GNSS系统弱信号捕获技术研究

发布时间：2018-01-24 17:46

本文关键词： GNSS 弱信号捕获 PMF-FFT 加窗　出处：《广东工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：全球导航卫星系统GNSS(Global Navigation Satellite System)发展至今,美国的GPS导航系统已经深入而广泛的应用到各个领域,俄罗斯的GLONASS、欧盟的GALILEO系统以及我国正在发展的北斗导航系统等也逐渐普及。目前导航定位技术在诸多领域都担任着重要的角色,人们对于导航定位技术的要求给导航定位技术带来极大挑战。多数应用中需要有GNSS系统的精确定位。信号同步过程是GNSS系统能精确定位的前提,要实现信号的同步,首先要完成捕获过程,然后才能进入跟踪阶段。但低轨道处的GNSS系统由于其传播信道的复杂性,在传播过程中容易受到大幅度衰减以及噪声的影响,到达地面的信号可能经历反射、折射等环境因素的干扰,加上接收机的快速移动问题,从而产生各种衰落,导致存在着较大的多普勒频偏及码延迟。这样,接收码和本地伪码同步过程中的相关峰值将会急剧下降,GNSS接收机对伪码捕获的难度加大,捕获时间延长。且由于无线设备接收到的信号功率非常低,通常载噪比C/N。小于25dB-Hz,传统的GNSS信号接收机甚至无法正常工作。因此,在弱信号环境下,实现伪码和多普勒频偏的快速捕获,无论在民用领域或是军事领域都具有重要的研究意义。目前,GNSS弱信号捕获主要可分为辅助型和无辅助两种,而无辅助的GNSS弱信号捕获技术主要以提高信号处理增益和合理选择捕获策略为主。针对以上问题,本文就基于PMF-FFT的弱信号捕获算法进行优化,再将基于PMF-FFT的码捕获算法与几种频偏估计算法进行结合,对联合捕获算法进行加窗减少扇贝损失,改善频偏对捕获概率的影响。并在不同的移动速度下,通过MATLAB仿真结果找出该速度和环境下最合适的捕获方法。本文的主要工作可以概括为以下四点： 1.深入研究GNSS信号结构及捕获定位技术,并建立数学模型； 2.分析部分匹配滤波PMF的原理以及用于捕获算法中的优势； 3.总结分析现有的GNSS系统弱信号环境下基于部分匹配滤波的码捕获算法； 4.对弱信号条件下基于PMF-FFT的码和多普勒联合捕获算法进行加窗处理,减小扇贝损失,提高检测概率,并在不同移动速度下对比仿真结果选择最优捕获算法。
[Abstract]:Global navigation satellite system (GNSS(Global Navigation Satellite system) has been developed so far. The GPS navigation system of the United States has been deeply and widely used in various fields, Russia's GLONASS. The GALILEO system of the European Union and the Beidou navigation system which is developing in our country are also gradually popularized. At present, the navigation and positioning technology plays an important role in many fields. The requirement of navigation and positioning technology brings great challenge to navigation and positioning technology. In most applications there is a need for accurate positioning of GNSS system. Signal synchronization is the premise of accurate positioning in GNSS system. In order to achieve signal synchronization the first step is to complete the acquisition process. But the GNSS system in low orbit is vulnerable to large attenuation and noise due to the complexity of its propagation channel. The signal arriving at the ground may experience the interference of environmental factors such as reflection refraction and so on plus the problem of the fast moving of the receiver which results in a variety of fading which leads to the existence of large Doppler frequency offset and code delay. The correlation peak value in the synchronization process between the received code and the local PN code will dramatically reduce the difficulty of GNSS receiver acquisition of PN code, and the acquisition time will be prolonged. Moreover, the signal power received by wireless equipment is very low. Usually the carrier noise ratio C / N. Is less than 25dB-Hz. the traditional GNSS signal receiver can not even work normally. Therefore, in the weak signal environment, the fast acquisition of pseudo-code and Doppler frequency offset is realized. It is of great significance in both civil and military fields. At present, the weak signal acquisition of GNSS can be divided into two types: auxiliary and non-auxiliary. But the unaided GNSS weak signal acquisition technology is mainly to improve the signal processing gain and reasonably select the acquisition strategy. In this paper, the weak signal acquisition algorithm based on PMF-FFT is optimized, and then the code acquisition algorithm based on PMF-FFT is combined with several frequency offset estimation algorithms. The joint acquisition algorithm is windowed to reduce scallop loss, and the influence of frequency offset on acquisition probability is improved. Through the MATLAB simulation results to find out the most suitable capture method under this speed and environment. The main work of this paper can be summarized as follows: 1. Deeply study the structure of GNSS signal and capture and position technology, and establish mathematical model; 2. Analyze the principle of partial matched filter (PMF) and its advantages in acquisition algorithm; 3. The code acquisition algorithm based on partial matched filter in weak signal environment of GNSS system is summarized and analyzed. 4. The joint acquisition algorithm of code and Doppler based on PMF-FFT under weak signal condition is windowed to reduce fan. The detection probability is improved and the optimal acquisition algorithm is selected by comparing the simulation results with different moving speeds.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN96.1

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