworth, J., Kittler, J.: The adaptive Hough transform. IEEE Trans. Pattern Anal. Mach. Intell. PAMI 9(5), 690–698 (1987)

    Article  Google Scholar 

  12. Sobhani, B.: Target TOA association with the Hough transform in UWB radars. IEEE Trans. Aerosp. Electron. Syst. 52(2), 743–754 (2016)

    Article  Google Scholar 

  13. Ballard, D.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognit. 13, 111–122 (1981)

    Article  Google Scholar 

  14. Xu, L., Oja, E., Kultanen, P.: A new curve detection method: randomized Hough transform (RHT). Pattern Recognit. Lett. 11(5), 331–338 (1990)

    Article  Google Scholar 

  15. Durak, L., Arikan, O.: Short-time Fourier transform: two fundamental properties and an optimal implementation. IEEE Trans. Signal Process. 2(5), 99–110 (2016)

    MathSciNet  MATH  Google Scholar 

  16. Awal, A., Ouelha, S., Dong, S., Boashash, B.: A robust high-resolution time-frequency representation based on the local optimization of the short-time fractional Fourier transform. Digit. Sig. Process. 70, 125–144 (2017)

    Article  Google Scholar 

  17. Mukhopadhyay, P., Chaudhuri, B.: A survey of Hough transform. Priyanka. Pattern Recognit. 48, 993–1010 (2015)

    Article  Google Scholar 

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Correspondence to YiCheng Jiang .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Liu, M., Jiang, Y., Zhang, Y., Jia, M. (2019). TOA Estimation of Unknown Chirp Signal Based on Short Time FRFT and Hough Transform. In: Jia, M., Guo, Q., Meng, W. (eds) Wireless and Satellite Systems. WiSATS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 280. Springer, Cham. https://doi.org/10.1007/978-3-030-19153-5_8

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  • DOI: https://doi.org/10.1007/978-3-030-19153-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19152-8

  • Online ISBN: 978-3-030-19153-5

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