高动态GNSS接收机载波跟踪的性能研究
发布时间：2019-03-18 10:06
【摘要】：目前,全球卫星导航系统(GNSS)已经渗透到世界各国的诸多领域中,成为一种提供全天候导航定位服务的空间信息基础设施。GNSS具有广阔的应用前景与巨大的产业化效益,各航天大国都在极力研制和推广各自的导航接收机。然而,在航空、航天与导弹制导等应用领域,卫星信号的多普勒频移及其变化率非常大,传统的载波跟踪环路难以承受由高速运动带来的动态应力,极易失锁,接收机无法工作。本文拟解决高动态环境下接收机载波跟踪环路的性能优化与鲁棒性设计等问题,为我国高动态GNSS导航接收机的研制提供一定的理论基础。 本文首先介绍GNSS的系统构成与接收机组成原理,其次构建高动态GNSS信号模型并产生基带中频信号源,然后阐明了传统跟踪环路对动态应力的局限性和基于信号参数估计理论的跟踪环路。最后,针对接收机的高动态运动模型,将卡尔曼滤波理论与粒子滤波理论引入环路的结构设计,以突破传统跟踪环路性能上的局限,提出几种适用于高动态环境的载波跟踪环路。本文的主要工作可以概括如下： (1)为解决传统环路中带宽必须在动态应力与跟踪精度间折中的矛盾,对最优带宽优化算法展开研究,提出了一种基于强跟踪自适应滤波(ASTF)的高动态载波跟踪环路,并设计两种实现结构：带鉴别器的闭环结构与参数估计结构。通过对ASTF环路的性能分析,推导闭环结构与锁相环的结构等效性,证明强跟踪机制带来的稳态带宽调整能力,最后探讨参数估计结构与闭环结构的性能差异。 (2)针对ASTF环路在处理非线性观测模型时求解雅各比矩阵带来的跟踪精度降低与算法复杂度高的问题,在平方根无迹卡尔曼滤波中引入基于新息协方差的自适应渐消因子,提出了一种基于自适应平方根无迹卡尔曼滤波(ASRUKF)的高动态载波跟踪环路,并设计其参数估计的实现结构。由于UT变换的逼近精度达到了二阶以上,ASRUKF环路的跟踪精度较ASTF更高。 (3)基于贝叶斯最优估计与粒子滤波理论,提出了一种基于高斯粒子滤波(GPF)的高动态载波跟踪环路,设计了相应的环路实现方案,并对其进行性能分析。为解决GPF对初始值敏感和建议分布不合理的问题,在原有算法框架下提出两种优化方法：强跟踪滤波优化(STF-GPF)和无迹卡尔曼滤波优化(UGPF),增强了GPF的鲁棒性和滤波精度。GPF环路利用粒子滤波的优越性能,有效地提高了接收机的灵敏度和跟踪性能。 本文所提出的算法在软件接收机平台上进行高动态仿真测试,验证了算法的可行性,并取得良好的跟踪性能,对我国高动态GNSS接收机的性能优化算法研究有一定的借鉴意义。
[Abstract]:At present, Global Satellite Navigation system (GNSS) has penetrated into many fields all over the world and become a kind of spatial information infrastructure to provide all-weather navigation and positioning service. All the big spaceflight countries are making great efforts to develop and promote their navigation receivers. However, in the fields of aerospace, aerospace and missile guidance, the Doppler frequency shift and its rate of change of satellite signals are very large, and the traditional carrier tracking loop is difficult to withstand the dynamic stress caused by high-speed motion, so it is easy to lose lock. The receiver does not work. In this paper, the performance optimization and robustness design of carrier tracking loop in high dynamic environment are solved, which provides a theoretical basis for the development of high dynamic GNSS navigation receiver in China. In this paper, the structure of GNSS system and the principle of receiver are introduced firstly. Secondly, the high dynamic GNSS signal model is constructed and the baseband intermediate frequency signal source is generated. Then the limitation of the traditional tracking loop to the dynamic stress and the tracking loop based on the theory of signal parameter estimation are expounded. Finally, aiming at the high dynamic motion model of the receiver, Kalman filter theory and particle filter theory are introduced into the loop structure design to break through the limitations of the traditional tracking loop performance. Several carrier tracking loops suitable for high dynamic environment are proposed. The main work of this paper can be summarized as follows: (1) in order to solve the contradiction between dynamic stress and tracking accuracy in traditional loop, the optimal bandwidth optimization algorithm is studied. A high dynamic carrier tracking loop based on strong tracking adaptive filter (ASTF) is proposed and two implementation structures are designed: closed loop structure with discriminator and parameter estimation structure. By analyzing the performance of the ASTF loop, the equivalence of the closed loop structure and the phase locked loop structure is deduced, and the steady-state bandwidth adjustment capability brought by the strong tracking mechanism is proved. Finally, the performance difference between the parameter estimation structure and the closed loop structure is discussed. (2) in order to solve the problem of reduced tracking accuracy and high algorithm complexity caused by Jacobi matrix when ASTF loop is used to deal with nonlinear observation model, an adaptive fading factor based on innovation covariance is introduced into square root unscented Kalman filter. A high dynamic carrier tracking loop based on adaptive square root unscented Kalman filter (ASRUKF) is proposed and its parameter estimation architecture is designed. Because the approximation accuracy of UT transform is higher than the second order, the tracking accuracy of ASRUKF loop is higher than that of ASTF. (3) based on Bayesian optimal estimation and particle filter theory, a high dynamic carrier tracking loop based on Gao Si particle filter (GPF) is proposed. The corresponding loop implementation scheme is designed and its performance is analyzed. In order to solve the problem of sensitivity of GPF to initial values and unreasonable distribution of recommendations, two optimization methods, strong tracking filter (STF-GPF) and unscented Kalman filter (UGPF), are proposed in the framework of the original algorithm. The GPF loop makes use of the superior performance of particle filter to improve the sensitivity and tracking performance of the receiver effectively. The algorithm proposed in this paper is tested on the software receiver platform by high dynamic simulation, and the feasibility of the algorithm is verified, and good tracking performance is obtained. It can be used for reference to study the performance optimization algorithm of high dynamic GNSS receiver in our country.
【学位授予单位】：厦门大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN965.5
本文编号：2442757
[Abstract]:At present, Global Satellite Navigation system (GNSS) has penetrated into many fields all over the world and become a kind of spatial information infrastructure to provide all-weather navigation and positioning service. All the big spaceflight countries are making great efforts to develop and promote their navigation receivers. However, in the fields of aerospace, aerospace and missile guidance, the Doppler frequency shift and its rate of change of satellite signals are very large, and the traditional carrier tracking loop is difficult to withstand the dynamic stress caused by high-speed motion, so it is easy to lose lock. The receiver does not work. In this paper, the performance optimization and robustness design of carrier tracking loop in high dynamic environment are solved, which provides a theoretical basis for the development of high dynamic GNSS navigation receiver in China. In this paper, the structure of GNSS system and the principle of receiver are introduced firstly. Secondly, the high dynamic GNSS signal model is constructed and the baseband intermediate frequency signal source is generated. Then the limitation of the traditional tracking loop to the dynamic stress and the tracking loop based on the theory of signal parameter estimation are expounded. Finally, aiming at the high dynamic motion model of the receiver, Kalman filter theory and particle filter theory are introduced into the loop structure design to break through the limitations of the traditional tracking loop performance. Several carrier tracking loops suitable for high dynamic environment are proposed. The main work of this paper can be summarized as follows: (1) in order to solve the contradiction between dynamic stress and tracking accuracy in traditional loop, the optimal bandwidth optimization algorithm is studied. A high dynamic carrier tracking loop based on strong tracking adaptive filter (ASTF) is proposed and two implementation structures are designed: closed loop structure with discriminator and parameter estimation structure. By analyzing the performance of the ASTF loop, the equivalence of the closed loop structure and the phase locked loop structure is deduced, and the steady-state bandwidth adjustment capability brought by the strong tracking mechanism is proved. Finally, the performance difference between the parameter estimation structure and the closed loop structure is discussed. (2) in order to solve the problem of reduced tracking accuracy and high algorithm complexity caused by Jacobi matrix when ASTF loop is used to deal with nonlinear observation model, an adaptive fading factor based on innovation covariance is introduced into square root unscented Kalman filter. A high dynamic carrier tracking loop based on adaptive square root unscented Kalman filter (ASRUKF) is proposed and its parameter estimation architecture is designed. Because the approximation accuracy of UT transform is higher than the second order, the tracking accuracy of ASRUKF loop is higher than that of ASTF. (3) based on Bayesian optimal estimation and particle filter theory, a high dynamic carrier tracking loop based on Gao Si particle filter (GPF) is proposed. The corresponding loop implementation scheme is designed and its performance is analyzed. In order to solve the problem of sensitivity of GPF to initial values and unreasonable distribution of recommendations, two optimization methods, strong tracking filter (STF-GPF) and unscented Kalman filter (UGPF), are proposed in the framework of the original algorithm. The GPF loop makes use of the superior performance of particle filter to improve the sensitivity and tracking performance of the receiver effectively. The algorithm proposed in this paper is tested on the software receiver platform by high dynamic simulation, and the feasibility of the algorithm is verified, and good tracking performance is obtained. It can be used for reference to study the performance optimization algorithm of high dynamic GNSS receiver in our country.
【学位授予单位】：厦门大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN965.5
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