A Joint Estimation Algorithm of TDOA and FDOA Based on Wavelet Threshold De-noising and Conjugate Fuzzy Function

DOU Huijing; WANG Qianlong; ZHANG Xue

doi:10.11999/JEIT150878

Volume 38 Issue 5

May 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(5): 1123-1128

DOU Huijing, WANG Qianlong, ZHANG Xue. A Joint Estimation Algorithm of TDOA and FDOA Based on Wavelet Threshold De-noising and Conjugate Fuzzy Function[J]. Journal of Electronics & Information Technology, 2016, 38(5): 1123-1128. doi: 10.11999/JEIT150878

Citation:

DOU Huijing, WANG Qianlong, ZHANG Xue. A Joint Estimation Algorithm of TDOA and FDOA Based on Wavelet Threshold De-noising and Conjugate Fuzzy Function[J]. Journal of Electronics & Information Technology, 2016, 38(5): 1123-1128. doi: 10.11999/JEIT150878

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A Joint Estimation Algorithm of TDOA and FDOA Based on Wavelet Threshold De-noising and Conjugate Fuzzy Function

doi: 10.11999/JEIT150878

Funds:

The National Natural Science Foundation of China (61171137), Beijing Municipal Education Commission Research and Development Programs (KM201210005001)

Received Date: 2015-07-23
Rev Recd Date: 2015-11-19
Publish Date: 2016-05-19

Abstract

Abstract

To solve the problem that the second-order fuzzy function can not deal with related noise, as well as the problem of large computation based on fourth-order cumulants joint estimation algorithm, this paper proposes a new joint estimation algorithm of TDOA and FDOA by using wavelet thresholding denoising method combined with characteristics of non-circular signals. The method operates firstly wavelet thresholding denoising for the received signal, then constructs conjugate fuzzy function, and finally two-dimensional search is made to obtain the time difference and frequency difference parameters. The simulation experimental results under different signal-to- noise ratio show that the proposed algorithm can not only suppress correlated noise, but also has relatively lower computational complexity and also can make accurate estimation under low signal-to-noise ratio.
- Signal processing,
- Wavelet threshold de-noising,
- Non-circular signal,
- Conjugate fuzzy function,
- Joint estimation

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References(24)

References

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