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Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor
Wenwen Ma1, Jiuxiang Gao2, Yanning Yuan2
1School of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel, Switzerland)
|November 13, 2021
Summary
A new method effectively suppresses continuous wave interference (CWI) in Loran-C signals without needing to know interference frequencies. This approach enhances positioning accuracy by separating Loran-C signals from CWI, offering a more convenient and effective solution.
Area of Science:
- Navigation Systems
- Signal Processing
- Radio Navigation
Background:
- Loran-C serves as a crucial backup for Global Navigation Satellite Systems (GNSS).
- Continuous Wave Interference (CWI) significantly degrades Loran-C signal accuracy and positioning performance.
- Existing CWI suppression methods, like adaptive notch filters, require prior knowledge of interference frequencies and have limitations.
Purpose of the Study:
- To develop a novel method for suppressing CWI in Loran-C signals.
- To address the limitations of traditional methods by eliminating the need for pre-determined CWI frequencies.
- To improve the robustness and accuracy of Loran-C navigation systems in the presence of interference.
Main Methods:
- A sparse representation-based approach utilizing morphological component analysis (MCA).
- Construction of distinct dictionaries tailored to the morphological characteristics of Loran-C signals and CWI.
- Application of tunable Q-factor wavelet transform and discrete cosine transform for sparse signal decomposition.
- Separation of Loran-C signal components from CWI components based on their sparse representations.
Main Results:
- The proposed method successfully suppresses CWI in both synthetic and real-world Loran-C data.
- Demonstrated effectiveness in handling CWI with changing frequencies, a common issue in real environments.
- Outperformed the traditional adaptive notch filter method in terms of effectiveness and convenience.
- Preserved the integrity of the Loran-C signal while mitigating interference.
Conclusions:
- The sparse representation-based MCA method provides a superior alternative for CWI suppression in Loran-C systems.
- This technique enhances the reliability and accuracy of Loran-C navigation, particularly in challenging interference conditions.
- The method's ability to adapt to frequency variations makes it highly practical for real-world applications.
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