Modeling long-period noise in kinematic GPS applications

We develop and test an algorithm for modeling and removing elevation error in kinematic GPS trajectories in the context of a kinematic GPS survey of the salar de Uyuni, Bolivia. Noise in the kinematic trajectory ranges over 15 cm and is highly autocorrelated, resulting in significant contamination of the topographic signal. We solve for a noise model using crossover differences at trajectory intersections as constraints in a least-squares inversion. Validation of the model using multiple realizations of synthetic/simulated noise shows an average decrease in root-mean-square-error (RMSE) by a factor of four. Applying the model to data from the salar de Uyuni survey, we find that crossover differences drop by a factor of eight (from an RMSE of 5.6 to 0.7 cm), and previously obscured topographic features are revealed in a plan view of the corrected trajectory. We believe that this algorithm can be successfully adapted to other survey methods that employ kinematic GPS for positioning.     

An intelligent and autonomous MEMS IMU/GPS integration scheme for low cost land navigation applications

An intelligent scheme to integrate inertial navigation system/global positioning system (GPS) is proposed using a constructive neural network (CNN) to overcome the limitations of current schemes, namely Kalman filtering (KF). The proposed CNN technique does not require prior knowledge or empirical trials to implement the proposed architecture since it is able to construct its architecture “on the fly,” based on the complexity of the vehicle dynamic variations. The proposed scheme is implemented and tested using Micro-electro-mechanical systems inertial measurement unit data collected in a land-vehicle environment. The performance of the proposed scheme is then compared with the multi-layer feed-forward neural networks (MFNN) and KF- based schemes in terms of positioning accuracy during GPS signal outages. The results are then analyzed and discussed in terms of positioning accuracy and learning time. The preliminary results presented in this article indicate that the positioning accuracy were improved by more than 55% when the MFNN and CNN-based schemes were implemented. In addition, the proposed CNN was able to construct the topology by itself autonomously on the fly and achieve similar prediction performance with less hidden neurons compared to MFNN-based schemes.     

Efficient interpolations to GPS orbits for precise wide area applications

For precise real time or near real time differential GPS positioning in a wide or global area, precise GPS orbits or, alternatively, precise orbital corrections with respect to a reference orbit, such as GPS broadcast ephemerides, must be used. This work tests orbit interpolation methods, in order to represent the GPS orbits and orbital corrections accurately and efficiently for these and other GPS applications. For precise GPS orbits given in the SP3 format at the 15 min interval, numerical tests were conducted using Lagrange and Chebyshev as well as trigonometric polynomial functions. The results have demonstrated that the 19- or 20-term trigonometric function is apparently the most efficient interpolator for a 12 h GPS orbital arc, achieving 1 cm level 3D interpolation accuracy that can meet the requirements of most precise applications. The test results also demonstrated that the 9-term trigonometric function always yields optimal interpolation for a 2 h GPS orbit arc, in terms of interpolation errors, compared to the results when using a different number of terms for the same function or one of the other tested polynomial functions. This is evident from the minimal performance degradation when using the 9-term trigonometric function to interpolate near or at the end of a data interval. By limiting interpolation to the center 15 min to 1.5 h of a 2 h orbit arc, thereby eliminating the need to interpolate near the ends of that interval, users can opt for more terms (11 and 13) or different interpolators to further improve interpolation accuracy. When interpolating the orbital corrections with respect to the GPS broadcast ephemeris, all the tested interpolation functions of 3- to 9-term yield the same suitably accurate results. Therefore, a 3- to 5-term trigonometric function is arguably sufficiently accurate and more efficient for GPS orbital correction messaging in wide area and real time positioning.     

一种改进的GPS随机模型建模方法

针对观测序列的异方差和时相关特性相互影响但又难以并行建模的问题,提出了一种迭代、序贯处理异方差和时相关问题的随机模型建模方案。实验结果显示,该方法较好地解决了异方差和时相关特性无法并行建模的难题,极大地消除了多路径及系统残余误差对GPS定位成果的影响,增加了基线数据处理的可靠性。     

GPS滑坡监测系统在铁路桥桥墩稳定性监测中的应用

结合对铁路桥桥墩的实际监测应用,介绍了GPS滑坡监测系统的工作原理和性能特点,阐述了现场安装过程中的许多重点问题及其对监测效果的影响,并结合实际测量数据论证了该系统应用于滑坡监测的可行性和优势所在。     

Forward modeling of GPS multipath for near-surface reflectometry and positioning applications

Multipath is detrimental for both GPS positioning and timing applications. However, the benefits of GPS multipath for reflectometry have become increasingly clear for soil moisture, snow depth, and vegetation growth monitoring. Most multipath forward models focus on the code modulation, adopting arbitrary values for the reflection power, phase, and delay, or they calculate the reflection delay based on a given geometry and keep reflection power empirically defined. Here, a fully polarimetric forward model is presented, accounting for right- and left-handed circularly polarized components of the GPS broadcast signal and of the antenna and surface responses as well. Starting from the fundamental direct and reflected voltages, we have defined the interferometric and error voltages, which are of more interest in reflectometry and positioning applications. We examined the effect of varying coherence on signal-to-noise ratio, carrier phase, and code pseudorange observables. The main features of the forward model are subsequently illustrated as they relate to the broadcast signal, reflector height, random surface roughness, surface material, antenna pattern, and antenna orientation. We demonstrated how the antenna orientation—upright, tipped, or upside-down—involves a number of trade-offs regarding the neglect of the antenna gain pattern, the minimization of CDMA self-interference, and the maximization of the number of satellites visible. The forward model was also used to understand the multipath signature in GPS positioning applications. For example, we have shown how geodetic GPS antennas offer little impediment for the intake of near-grazing reflections off natural surfaces, in contrast to off metal, because of the lack of diversity with respect to the direct signal—small interferometric delay and Doppler, same sense of polarization, and similar direction of arrival.     

The topological viewshed: embedding topological pointers into digital terrain models to improve GIS capability for visual landscape analysis

The effort to develop a Digital Earth has made dramatic progress in terms of visualisation and visual data integration for use-cases which demand semantically rich analysis. To provide this analysis and ensure legitimate representations of the spatial data from which visualisation are derived, it is necessary to provide more comprehensive analytical capabilities of the view. Questions of aesthetic valuation of landscape require a richer analytical response than simply ‘whether and possibly how much of’ an object or area of land can be seen. It requires interrogation of the scene as it appears and to distinguish between transient visual effects and those locally invariant to view point change. This paper explores a data structure to support scene analytics. As such, it first reviews the existing techniques from the fields of GIS and computer graphics as to their potential and limitations in providing a qualitatively more nuanced visual analysis. It then introduces a new method of encoding visually apparent relationships into terrain models. A prototype implementation is presented based on the Quad-Edge Triangular Irregular Network, though it is believed that raster or vector implementation would be possible. Although developed primarily with landscape analysis in mind, the method could have wider applicability.     

遥感图像中GPS控制点的建立

利用GPS和高精度GAMIT计算软件,沿长江建立了以宜昌、监利、锣山、武汉4个地区的遥感控制点。每个测区采用设置长时间控制点观测,将其与武昌九峰GPS观测点进行联合处理,使得每个控制点的精度高于0.5m,保证了控制点精度满足1m遥感卫星图像的纠正要求。     

GPS模糊度降相关LLL算法的一种改进

针对LLL(Lenstra,Lenstra,Lovasz algorithm)算法的不足,提出了具有自适应性的整数正交变换算法,并采用此算法和升序排序调整矩阵对LLL算法进行了改进。通过LLL算法和改进的LLL算法对随机模拟的600个对称正定矩阵的模糊度方差-协方差阵和30组实测数据进行处理分析,发现改进的LLL算法能够更有效地降低协方差阵的条件数,减小备选模糊度组合数,更有利于整周模糊度的搜索和解算。     

GPS基线向量网粗差定位试验

应用文献[1]中提出的关于粗差定位的逐个搜索法,研究了GPS基线向量网的粗差定位问题;同时改进了粗差定位的逐个搜索法。通过研究以及大量的粗差定位试验表明;应用改进的逐个搜索法进行多个粗差定位,只要粗差个数满足n_g≤1.95n_b-3p+3,且任一点上至少有三条基线通过,则不论粗差位于何处,都能正确定位,并较准确地给出粗差的估值。文中还对GPS网的布网方案提出了合理的建议。     

An Artificial Intelligent design for GPS Surveying Networks

Metaheuristic techniques, which are based on ideas of Artificial Intelligence, are among the best methods for solving computationally the GPS surveying network problem. In this paper, the ant colony optimization metaheuristic, which is inspired by the behavior of real ant colonies, is developed to efficiently provide a general framework for optimizing GPS surveying networks. In this framework, a set of ants co-operate together using an indirect communication procedure to find good GPS observation schedules. A GPS surveying network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order in which to observe these sessions to give the best schedule at minimum cost. Computational results obtained by applying the proposed technique on several networks, with known and unknown optimal schedules, prove the effectiveness of the proposed metaheuristic technique to solve the GPS surveying network problem.     

一种改进的GPS区域叠加滤波算法

GPS时间序列的空间滤波可以提高观测数据的信噪比,有利于获取更高精度的地壳形变信息。区域叠加滤波算法的空间滤波结果随着测站数和空间尺度不同而不同,不利于研究GPS时间序列中的形变信息。为了削弱区域叠加滤波受空间尺度的影响,提出一种不以空间尺度作为约束条件,同时引入相关系数和距离因子的区域叠加滤波算法。采用2010—2017年中国区域260个GPS连续观测站的时间序列展开空间滤波方法的研究,计算结果表明,对比相关性区域叠加滤波算法,考虑GPS时间序列之间的相关系数和距离因子更有利于提取GPS时间序列中的共模误差,且受空间尺度的影响较小。对比3种不同距离因子的区域叠加滤波算法,可知引入距离反比的空间滤波算法可实现更优的空间滤波。采用该方法空间滤波后可使GPS时间序列残差降低30%~40%,GPS速度场精度提高30%~40%。此算法实现了更优的GPS形变场估计,为研究中国区域的地壳运动和其动力学机制提供了可靠的数据基础。     

Ionospheric correction using NTCM driven by GPS Klobuchar coefficients for GNSS applications

Global Navigation Satellite Systems (GNSS) require mitigation of ionospheric propagation errors because the ionospheric range errors might be larger than tens of meters at the zenith direction. Taking advantage of the frequency-dispersive property of ionospheric refractivity, the ionospheric range errors can be mitigated in dual-frequency applications to a great extent by a linear combination of carrier phases or pseudoranges. However, single-frequency GNSS operations require additional ionospheric information to apply signal delay or range error corrections. To aid single-frequency operations, the global positioning system (GPS) broadcasts 8 coefficients as part of the navigation message to drive the ionospheric correction algorithm (ICA) also known as Klobuchar model. We presented here an ionospheric correction algorithm called Neustrelitz TEC model (NTCM) which can be used as complementary to the GPS ICA. Our investigation shows that the NTCM can be driven by Klobuchar model parameters to achieve a significantly better performance than obtained by the mother ICA algorithm. Our research, using post-processed reference total electron content (TEC) data from more than one solar cycle, shows that on average the RMS modeled TEC errors are up to 40% less for the proposed NTCM model compared to the Klobuchar model during high solar activity period, and about 10% less during low solar activity period. Such an approach does not require major technology changes for GPS users rather requires only introducing the NTCM approach a complement to the existing ICA algorithm while maintaining the simplicity of ionospheric range error mitigation with an improved model performance.     

改进的GPS模糊度降相关LLL算法

模糊度降相关技术可以有效提高模糊度求解的效率及成功率,LLL(A.K.Lenstra,H.W.Lenstra,L.Lovasz)算法是新出现的模糊度降相关方法。详细分析LLL算法,针对该算法中存在的缺陷,提出逆整数乔勒斯基、整数高斯算法和升序调整矩阵辅助的改进LLL算法。利用谱条件数及平均相关系数为准则,以300个随机模拟的对称正定矩阵作为模糊度方差-协方差矩阵,对LLL算法和改进的LLL算法进行仿真计算。比较与分析结果表明,改进LLL算法模糊度降相关处理更加彻底,能有效地加速整周模糊度搜索及成功解算。     

A wavelet-extreme learning machine for low-cost INS/GPS navigation system in high-speed applications

The combined navigation system consisting of both global positioning system (GPS) and inertial navigation system (INS) results in reliable, accurate, and continuous navigation capability when compared to either a GPS or an INS stand-alone system. To improve the overall performance of low-cost micro-electro-mechanical systems (MEMS)-based INS/GPS by considering a high level of stochastic noise on low-cost MEMS-based inertial sensors, a highly complex problems with noisy real data, a high-speed vehicle, and GPS signal outage during our experiments, we suggest two approaches at different steps: (1) improving the signal-to-noise ratio of the inertial sensor measurements and attenuating high-frequency noise using the discrete wavelet transform technique before data fusion while preserving important information like the vehicle motion information and (2) enhancing the positioning accuracy and speed by an extreme learning machine (ELM) which has the characteristics of quick learning speed and impressive generalization performance. We present a single-hidden layer feedforward neural network which is employed to optimize the estimation accuracy and speed by minimizing the error, especially in the high-speed vehicle and real-time implementation applications. To validate the performance of our proposed method, the results are compared with an adaptive neuro-fuzzy inference system (ANFIS) and an extended Kalman filter (EKF) method. The achieved accuracies are discussed. The results suggest a promising and superior prospect for ELM in the field of positioning for low-cost MEMS-based inertial sensors in the absence of GPS signal, as it outperforms ANFIS and EKF by approximately 50 and 70%, respectively.     

道路工程GPS平面控制网建网方法

以往GPS建立的平面坐标系属法线系统,而选线设计均在垂线和水准面为基准的坐标系统下进行,其数据未做两化改正而直接用于施工放样。为了消除因GPS引入线路勘测而引发的法线系统坐标系与垂线系统坐标系之间的矛盾,本文采用逆向两化改正的方法,从理论上提出了直接用GPS建立垂线和水准面系统下平面坐标系的技术路线,并推导出逆向两化改正及其精度评定公式。     

Smoothing GPS carrier phase double differences using inertial measurements for high performance applications

This paper will describe an enhancement to the GPS double difference carrier phase measurements on a single airborne platform by smoothing them with inertial measurements while preserving the dynamic bandwidth. This enhancement will reduce the impact of carrier phase multipath and carrier phase noise on baseline determination between multiple antennas on an aircraft when in flight. This type of measurement system has numerous applications where platform pointing and relative body motion must be determined at the mm-level for applications such as sensor stabilization, Synthetic Aperture Radar, long range RADAR (i.e. angle-of-arrival measurements). Lower noise levels (mm-level and below) enable more performance to the stabilized system such as increased aperture for longer range, operation at higher frequencies, and more image resolution. The focus of this paper will be on a technique to provide this enhanced performance for these various applications using the available navigation systems. Additionally, this type of smoothing can effectively remove the additional noise induced by carrier phase measurement differencing. The noise level of a double or triple difference can be reduced below that of the raw measurement. A complimentary synthesized double difference quantity with ultra-low-noise characteristics will be used to smooth the GPS carrier phase double difference measurements without losing dynamic bandwidth since it follows the airborne dynamics. Flight test data will be presented to demonstrate the performance improvement in the midst of aircraft dynamics. Results will show that the noise reduction follows the theoretical prediction.     

改进的GPS模糊度联合降相关算法

针对联合降相关算法中存在的缺陷,提出了改进的联合降相关算法。该算法在降相关每个模糊度之前先查找精度最高的模糊度进行降相关,并将条件方差按照大致降序顺序排列。对联合降相关算法和改进的联合降相关算法进行仿真计算,结果表明,改进的联合降相关算法能降低方差-协方差矩阵的相关性,减少降相关过程所花费的时间,有效地提高条件搜索的速度。