城市环境中短多径自适应抑制方法的研究

发布时间：2018-02-21 16:39

本文关键词： 导航定位多径残留误差卡尔曼滤波高度约束　出处：《东南大学》2017年硕士论文　论文类型：学位论文

【摘要】：全球导航卫星系统(Global Navigation Satellite System,GNSS)经过三十余年不断研究与发展,在军事和民用的各个领域产生了深刻影响。城市环境中由于高楼林立产生的短多径效应,成为GNSS观测值中的一个重要误差源,严重降低了定位精度。本文重点研究了卡尔曼滤波算法在抑制多径误差方面的应用,在此基础上研究复杂城市环境中的短多径自适应抑制方法。本文首先根据伪距定位原理建立球面定位模型,从理论上分析呈"矩形"分布和"震荡"分布的伪距误差对定位结果的影响,得出站心坐标系下三个方向上的定位误差也呈"矩形"和"震荡"分布且高度定位误差要大于东北平面水平定位误差的结论,并通过卫星信号模拟器仿真验证了该结论,并且,仿真结果表明高度定位误差约为水平定位误差的三倍。为解决高度定位误差大的问题,本文提出了一种基于高度约束的自适应卡尔曼滤波(Height Constrained Adaptive Kalman Filtering,HCAKF)算法,根据车载等低速接收机建立高度约束模型,通过构造高度上的约束条件和上一历元的接收机状态,利用最小均方误差原理来约束当前接收机的运动状态,从而使得定位结果更加准确。为验证HCAKF算法对短多径效应的抑制性能,分别在静态开放天空场景和直线运动场景下进行仿真测试,结果表明:静态开放天空场景下,HCAKF算法的高度定位误差几乎为零,水平定位误差相对于标准扩展卡尔曼滤波(Extended Kaman Filtering,EKF)算法减小了 25.36%,相对于AKF算法减小了 13.05%,总误差相对于EKF算法减小了 44.37%,相对于自适应卡尔曼滤波(Adaptive Kaman Filtering,AKF)算法减小了 39.86%;直线运动场景下,HCAKF算法的高度定位误差相对于EKF算法减小了 67.12%,相对于AKF算法减小了 47.63%,总误差相对于EKF算法减小了 63.50%,相对于AKF算法减小了 35.65%。为了对比本论文定位算法和市面上同类产品定位性能,建立了同信号源全球定位系统(Global Position System,GPS)/北斗二号(Beidou-2,BD2)卫星导航系统双模接收机验证平台。基于该双模接收机验证平台,在城市复杂环境中测试了 HCAKF算法的短多径抑制性能。测试结果表明:在窗台短多径静态环境中,HCAKF算法的高度定位误差几乎为零,水平定位误差相对于对照组减小了 48.44%,总体定位误差相对于对照组减小了 53.71%。在城市复杂动态环境下,HCAKF算法的高度定位误差相对于对照组减小了 69.24%,总体定位误差相对于对照组减小了 50.32%。
[Abstract]:After more than 30 years' continuous research and development, the Global Navigation Satellite system (GNSS) has had a profound impact in military and civilian fields. It has become an important error source in GNSS observations, which seriously reduces the positioning accuracy. In this paper, the application of Kalman filtering algorithm to the suppression of multipath errors is mainly studied. On this basis, the short and multi-track self-adaptive suppression method in complex urban environment is studied. Firstly, a spherical localization model is established according to the pseudo-range positioning principle. The influence of pseudo-range error of "rectangular" distribution and "oscillation" distribution on the positioning results is theoretically analyzed. It is concluded that the positioning error in three directions is also "rectangular" and "oscillating" in the geostationary coordinate system, and the height positioning error is larger than the horizontal positioning error in the northeast plane, which is verified by the simulation of the satellite signal simulator. The simulation results show that the height location error is about three times that of the horizontal positioning error. In order to solve the problem of large height location error, a height Constrained Adaptive Kalman filtering algorithm based on height constraint is proposed in this paper. The height constraint model is established according to the vehicle equal low speed receiver. By constructing the height constraint condition and the receiver state of the previous epoch, the moving state of the current receiver is constrained by the principle of minimum mean square error. In order to verify the performance of the HCAKF algorithm to suppress the short multipath effect, the simulation tests are carried out in the static open sky scene and the linear motion scene, respectively. The results show that the altitude location error of HCAKF algorithm is almost zero in the static open sky scene. Compared with the standard extended Kaman filtering algorithm, the horizontal location error is reduced by 25.36, compared with the AKF algorithm by 13.05, the total error is reduced by 44.37 compared with the EKF algorithm, and the adaptive Kaman filtering algorithm is reduced by the adaptive Kalman filter algorithm. The height error of EKF algorithm is reduced 67.12 compared with that of EKF algorithm, the total error is reduced by 63.50 and 35.65 points relative to EKF algorithm, compared with AKF algorithm, the total error is reduced by 63.50 and 35.65 respectively, compared with that of EKF algorithm, the total error is reduced by 63.50 and 35.65, respectively, and that of EKF algorithm is reduced by 67.63 compared with AKF algorithm, and the total error is reduced by 63.50 compared with EKF algorithm. Comparing the localization algorithm of this paper with the localization performance of similar products on the market, A dual-mode receiver verification platform for Global Position system (GPS) / Beidou-2 (BD2) satellite navigation system with the same signal source is established. The short multipath suppression performance of HCAKF algorithm is tested in complex urban environment. The test results show that the height location error of HCAKF algorithm is almost zero in the short multipath static environment of window sill. Compared with the control group, the horizontal positioning error was reduced by 48.44 and the overall positioning error was reduced by 53.71.The height positioning error of HCAKF algorithm was reduced by 69.24and the total positioning error was decreased compared with the control group in the complex dynamic environment of the city. The difference was 50.32 in comparison with the control group.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN967.1

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