Parameter Estimation Algorithm for Frequency-hopping Signal in Compressed Domain Based on Sliding Window and Atomic Dictionary

FU Weihong; ZHANG Yunfei; WEI Juan; LIU Naian

doi:10.11999/JEIT170084

Volume 39 Issue 11

Nov. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(11): 2600-2606

FU Weihong, ZHANG Yunfei, WEI Juan, LIU Naian . Parameter Estimation Algorithm for Frequency-hopping Signal in Compressed Domain Based on Sliding Window and Atomic Dictionary[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2600-2606. doi: 10.11999/JEIT170084

Citation:

FU Weihong, ZHANG Yunfei, WEI Juan, LIU Naian . Parameter Estimation Algorithm for Frequency-hopping Signal in Compressed Domain Based on Sliding Window and Atomic Dictionary[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2600-2606. doi: 10.11999/JEIT170084

Citation:

FU Weihong, ZHANG Yunfei, WEI Juan, LIU Naian . Parameter Estimation Algorithm for Frequency-hopping Signal in Compressed Domain Based on Sliding Window and Atomic Dictionary[J]. Journal of Electronics & Information Technology, 2017, 39(11): 2600-2606. doi: 10.11999/JEIT170084

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Parameter Estimation Algorithm for Frequency-hopping Signal in Compressed Domain Based on Sliding Window and Atomic Dictionary

doi: 10.11999/JEIT170084

Funds:

The National Natural Science Foundation of China (61201134), 111 Project (B08038)

Received Date: 2017-01-23
Rev Recd Date: 2017-05-09
Publish Date: 2017-11-19

Abstract

Abstract

Most existing parameter estimation algorithms for Frequency Hopping (FH) signal do not consider the structural characteristics of FH signals, and have the disadvantages of high computational complexity or low estimation accuracy in low signal-to-noise ratio circumstance. To solve this problem, this paper proposes a parameter estimation algorithm for frequency hopping signal in compressed domain based on sliding window and atomic dictionary. The frequency hopping signal is acquired by sliding compression sampling, and hopping time is roughly estimated with sliding window method. The Fourier orthogonal basis of block diagonalization is used as sparse basis to estimate the frequency of the signal. An atomic dictionary, which can represent the local time-frequency characteristics of the frequency hopping signal, is constructed based on the estimated frequency and rough hopping time. Then the hopping time can be estimated accurately by the matching pursuit algorithm. Simulation results show that this algorithm can significantly reduce the sampling data and computational complexity, while maintaining the high accuracy estimation.
- Frequency-hopping signal,
- Compressive sampling,
- Parameter estimation,
- Atomic dictionary

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References(22)

References

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