基于宽窄带功率比值法的GNSS载噪比估计改进方法
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摘要
为了降低载噪比估计算法的实现复杂度,提出了一种改进的宽窄带载噪比估计方法。该方法利用接收机良好跟踪信号时信号能量主要分布在I支路这一特点,将传统的宽窄带功率比值法中的宽带进行简化变为仅取I支路信号,而窄带保持不变来进行载噪比估计。在详细推导了改进后算法的载噪比估计的理论表达式后,通过仿真测试进行了验证与分析,最后对K值的选取进行了讨论。测试结果表明,改进后的算法与传统算法的性能基本相当,但相比传统的宽窄带功率比值法而言,在算法复杂度方面加法和乘法次数都减少了1 000次左右,约为传统算法的60%,使算法复杂度得到了有效降低。
In order to reduce the implementation complexity of the carrier-to-noise ratio estimation algorithm,an improved method of narrow to wide bandwidth carrier-to-noise ratio estimation is proposed. The signal energy is mainly distributed in the I branch when the signal is tracked well. Based on this feature,this method which only takes the I-branch signal simplifies the broadband in the traditional Narrow to Wide Power Ratio Method,and holds the narrow band constant for the carrier-to-noise ratio estimation.After the theoretical expression of the improved carrier-to-noise ratio estimation is deduced in detail,the verification and analysis are carried out by simulation test. Finally,the selection of K value is discussed.The test results show that the improved algorithm is basically equivalent to the traditional algorithm,however,compared with the traditional Narrow to Wide Power Ratio Method,the improved algorithm can reduce about 1 000 times in the add and multiply amount of the algorithm complexity,about 60% of the traditional algorithm,which makes the complexity is effectively reduced.
In order to reduce the implementation complexity of the carrier-to-noise ratio estimation algorithm,an improved method of narrow to wide bandwidth carrier-to-noise ratio estimation is proposed. The signal energy is mainly distributed in the I branch when the signal is tracked well. Based on this feature,this method which only takes the I-branch signal simplifies the broadband in the traditional Narrow to Wide Power Ratio Method,and holds the narrow band constant for the carrier-to-noise ratio estimation.After the theoretical expression of the improved carrier-to-noise ratio estimation is deduced in detail,the verification and analysis are carried out by simulation test. Finally,the selection of K value is discussed.The test results show that the improved algorithm is basically equivalent to the traditional algorithm,however,compared with the traditional Narrow to Wide Power Ratio Method,the improved algorithm can reduce about 1 000 times in the add and multiply amount of the algorithm complexity,about 60% of the traditional algorithm,which makes the complexity is effectively reduced.
引文
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[2]巴晓辉,刘海洋,郑睿,等.一种有效的GNSS接收机载噪比估计方法[J].武汉大学学报(信息科学版),2011,36(4):457-460.BA Xiaohui,LIU Haiyang,ZHENG Rui,et al.An effective carrier-to-noise ratio estimation method for GNSS receiver[J].Geomatics and Information Science of Wuhan U-niversity,2011,36(4):457-460.(in Chinese)
[3]BRAASCH M S,VAN DIERENDONCK A J.GPS receiver architectures and measurements[J].Proceedings of the IEEE,1999,87(1):48-64.
[4]DANIELE B,CIRO G,GIANMARCO B.Asynchronous pseudolite navigation using C/N0 measurements[J].Journal of Navigation,2016,69(3):639-658.
[5]FALLETTI E,PINI M.Low complexity carrier-to-noise ratio estimators for GNSS digital receivers[J].IEEE Transactions on Aerospace and Electronic Systems,2011,47(1):420-437.
[6]LI L,WAYN C J,WU J,et al.Improvement to multi-resolution collective detection in GNSS receivers[J].Journal of Navigation,2014,67(2):277-293.
[7]BHUIYAN M Z H,SDERHOLM S,THOMBRE S,et al.Performance evaluation of carrier-to-noise density ratio estimation techniques for Bei Dou Bl signal[C]//Proceedings of 2015 IEEE Ubiquitous Positioning Indoor Navigation&Location Based Services.Corpus Christ,TX,USA:IEEE,2015:19-25.
[8]SHARAWI M S,AKOS D,ALOI D N.GPS C/N0 estimation in the presence of interference and limited quantization levels[J].IEEE Transactions on Aerospace and Electronic Systems,2007,43(1):227-238.
[9]傅金琳,赵子阳,李醒飞.一种改进的功率比值法载噪比估算算法[J].中国惯性技术学报,2015,23(5):642-647.FU Jinlin,ZHAO Ziyang,LI Xingfei.Improved power ratio method of carrier-to-noise ratio estimation algorithm[J].Journal of Chinese Inertial Technology,2015,23(5):642-647.(in Chinese)
[10]谢钢.GPS原理与接收机设计[M].北京:电子工业出版社,2015.
[11]盛骤,谢式千,潘承毅.概率论与数理统计[M].4版.北京:高等教育出版社,2015.