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| A Frequency Tracking Method for Multiple Frequency-hopping Signals Based on Sparse Bayesian Learning |
| Wang Feng-hua Sha Zhi-chao Liu Zhang-meng Huang Zhi-tao |
| School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China |
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Abstract Most of previous blind parameter estimation methods of Frequency Hopping (FH) signals with a single channel do not adapt to overlapped signals. Moreover, the single- and multiple-channel-based methods use batch processing techniques almost, so they are not able to estimate FH signals in real time. To get real-time tracking reliably, a novel method for single- and multiple-channel-based frequency estimating and hop timing detecting for FH signals is proposed to track the frequency of multiple frequency-hopping signals based on Sparse Bayesian Learning (SBL). Firstly, overlapped FH signals sparse representation model is established. Then, the Sparse Bayesian Learning is used to estimate hopping frequencies and detect the frequency hops once they happen. Numerical examples are carried out to demonstrate the effectiveness of the proposed method.
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Received: 16 November 2012
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Corresponding Authors:
Sha Zhi-chao
E-mail: shazhichao_163@163.com
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2013, Vol. 35 
