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Modified higher order spectral analysis based TDE algorithm for CFAR signal detection problem

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Journal of Electronics

Abstract

With the conditions of small data size and low Signal-to-Noise Ratio (SNR), the application of Higher Order Statistics (HOS) is restrained not only by its high estimation variance, but also by its low estimation precision. Therefore, a modified HOS based Time Delay Estimation (TDE) algorithm is proposed to overcome these problems. Comparing with the conventional TDE algorithms, the estimation variance is improved greatly. A typical simulation example is completed in order to test the performance of the algorithm proposed, which shows that the proposed algorithm has advantages over the traditional ones in both detection performance and computation efficiency.

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References

  1. G. C. Carter, Time delay estimation for passive sonar signal processing, IEEE Trans. on Acoustics, Speech, and Signal Processing, 29(1981)3, 463–470.

    Article  Google Scholar 

  2. G. C. Carter, Coherence and time delay estimation, Proc. IEEE, 75(1987)2, 236–255.

    Article  Google Scholar 

  3. Y. T. Chan, J. M. Riley, J. B. Plant, A parameter estimation approach to time delay estimation and signal detection, IEEE Trans. on Acoustic, Speech, and Signal Processing, 28(1980)1, 8–16.

    Article  MATH  Google Scholar 

  4. C. L. Nikias, R. Pan, Time delay estimation in unknown Gaussian spatially correlated noise, IEEE Trans. on Acoustic, Speech and Signal Processing, 36(1988)11, 1706–1714.

    Article  MATH  Google Scholar 

  5. J. K. Tugnait, On time delay estimation with unknown spatially correlated Gaussian noise using fourth-order cumulants and cross cumulants, IEEE Trans. on Signal Processing, 39(1991)6, 1258–1267.

    Article  MATH  MathSciNet  Google Scholar 

  6. C. L. Nikias, J. M. Mendel, Signal processing with higher-order spectra, IEEE Signal Processing Magazine, 37(1993)7, 10–37.

    Article  Google Scholar 

  7. L. M. Garth, H. V. Poor, Detection of non-Gaussian signals: A paradigm for modern statistical signal processing, Proc. IEEE, 82(1994)7, 1061–1095.

    Article  Google Scholar 

  8. T. F. Andre, R. D. Nowak, D. V. Veen, Low-rank estimation of higher order statistics, IEEE Trans. on Signal Processing, 45(1997)3, 673–685.

    Article  Google Scholar 

  9. J. K. Tugnait, Time delay estimation with unknown spatially correlated Gaussian noise, IEEE Trans. on Signal Processing, 41(1993)2, 549–558.

    Article  MATH  Google Scholar 

  10. M. Weiss, Analysis of some modified cell-averaging CFAR processors in multiple-target situations, IEEE Trans. on AES, 18(1982)1, 213–223.

    Google Scholar 

Download references

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Supported by the National Natural Science Foundation of China (No.60072027)

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Liang, Z., Liu, X. & Liu, Y. Modified higher order spectral analysis based TDE algorithm for CFAR signal detection problem. J. of Electron.(China) 21, 461–466 (2004). https://doi.org/10.1007/BF03036997

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  • DOI: https://doi.org/10.1007/BF03036997

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