摘要
GNSS接收机的基带处理主要包括两个环节：捕获和跟踪。这两者就实质来说分别是统计信号的检测和估计问题。近年来，矢量跟踪由于其在弱信号及抗干扰方面的突出优点，成为学界和业界的研究重点和热点。所谓“矢量”，是指估计滤波器的状态变量是元素数目大于等于2的向量，而对应的“标量”主要指传统的接收机理论中锁相环输出的只是单一的码相位或载波相位标量。矢量跟踪领域目前尚未解决的主要有两个问题：一、矢量跟踪性能优于标量跟踪的理论依据；二、矢量跟踪的实时实现。目前没有统一的理论解释第一个问题；至于第二个问题，国内外目前均缺乏相应的报道。因此，本文研究的目标是解决第一个问题，突破第二个问题的理论问题。
本文深入研究了接收机灵敏度影响因素；创新的高灵敏算法，并研究这些算法对接收机定位精度的影响，实现矢量跟踪在提高接收灵敏度方面的原理和方法；完成上述接收机的L1GPS/Galileo实时和后处理样机各一台，研究软件接收机的优化程序架构。主要研究工作和方法体现在三个方面：
(1)研究接收机灵敏度影响参数的一体化确定方法，包括前端带宽、量化位数、量化策略、采样频率等的作用。
本部分着重研究GNSS软件接收机射频前端配置（包括采样频率、量化、前端带宽等）对后续基带信号处理结果的影响。影响的评估通过建模、理论推导及数值仿真，将理想情况（无量化、前端带宽无限大、采样频率无限高）和实际应用（不同量化策略、多种有限带宽、特定采样频率）进行对比，将两种情况下的差值定义为损耗，以损耗值的大小评价当前前端配置的合理性，从而决定接收机的频率方案（frequency plan）。此外，以L1单频软件接收机的实现为支撑，对比模拟值和实际值，检验模型的有效性能。
(2)研究并实现矢量跟踪在提高接收灵敏度方面的原理和方法。
矢量跟踪环以扩展卡尔曼滤波为工具，用一个大环路代替原来的两步估计方案。传统的接收机的两步估计方法是指：第一步，用码跟踪环完成本地码与接收信号伪随机码的精确对准，以此估计伪距（pseudorange），第二步，用扩展卡尔曼滤波器以伪距为输入值估计出接收机天线相位中心的状态量（如最基本的四状态量：天线中心的三维坐标以及接收机钟差；抑或是常用的八状态量：三维坐标、三维速度、接收机钟差以及接收机钟漂）。矢量跟踪环用一个大环路代替传统接收机中的这两个小环路，一步算出天线相位中心的状态。因此，如何列写卡尔曼方程的状态方程和观测方程，是本部分需要解决的第一个问题。当然，纯粹的卡尔曼滤波方程不能解决问题，因为计算量过于庞大了，目前通行的方法是用联合卡尔曼滤波结构实现实时矢量环接收机，本文描述的矢量环接收机研制也将如此进行。
(3)完成上述接收机的L1GPS/Galileo实时和后处理样机各一台。
本论文研究的关键技术和创新点主要体现在以下几个方面：
(1)首次完整研究GNSS接收机前端设计所有因素（最后一级带宽、量化策略、采样频率等）对接收机灵敏度的影响（第二章）。
目前，Christopher Hegarty对最后一级带宽、量化策略以及采样频率对接收机implementation loss的联合作用提出理论预测公式。由于该公式囊括了incommensurate sampling以及任意整数位量化的作用，因此它是该领域内目前考虑最为完善的结果。但该方法尚缺对任意位数(包括非整数位数)量化作用的影响。而这就是本文对该领域的创新贡献。本文最终将形成一个通用的性能预测公式，这对用于接收GNSS新信号的接收机前端设计具有决定性的指导意义。
(2)指出John Betz关于接收机DLL误差方差公式的错误，提出修正公式，并得到认可（附录A），即：
若将未经平滑的DLL的TOA估计值的方差记为σ_u~2，则经过平滑的TOA估计值的方差（记为σ_s~2）可以用下式表达：σ_s~2=σ_s~2_u~2B_LT
这里有一点需要说明。在Betz公式[10]中，σ_s~2用下式表达而非上式：σ_s~2≈σ_u~2B_LT (1-0.5B_LT)
事实上，后式比前式多出来的那一项因子(1-0.5BLT)是个推导过程中的失误造成的。在~([10])中，用了一个零阶保持电路~([62])将数字信号又转成了模拟信号，真实接收机里这个环节是不存在的，而且为最终结果引入了一个低频成分，因此后式是个错误的结论。根据一般的跟踪环理论得出的结果应该是σ_s~2≈σ_u~2B_LT。
A GNSS Rx baseband has two functions: acquisition and tracking, which isbasically a detection and estimation problem of statistical signal respectively. Inrecent years, vector tracking attracts far more attention than other issues in GNSSreceiver due to its promising advantages in weak signal processing, interferencemitigation and potential for migration into a INS/GNSS deep integration system. Theword vector, as it implies, means there are more than one state to estimate in thesignal estimation (tracking) problem and hence when it comes to implementation, thestate is a vector (e.g. a vector of positions, velocities and clock parameters of thevehicle) rather than a single variable (e.g. code phase or carrier phase in a traditionalscalar receiver) in the filtering mechanization. Two questions remain totallyunresolved in this field: first is lack of unified theorem explaining the superiorities ofvector loop over scalar loop and second is the real-time implementation of a vectorsoftware receiver. This dissertation is dedicated to solving the first problem and tryingto shed some light on the second one.
The thesis focus on the theory and implememtation of vector tracking loop in aGNSS receiver. In detail, it includes the following three aspects:
(1) Performance metric. Obviously we need a performance metric to prove theeffectiveness of our filter, but existing ones are inappropriate to use. As a result, thisthesis proposes a unique method–tracking loss in meters to evaluate front-endparameters’ effects on the variance of the output of a code-tracking loop. Suchparameters are front-end bandwidth, number of bits used in quantization and samplingfrequency. The metric gives a single indicator instead of three separate values, toindicate how different combinations of these three parameters will degrade theprecision of code tracking, as opposed to the ideal situation where positive infinitequantization bit, sampling frequency and front-end bandiwth are assumed. This metricis used to determine the frequency-plan of the real-time SW receiver, described inChapter7in this thesis.
(2) Theory and mechanization of a vector tracking loop. Take vector delay-lockloop (VDLL) as an example. VDLL is a further generalization of the extended kalman filter (EKF). VDLL closes the loop all the way back to the signal correlators insteadof having two separate sets of shorter loops (delay lock loops and the EKF loop).Transition from a scalar receiver to its vector version nessecitates examination oftheory and mechanization of a VTL. Kalman filter parameters such as process andmeasurement covariance matrices have to be taken with extreme care. The secondsubtask is to explain the superiority of a vector receiver over a scalar receiver usingcovariance analysis.
Vector tracking loop (VTL) including VDLL (Vector DLL), VPLL (Vector PLL)and VFLL (Vector FLL) is one of the most promising architectures fornext-generation Global Navigation Satellite System (GNSS) receiver due to itsrobustness during unplanned GNSS satellite outages and in adverse environments (e.g.Radio Frequency Interference (RFI) or user high dynamics), improved accuracy ofnavigation solutions compared with that of traditional receivers using scalar loopsunder regular conditions, and most important of all, easy integration with inertialNavigation System (INS) measurements to form an ultra-tight INS/GNSS integratedsystem. In the current State High Technology Project (or863), a real-timehigh-sensitivity receiver with Interference Detection and Mitigation (IDM) capabilityis required to form the core of the GNSS Vulnerability Assessment and ValidationPlatform (VAVE). As a result, an ultra-tightly coupled GNSS/INS structure wasdecided on and as a natural first step, a software vector GNSS receiver has to berealized for research and fast-prototyping.
There has long been interest in theoretical analysis and implementation of VTL.Nonetheless, previous efforts to implement the vector tracking structure often focuson either post-processing data collected from a front-end or offering limited view ondetails of real-time implementation. In addition, system parameters of the VTLimplementation are often chosen in an empirical rather than an analytical way. Thispaper tries to address these two issues by presenting a panoramic view on design andreal-time implementation of an open-source Global Navigation Satellite System(GNSS) software receiver restructured to use vector delay-lock loop for signaltracking. Drive test results on navigation solutions under stringent conditions areprovided to prove the performance margin over traditional scalar loop.
This particular part is structured as follows. The second sub-section defines theproblem being analyzed, introduces the notation and assumptions that are employed,and develop the measurement and system model for the extended Kalman filter (EKF)structure of VTL. However, for real-time employment of the equations, this configuration has to be slightly restructured. Therefore a cascaded (or federated) EKFis developed and described.
The third subsection describes the implementation of a post-processing VTLreceiver, which has been developed as a research and teaching tool in university lab toprovide useful insights in parameter tuning, especially the determination of the Q andR matrix (i.e. the covariance matrix of system noise due to user dynamics andnon-modeling error, and the covariance matrix of measurement noise represented bydiscriminator output noise and due to the nonlinearities of receiver such as the jointeffects of precorrelation filtering, sampling and quantization) of the Kalman filter.
(3) Implementation
First we give the details of the real-time implementation of VTL in a softwarereceiver. A widely-used USB FE, GN3sV2, designed by CCAR of University ofColorado, Boulder is used to provide digital Intermediate Frequency (IF) samples tothe receiver. This FE has sufficient bandwidth for GPS L1C/A and Galileo E1B/C(only BOC(1,1)). Since originally, there is an upper limit to the data grabbed by thefront-end, it has to be flashed to lift off this limit for continuous operation of thesoftware receiver. The VTL software receiver is a modified version of an open-sourcereceiver, GPS-SDR, which is widely used in researches on GNSS signal-processing.The architecture of the VTL receiver is exposed by using a state flow chart, where theinitialization of the VDLL and the definition of measurement epoch and integrationepoch are emphasized. The system parameters are also provided and threshold for lossof lock in the context of VDLL is established. Later this GN3sV2FE will be replacedby a USRP2to explore SCA.
Next we present the navigation performance by comparing the vector trackingreceiver with its scalar tracking counterpart in drive test. The results confirm that thatthe former is much superior to the latter in terms of robustness in poor satellitevisibility and noise in the navigation solutions.
The last subsection summarizes the paper and discusses the framework for futurework, especially its promising prospects in UAS (Unmanned Aerial System)
All in all, a VTL is the very starting point for INS/GPS deep integration. This isthe ultimate goal of the work described in this thesis–to provide theorectical andexperimental results for future efforts to implement a lab deep integration prototype.
引文
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