Dr. Yiyang He Profile

Dr. Yiyang He

at Xi'an Research Institute of High Technology

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Proceedings Article | 31 December 2019 Paper

Lifting wavelet denoising based on pulsar wavelet basis

Sihai You, Hongli Wang, Lei Feng, Yiyang He, Qiang Xu, Yongqiang Xiao

Proceedings Volume 11384, 1138405 (2019) https://doi.org/10.1117/12.2559602

KEYWORDS: Wavelets, Pulsars, Denoising, Signal to noise ratio, Signal processing, Photons, Linear filtering, Electronic filtering, X-rays, MATLAB

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In the X-ray pulsar navigation process, since the pulsar signal obtained by the epoch folding contains a large amount of noise, the signal must be denoised in order to obtain higher positioning accuracy. In order to further optimize the denoising effect and improve the algorithm in real time, this paper proposes a pulsar wavelet base and implements its lifting scheme. In this paper, wavelet multi-level decomposition is performed on the pulsar outline, then a wavelet base based on the pulsar's own signal is constructed according to the low-frequency coefficients, and its lifting method is realized. Matlab simulation shows that compared with db4 and db5 methods, the proposed method performs better in terms of signal-to-noise ratio, mean square error, peak relative error, peak position error and real-time performance. Although the peak error of the db1 wavelet is relatively small, its signal-to-noise ratio is too large, and the overall performance is obviously not as good as the proposed method. The proposed signal-to-noise ratio is up to 4.2dB higher than the db4 and db5 methods, and the mean square error is only 24.3% of the db4 and db5 methods. The peak position error is only 50% of the db4 and db5 methods.

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