动态定位解算中测量粗差的探测与修复

基于Kalman滤波的动态定位中,动态观测量可能存在粗差,若数据处理不考虑对这些粗差的特别处理,则所提供的动态信息将极不可靠。文中计算了粗差对滤波结果的影响,并由此建立了动态定位中粗差的探测和修复算法。最后以一数字仿真(模拟)实验论证了方法的可行性。     

基于小波变换的SA误差建模与预报

运用小波分析方法对GPS单点动态定位误差进行分解,提出了基于小波变换的信号去噪与粗差的定位和剔除方法。将时间序列分析方法用于SA误差建模,提出了基于小波变换的SA误差建模及预报方法,并通过实例验证了方法的正确性     

Code and carrier phase based short baseline GPS positioning: computational aspects

A recursive least squares algorithm is presented for short baseline GPS positioning using both carrier phase and code measurements. We take advantage of the structure of the problem to make the algorithm computationally efficient and use orthogonal transformations to ensure that the algorithm is numerically reliable. Details are given for computing position estimates and error covariance matrices with possible satellite rising and setting. Real data test results suggest our algorithm is effective.This research was supported by NSERC of Canada Grant RGPIN217191–99, FCAR of Quebec Grant 2001-NC-66487, and NSERCGEOIDE Network Project ENV#14 for Xiao-Wen Chang, and by NSERC of Canada Grant RGPIN9236–01 for Christopher C. Paige.An erratum to this article can be found at     

Carrier phase-based integrity monitoring for high-accuracy positioning

Pseudorange-based integrity monitoring, for example receiver autonomous integrity monitoring (RAIM), has been investigated for many years and is used in various applications such as non-precision approach phase of flight. However, for high-accuracy applications, carrier phase-based RAIM (CRAIM), an extension of pseudorange-based RAIM (PRAIM) must be used. Existing CRAIM algorithms are a direct extension of PRAIM in which the carrier phase ambiguities are estimated together with the estimation of the position solution. The main issues with the existing algorithms are reliability and robustness, which are dominated by the correctness of the ambiguity resolution, ambiguity validation and error sources such as multipath, cycle slips and noise correlation. This paper proposes a new carrier phase-based integrity monitoring algorithm for high-accuracy positioning, using a Kalman filter. The ambiguities are estimated together with other states in the Kalman filter. The double differenced pseudorange, widelane and carrier phase observations are used as measurements in the Kalman filter. This configuration makes the positioning solution both robust and reliable. The integrity monitoring is based on a number of test statistics and error propagation for the determination of the protection levels. The measurement noise and covariance matrices in the Kalman filter are used to account for the correlation due to differencing of measurements and in the construction of the test statistics. The coefficient used to project the test statistic to the position domain is derived and the synthesis of correlated noise errors is used to determine the protection level. Results from four cases based on limited real data injected with simulated cycle slips show that residual cycle slips have a negative impact on positioning accuracy and that the integrity monitoring algorithm proposed can be effective in detecting and isolating such occurrences if their effects violate the integrity requirements. The CRAIM algorithm proposed is suitable for use within Kalman filter-based integrated navigation systems.

Code and carrier phase based short baseline GPS positioning: computational aspects

A recursive least squares algorithm is presented for short baseline GPS positioning using both carrier phase and code measurements. We take advantage of the structure of the problem to make the algorithm computationally efficient and use orthogonal transformations to ensure that the algorithm is numerically reliable. Details are given for computing position estimates and error covariance matrices with possible satellite rising and setting. Real data test results suggest our algorithm is effective.This research was supported by NSERC of Canada Grant RGPIN217191–99, FCAR of Quebec Grant 2001-NC-66487, and NSERCGEOIDE Network Project ENV#14 for Xiao-Wen Chang, and by NSERC of Canada Grant RGPIN9236–01 for Christopher C. Paige.The online version of the original article can be found at     

不规则DEM数据的粗差探测算法的应用

粗差作为影响精度的重要因素,其存在会造成DEM空间上的严重扭曲,有时能导致DEM及其产品严重失真,甚至完全不能使用。本文在对现有的粗差探测算法分析的基础上,提出了一种新型的适用于离散形式DEM粗差探测算法,并采用实测的ZX铁路线DEM数据对该算法进行检验,试验结果证实,新算法对不规则DEM粗差的探测有效实用。     

Temporal impact of selected GPS errors on point positioning

This paper is aimed at investigating the stability of point positions over time in support of applications that require high position stability when differential GPS is not feasible. One such application is the use of a P3-Orion aircraft offshore for magnetic measurement in support of submarine detection. Temporal changes in several GPS errors lead to variability in the computed positions, so it is not the absolute errors, but rather their temporal variations that are of importance. Furthermore, the temporal variability of the different error sources may dictate a certain algorithm approach and processing strategy. This paper analyzes the temporal variations of the broadcast satellite clock model and orbit parameters, as well as ionospheric errors, because these will typically be the dominant errors for real-time point positioning. These three errors are analyzed independently. A tropospheric correction is applied when computing all of the position results, so the tropospheric error itself is not investigated. Satellite clock and orbit errors are analyzed by comparing broadcast and precise post-mission SV clock corrections and orbits. For the ionosphere, the effect is separated using dual-frequency data. The analysis comprises primarily of assessing error behaviors and magnitudes through time and frequency analyses. In this way, the differences in variability of the errors are easily determined. The effect of each error in the position domain is also investigated in addition to the combined effect. Results show that, on a typical day when single frequency data are processed with broadcast orbit and clock data, the root mean square (RMS) of the changes in the position errors over a 50-s interval is about 5.8 cm in northing, 4.0 in easting, and 11.0 cm in height. When using precise orbits and clocks, in addition to dual frequency data, these values improve by 46–56% to 2.7 cm in northing, 2.2 cm in easting, and 4.9 cm in height. Under severe ionospheric activity, the RMS of the errors decrease from 8.1 to 3.3 cm in northing, 5.7 to 2.6 cm in easting, and 17.0 to 4.9 cm in height, which are improvements of 54–71%. Electronic Publication     

三种国际主流的北极卫星遥感冰速产品评估和分析

冰速是海冰的重要参数,但是受资料长度限制,对卫星遥感冰速产品进行系统比较和评估的研究还较少。利用2009年—2017年国际北极浮标计划（IABP）浮标冰速数据,较系统地评估了不同时间间隔的遥感反演冰速产品在北冰洋内区和弗拉姆海峡附近海区的表现。结果显示,对北冰洋内区而言,1 d间隔的美国国家雪冰数据中心（NSIDC）遥感冰速冬季误差整体大于夏季,冬季高估了波弗特海南部海冰向西的运动,低估了从喀拉海流向格陵兰岛北部的穿极流。对于5种2 d间隔冰速产品而言,产品精度不完全取决于源数据空间分辨率的高低,反演算法的改进和数据融合均能提高冰速的精度,均方根误差大小的顺序是OSISAF-Merged <OSISAF-AMSR <Ifremer-AMSR <OSISAF-SSM < OSISAF-ASCAT。对于4种使用相同反演算法的3 d间隔的冰速产品,产品的均方根误差取决于源数据分辨率,空间分辨率最高的Ifremer-AMSR冰速均方根误差最小。比较不同种类、不同时间间隔冰速的月平均均方根误差后可知,采用3 d间隔反演的冰速由于能够忽略更多短时间尺度海冰运动,其冰速均方根误差低于2 d间隔的冰速。在弗拉姆海峡,除Ifremer-AMSR外,其余冰速产品均具有较大的经向偏差和均方根误差。在冰速较快弗拉姆海峡,冰速产品均方根误差取决于源数据的分辨率。     

空间前方交会中的系统误差处理

空间前方交会测量中,基线长及基线方向值的误差对所有观测点的坐标影响是系统性的。本文提出一种方法,利用空间交会测量中的多余观测,可以精确计算出这些系统误差,同时在交会点的坐标中也消去了基线误差的影响。     

基于不同大小窗口的移动曲面拟合法探测不规则DEM粗差的一种方法

粗差的存在会造成数字高程模型(DEM)空间上的严重扭曲,有时能导致DEM及其产品严重失真,甚至完全不能使用.因而有关DEM的粗差诊断问题已愈来愈引起人们的关注.本文在对现有的基于点方式的DEM粗差探测算法进行分析的基础上,提出一种基于不同大小窗口的移动曲面拟合法探测DEM粗差的一种方法(简称YXY算法),并通过蒙特卡洛仿真试验来验证该算法的有效性和可行性.     

近地表大气逆温条件下的地表温度遥感反演与验证

为了减少近地表大气逆温对地表温度遥感反演精度的影响,提出在晴空的地表温度"通用劈窗算法"模型中增加一个温度改正项来实现。在建立该误差改正项时,利用正常条件下的通用劈窗算法系数和具有不同逆温强度的逆温廓线,并结合大气辐射传输模型MODTRAN计算,得到近地表大气逆温条件下的地表温度反演误差,并在分析了该误差值与相应的逆温强度的关系后,发现该温度改正项可以表示为近地表大气逆温强度的二次项函数。为了进一步提高地表温度的反演精度,将地表温度和大气水汽含量进行分组,分别针对每个分组来确定温度改正项方程的系数。模拟结果表明,在逆温强度为1.7 K/100m时,该温度改正项可以使地表温度的反演精度提高0.44 K。利用内蒙古海拉尔试验站的实测数据对地表温度反演结果进行了验证,在近地表大气存在逆温的条件下,该方法能提高地表温度的遥感反演精度0.47K。但是,由于本文提出的方法需要已知大气温度廓线来计算大气逆温强度,因此在实际应用中该方法受到了一定的限制。     

Accurate absolute GPS positioning through satellite clock error estimation

 An algorithm for very accurate absolute positioning through Global Positioning System (GPS) satellite clock estimation has been developed. Using International GPS Service (IGS) precise orbits and measurements, GPS clock errors were estimated at 30-s intervals. Compared to values determined by the Jet Propulsion Laboratory, the agreement was at the level of about 0.1 ns (3 cm). The clock error estimates were then applied to an absolute positioning algorithm in both static and kinematic modes. For the static case, an IGS station was selected and the coordinates were estimated every 30 s. The estimated absolute position coordinates and the known values had a mean difference of up to 18 cm with standard deviation less than 2 cm. For the kinematic case, data obtained every second from a GPS buoy were tested and the result from the absolute positioning was compared to a differential GPS (DGPS) solution. The mean differences between the coordinates estimated by the two methods are less than 40 cm and the standard deviations are less than 25 cm. It was verified that this poorer standard deviation on 1-s position results is due to the clock error interpolation from 30-s estimates with Selective Availability (SA). After SA was turned off, higher-rate clock error estimates (such as 1 s) could be obtained by a simple interpolation with negligible corruption. Therefore, the proposed absolute positioning technique can be used to within a few centimeters' precision at any rate by estimating 30-s satellite clock errors and interpolating them. Received: 16 May 2000 / Accepted: 23 October 2000     

Error analyses of CHAMP data for recovery of the Earth’s gravity field

A preliminary commission error analysis whereby orbit perturbation theory and other techniques are used to assess and predict the recovery of the Earths gravity field from the challenging microsatellite payload (CHAMP) mission is developed and implemented. With CHAMP launched in July 2000, accumulated evidence is now available to quantify the errors in the recovery procedure including the orbital precision from GPS, attitude errors, accelerometer noise and thruster mismatch/misalignment. For the latter, numerical integrations using a variable length single-step Runge–Kutta integrator and a fixed length multi-step method are compared to assess the error associated with assuming that the thruster misalignment can be spread uniformly across a step interval. Error degree variances from simulated studies are compared to results from a recently released CHAMP-based gravity field, EIGEN-1S. It is seen that the orbital positioning, as derived from the onboard GPS receiver, is critical, with accelerometer noise contributing at a lower level. Attitude error, at currently quoted accuracy, is not significant as an error source. AcknowledgementsThe authors would like to thank the UK Natural Environment Research Council (Grant No. NER/A/0000/00612) for financing this study and GFZ for supplying the data and technical support.     

New jump trajectory determination method using low-cost MEMS sensor fusion and augmented observations for GPS/INS integration

Objective information on athletic maneuvers for performance evaluation has become highly desired in sports such as skiing, snowboarding, and mountain biking. Body-mounted devices, incorporating low-cost microelectromechanical, inertial navigation units, and global positioning system (GPS) receivers, to calculate sport-specific key performance variables (KPVs) and provide real-time feedback, are now commercially available. However, algorithms implemented for such purposes still lack accuracy and power efficiency. A new GPS/INS (inertial navigation system) integration algorithm is proposed to determine the trajectory of an athlete executing jumps while skiing, snowboarding, mountain biking etc. KPVs, such as jump horizontal distance, vertical height, and drop, are calculated from the trajectory. A new sensor error compensation scheme is developed using sensor fusion and linear Kalman filters (LKF). The LKF parameters are varied to address the fluctuating dynamics of the athlete during a jump. The extended Kalman filter used for GPS/INS integration has an observation vector augmented with sensor error measurements derived from sensor fusion. The performance of the proposed algorithm is evaluated through experimental field tests. For the determination of jump horizontal distance, height, and drop, the proposed algorithm has errors of 14.3 cm (5.5 %), 1.6 cm (38 %), and 6.7 cm (9.4 %), respectively. Errors in KPVs for a set of jumps were first determined with respect to the true KPVs, and then the errors for all the jumps were averaged to calculate the absolute and percentage errors. The accuracy achieved is deemed to fulfill the expectations of both recreational and professional athletes.     

A topology-preserving polygon rasterization algorithm

Conventional algorithms for polygon rasterization are typically designed to maintain non-topological characteristics. Consequently, topological relationships, such as the adjacency between polygons, may also be lost or altered, creating topological errors. This paper proposes a topology-preserving polygon rasterization algorithm to avoid topological errors. Four types of topological error may occur during polygon rasterization. The algorithm starts from an initial polygon rasterization and uses a set of preserving strategies to increase topological accuracy. The count of the four types of error measures the topological errors of the conversion. Topological accuracy is summarized as 1 minus the ratio of actual topological errors to the total number of possible error cases. When applied to a land-use dataset with a data volume of 128 MB, 127,836 polygons, and extending 1352 km², the algorithm achieves a topological accuracy of more than 99% when raster cell size is 30 m or smaller (100% for 5 and 10 m). The effects of cell size, polygon shape, and number of iterations on topological accuracy are also examined.     

面向交叉路口特征点的矢量数据化简算法

针对现有的算法不能够很好地保留道路交叉路口特征点的问题,该文提出了一种基于道路交叉路口特征点的矢量数据化简算法。把曲线上的特征点分为交叉路口特征点和重要的特征点两类,对两类点分别进行处理得到分段点;利用相邻的分段点作为道格拉斯-普克算法的首尾点,对每段子曲线以基于最小二乘法拟合曲线选定最优距离阈值,进行逐段化简。实验结果表明,该算法能够有效地化简道路矢量数据并保留交叉路口和重要的特征点。     

嫦娥三号导航相机测图能力分析及地形重建

基于立体相机成像模型并结合相机参数对嫦娥三号导航相机3维测图能力进行分析,利用摄影测量原理和误差传播定律对巡视器30 m范围内的DEM精度进行了理论分析,推导出导航相机立体影像获得的采样点精度公式,并绘制了DEM的平面精度图和高程精度图;同时使用多线程技术开发了基于导航相机立体影像的地形快速重建算法,利用多线程技术完成影像的特征匹配和密集匹配,并通过分块内插生成DEM。该技术应用于嫦娥三号任务中,有力地支持了嫦娥三号遥操作路径规划相关任务。     

Effect of post-seismic deformation on earth orientation parameter estimates from VLBI observations: a case study at Gilcreek, Alaska

Earth orientation parameters (EOPs) provide a link between the International Celestial Reference Frame (ICRF) and the International Terrestrial Reference Frame (ITRF). Natural geodynamic processes, such as earthquakes, can cause the motion of stations to become discontinuous and/or non-linear, thereby corrupting the EOP estimates if the sites are assumed to move linearly. The VLBI antenna at the Gilcreek Geophysical Observatory has undergone non-linear, post-seismic motion as a result of the M_w=7.9 Denali earthquake in November 2002, yet some VLBI analysts have adopted co-seismic offsets and a linear velocity model to represent the motion of the site after the earthquake. Ignoring the effects of the Denali earthquake leads to error on the order of 300–600 μas for the EOP, while modelling the post-seismic motion of Gilcreek with a linear velocity generates errors of 20–50 μas. Only by modelling the site motion with a non-linear function is the same level of accuracy of EOP estimates maintained. The effect of post-seismic motion on EOP estimates derived from the International VLBI Service IVS-R1 and IVS-R4 networks are not the same, although changes in network geometries and equipment improvements have probably affected the estimates more significantly than the earthquake-induced deformation at Gilcreek.     

长距离GPS/BDS双系统网络RTK方法

基于区域参考站网的网络实时动态定位(real-time kinematic,RTK)方法是实现全球定位系统(global positioning system,GPS)、北斗卫星导航系统(BeiDou satellite navigation system,BDS)高精度定位的主要手段.研究了一种长距离GPS/BDS双...     

复杂环境磁转向检测HDE辅助的RTK+IEZ行人定位方法

针对复杂环境下传统INS-EKF-ZUPT (IEZ)方法中存在位置及航向误差累积导致定位精度差的问题,本文提出一种能与RTK一同融入IEZ中的磁转向启发式航向约束(MTHDE)算法,并结合该算法设计了一种适用于四正交主方向场景的RTK+IEZ+MTHDE行人定位方法。在具有开阔地带、林荫道、林荫道及建筑半遮挡、室内等场景的约800 m矩形试验轨迹中,对该方法进行了验证。结果表明,RTK及MTHDE算法对IEZ的位置及航向进行了有效的修正,在12个参考点的试验轨迹中,该方法的平均平面定位误差为1.35 m,优于传统RTK+IEZ方法。