高动态及微弱GPS信号的跟踪算法研究

发布时间：2018-04-26 07:33

本文选题：全球定位系统 + 高动态　；参考：《上海交通大学》2013年硕士论文

【摘要】：全球定位系统（GPS, Global Positioning System），是目前国际上最完善的卫星导航定位系统，可以为地球表面绝大部分地区（98%）提供连续实时的三维坐标信息、速度信息与授时服务。近年来，基于GPS的导航设备运用越来越广泛，在未来有着广阔的发展前景。GPS信号跟踪是在已经完成信号捕获的基础之上，实时地跟踪码相位变化和载波多普勒变化，实现接收机本地复现信号同输入信号的准确同步的过程，是GPS信号处理最重要的组成部分之一。传统的GPS信号跟踪环路采用延迟锁定环（Delay Locked Loop，DLL）和锁相环（PhaseLocked Loop，PLL）来实现码相位跟踪和载波跟踪，但是在高动态或是微弱信号的条件下，传统的跟踪环路由于其固有缺陷，性能大大下降。首先在高动态的环境下，由于GPS信号的多普勒频移过大，传统跟踪环路很容易失锁，跟踪精度也不够理想。本文采用了包含多普勒频移与码相位误差的二维观测相关器组，并通过基于列文伯格-马夸尔特方法优化的迭代扩展卡尔曼滤波算法，使跟踪环路在码相位与载波频率初始捕获误差较大的情况下，依然能够快速而准确地收敛，并成功解调出导航信息。仿真结果显示，利用新的GPS信号跟踪模型能够高质量地完成加速度为150g的高动态GPS信号的跟踪。其次，针对传统跟踪算法对微弱GPS信号跟踪困难、容易发散的缺陷，提出了一种新的跟踪算法。采用自适应卡尔曼滤波，减轻噪声对信号的影响，并通过列文伯格-马夸尔特优化方法，进一步提高自适应卡尔曼滤波算法的稳定性和收敛速度。仿真结果显示，利用新的算法对载噪比低至21dB-Hz的微弱GPS信号取得了良好的跟踪精度和极高的灵敏度。本文对GPS信号跟踪算法进行了详细的分析研究，针对两种不同的应用环境分别提出了改进的模型与算法，，并实验验证了算法的可行性，为今后更复杂情况下GPS信号应用的研究打下了坚实的基础。
[Abstract]:GPS (Global Positioning system) is the most perfect satellite navigation and positioning system in the world at present. It can provide continuous and real-time 3D coordinate information, velocity information and time service for most parts of the earth's surface. In recent years, the navigation equipment based on GPS is more and more widely used. In the future, GPS signal tracking is based on the completion of signal acquisition, tracking code phase changes and carrier Doppler changes in real time. It is one of the most important parts of GPS signal processing to realize the accurate synchronization of local replica signal and input signal. The traditional GPS signal tracking loop uses delay Locked loop (DLL) and phase locked loop (PLL) to realize code phase tracking and carrier tracking. However, under the condition of high dynamic or weak signal, the traditional tracking loop is due to its inherent defects. The performance is greatly reduced. Firstly, in the high dynamic environment, because of the large Doppler frequency shift of GPS signal, the traditional tracking loop is easy to lose lock, and the tracking accuracy is not ideal. In this paper, a two-dimensional observation correlator group with Doppler frequency shift and code phase error is adopted, and an iterative extended Kalman filter algorithm based on Levenberg-Marquardt method is proposed. The tracking loop can converge quickly and accurately when the initial acquisition error between the code phase and the carrier frequency is large, and the navigation information can be demodulated successfully. The simulation results show that using the new GPS signal tracking model, the high dynamic GPS signal with an acceleration of 150g can be tracked with high quality. Secondly, a new tracking algorithm is proposed to overcome the difficulty and divergence of the traditional tracking algorithm for weak GPS signals. Adaptive Kalman filter is used to reduce the influence of noise on the signal, and the stability and convergence speed of adaptive Kalman filter algorithm are further improved by Levenberg-Marquardt optimization method. Simulation results show that the new algorithm has good tracking accuracy and high sensitivity for weak GPS signals with low carrier to noise ratio as low as 21dB-Hz. In this paper, the GPS signal tracking algorithm is analyzed and studied in detail. The improved model and algorithm are proposed for two different application environments, and the feasibility of the algorithm is verified by experiments. It will lay a solid foundation for the research of GPS signal application in more complex cases in the future.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：P228.4

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