Performance of Interference Mitigation with Different Wavelets in Global Positioning Systems
1
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In this paper, we apply a discrete wavelet packet transform (DWPT) to reduce the influence of interference in global positioning system (GPS) signals and compare the interference mitigation performance of various wavelets. By applying DWPT to the received signal, we can gradually divide the received signal band into low-pass and high-pass bands. After calculating the average power for the separate bands, we can determine whether there is interference by comparing the value with the given threshold. For a band that includes interference, we can reconstruct the whole band signal using inverse DWPT (IDWPT) after applying a nulling method that sets all of the wavelet coefficients to 0. The reconstructed signals are correlated with the pseudorandom noise (PRN) codes to acquire GPS signals. The performance evaluation is based on the number of satellite signals whose peak ratio (defined as the ratio of the first and second correlation peak values in the acquisition stage) exceeds the threshold. In this paper, we compare and evaluate the performance of 6 wavelets including Haar, Daubechies, Symlets, Coiflets, Biorthogonal Splines, and Discrete Meyer.
Abstract
In this paper, we apply a discrete wavelet packet transform (DWPT) to reduce the influence of interference in global positioning system (GPS) signals and compare the interference mitigation performance of various wavelets. By applying DWPT to the received signal, we can gradually divide the received signal band into low-pass and high-pass bands. After calculating the average power for the separate bands, we can determine whether there is interference by comparing the value with the given threshold. For a band that includes interference, we can reconstruct the whole band signal using inverse DWPT (IDWPT) after applying a nulling method that sets all of the wavelet coefficients to 0. The reconstructed signals are correlated with the pseudorandom noise (PRN) codes to acquire GPS signals. The performance evaluation is based on the number of satellite signals whose peak ratio (defined as the ratio of the first and second correlation peak values in the acquisition stage) exceeds the threshold. In this paper, we compare and evaluate the performance of 6 wavelets including Haar, Daubechies, Symlets, Coiflets, Biorthogonal Splines, and Discrete Meyer.
참고문헌 (8)
- Borio, D., "GNSS Jammers: Effects and countermeasures", 2012 6th ESA Workshop on Satellite Navigation Technologies (Navitec 2012) & European Workshop on GNSS Signals and Signal Processing (2012)
- Choi, J. W., "Wideband interference detection by using discrete wavelet transform in a direct RF sampling receiver", Proc. of International Conference on Electronics, Information and Communication, pp.1241~1242 (2018)
- P.Y. Dibal, "Application of wavelet transform in spectrum sensing for cognitive radio: A survey", Physical Communication, 28, pp.45~57 (2018), Elsevier BV[DOI]
- Karthik Divakaran, "Wavelet Based Spectrum Sensing Techniques for Cognitive Radio - A Survey", International Journal of Computer Science and Information Technology, 3(2), pp.123~137 (2011), Academy and Industry Research Collaboration Center (AIRCC)[DOI]
- S.G. Mallat, "A theory for multiresolution signal decomposition: the wavelet representation", IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), pp.674~693 (1989), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- Musumeci, L., "Use of the wavelet transform for interference detection and mitigation in global navigation satellite systems", International Journal of Navigation and Observation (2014)[DOI]
- Tian, Z., "A wavelet approach to wideband spectrum sensing for cognitive radios", 2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications (2006)
- Vakin, S. A., "Fundamentals of Electronic Warfare" (2001), Artech House
