北斗Bl信号载波噪声密度比估计技术性能评价

M. Z. H. Bhuiyan, Stefan Söderholm, S. Thombre, L. Ruotsalainen, M. Kirkko-Jaakkola, H. Kuusniemi
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引用次数: 9

摘要

全球导航卫星系统(GNSS)接收机的载波噪声密度比(C/N0)是衡量GNSS信号质量的重要参数。最传统的C/N0估计技术是基于窄带和宽带功率比(NWPR)实现的,它适用于传统的GPS LI C/A接收机。随着来自不同系统的新的现代化GNSS信号的出现,这些信号的一些基本信号特征也发生了变化,因此它们可能不再具有基于nwpr的GPS LI C/ a信号的类似C/N0估计性能。例如,在北斗B1I信号中,Dl信号的额外调制层(即诺伊曼-霍夫曼码)的存在以及D2信号中较高的数据比特率可能会降低基于nwpr的C/No估计技术的性能。针对这一特殊问题,结合传统的基于nwpr的C/N0估计技术,对L1/E1/B1频段的4种不同GNSS信号分别实现了基于噪声估计的信噪功率比(SNPR)和信噪方差比(SNVR)两种C/N0估计技术。本文的目的是通过基于matlab的信号仿真以及硬件信号模拟器和软件定义的多gnss接收机来评估这三种C/N0估计技术的性能。仿真结果表明,基于SNPR和snvr的C/N0估计技术在微弱信号条件下以及在数据比特率较高的信号(即北斗bd2信号和伽利略El信号)下都比传统的基于nwpr的估计技术具有更好的估计性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance evaluation of carrier-to-noise density ratio estimation techniques for BeiDou Bl signal
The Carrier-to-Noise density ratio (C/N0) in a Global Navigation Satellite System (GNSS) receiver is an important parameter to measure the quality of a GNSS signal. The most traditional C/N0 estimation technique is implemented based on the Narrowband and the Wideband Power Ratio (NWPR), which works just perfectly for the legacy GPS LI C/A receiver. With the advent of new modernized GNSS signals from different systems, some basic signal characteristics of these signals have also changed in such a way that they might no longer enjoy the similar C/N0 estimation performance that NWPR-based C/N0 estimation does for GPS LI C/A signal. For example, in case of BeiDou B1I signal, the presence of an extra tier of modulation (i.e., Neumann-Hoffman code) for Dl signal, and the higher data bit rate in D2 signal may deteriorate the performance of NWPR-based C/No estimation technique. In view of this particular issue, two noise-estimation based C/N0 estimation techniques, namely Signal-to-Noise Power Ratio (SNPR) and Signal-to-Noise Variance Ratio (SNVR), are implemented along with the traditional NWPR-based C/N0 technique for four different GNSS signals in L1/E1/B1 bands. The objective of this paper is to evaluate the performance of these three C/N0 estimation techniques via Matlab-based signal simulations and also via hardware signal simulator and a software-defined multi-GNSS receiver. The simulation results show that the SNPR and SNVR-based C/N0 estimation techniques offer much better estimation performance than the traditional NWPR-based technique in weak signal condition and also with the signals which have relatively higher data bit rate (i.e., BeiDou Bl D2 signal and Galileo El signal).
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