Online Estimation Algorithm of 2D-DOA and Frequency Tracking for Multiple Frequency-hopping Signals

ZHANG Dongwei; GUO Ying; ZHANG Kunfeng; QI Zisen; HAN Lifeng; SHANG Yaobo

doi:10.11999/JEIT151170

Volume 38 Issue 9

Sep. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(9): 2377-2384

ZHANG Dongwei, GUO Ying, ZHANG Kunfeng, QI Zisen, HAN Lifeng, SHANG Yaobo. Online Estimation Algorithm of 2D-DOA and Frequency Tracking for Multiple Frequency-hopping Signals[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2377-2384. doi: 10.11999/JEIT151170

Citation:

ZHANG Dongwei, GUO Ying, ZHANG Kunfeng, QI Zisen, HAN Lifeng, SHANG Yaobo. Online Estimation Algorithm of 2D-DOA and Frequency Tracking for Multiple Frequency-hopping Signals[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2377-2384. doi: 10.11999/JEIT151170

Citation:

ZHANG Dongwei, GUO Ying, ZHANG Kunfeng, QI Zisen, HAN Lifeng, SHANG Yaobo. Online Estimation Algorithm of 2D-DOA and Frequency Tracking for Multiple Frequency-hopping Signals[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2377-2384. doi: 10.11999/JEIT151170

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Online Estimation Algorithm of 2D-DOA and Frequency Tracking for Multiple Frequency-hopping Signals

doi: 10.11999/JEIT151170

1.
2.
ZHANG Dongwei①② GUO Ying② ZHANG Kunfeng② QI Zisen② HAN Lifeng① SHANG Yaobo

Funds:

The National Natural Science Foundation of China (61401499), The Foundation of Electronic Information System Integration Laboratory in Shaanxi Province (201501A)，The Aviation Science Foundation of China (20112096016)

Received Date: 2015-10-23
Rev Recd Date: 2016-07-01
Publish Date: 2016-09-19

Abstract

Abstract

In order to extract Frequency-Hopping (FH) communication parameters and provide the necessary information for the communication countermeasure, an online estimation algorithm of 2D-DOA and frequency tracking for multiple FH signals is proposed in this paper. Firstly, the data model of the L-array for FH signals is built and the applicability of Auto Regresive Moving Average (ARMA) model to L-array data is proved. Then, the particle filtering is introduced to conduct the online estimation of manifold matrix and the frequency, and the ARMA model is built based on the frequency estimates, depending on which, the online detection of hop timing is obtained. After that , the precise estimation of 2D-DOA can be gained via manifold matrix estimates and without parameter matching. With the rational method of particle generation and the weight updating, the new method makes the estimates of manifold matrix and the frequency reach to the stable value promptly. Finally the the Monte-Carlo simulation results show the effectiveness of the proposed algorithm.
- Signal processing,
- Frequency-Hopping (FH),
- Frequency estimation,
- Direction Of Arrival (DOA),
- Particle filtering,
- Auto Regresive Moving Average (ARMA) model

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References(21)

References

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