Incorporation of neural network-like processors for GPS navigation

The solution for the receivers position and clock bias using four or more GPS pseudorange measurements involves nonlinear quadratic equations. One of the popular techniques for linearizing the equations and solving them is the least squares (LS) scheme based on an iterative gradient approach. For real-time applications when the solution is to be obtained within a time of the order of 100 ns, a computer often cannot comply with the desired computation time, or high-end computers are too expensive. In this paper various ordinary differential equation formulation schemes, and corresponding circuits of neuron-like analog processors, will be described and several tested in order to ascertain their suitability for GPS navigation processing purposes. The circuits of simple neuron-like analog processors are employed essentially for on-line inversion of matrices, which is usually required for determining LS solutions, as well as dilution of precision (DOP) calculation in standard GPS receivers. Data from single epoch and kinematic positioning experiments will be simulated to validate the effectiveness of the proposed scheme. The properties and performance of the proposed scheme will be assessed and compared to those of the conventional method of matrix inversion.     

BP神经网络在GPS导航中的应用

Kalman滤波常用于GPS动态数据的处理,由于系统存在的不确定性和非先验性,导致滤波产生较大的估计误差,甚至发散。介绍了BP神经网络算法及其非线性逼近能力,并基于BP神经网络的非线性逼近性能设计了BP神经网络进行GPS导航的新算法。实测数据计算结果表明该算法能够真实地反映载体运动轨迹,其导航解具有良好的精度和可靠性。     

Modelling local GPS/levelling geoid undulations using artificial neural networks

The use of GPS for establishing height control in an area where levelling data are available can involve the so-called GPS/levelling technique. Modelling of the GPS/levelling geoid undulations has usually been carried out using polynomial surface fitting, least-squares collocation (LSC) and finite-element methods. Artificial neural networks (ANNs) have recently been used for many investigations, and proven to be effective in solving complex problems represented by noisy and missing data. In this study, a feed-forward ANN structure, learning the characteristics of the training data through the back-propagation algorithm, is employed to model the local GPS/levelling geoid surface. The GPS/levelling geoid undulations for Istanbul, Turkey, were estimated from GPS and precise levelling measurements obtained during a field study in the period 1998–99. The results are compared to those produced by two well-known conventional methods, namely polynomial fitting and LSC, in terms of root mean square error (RMSE) that ranged from 3.97 to 5.73 cm. The results show that ANNs can produce results that are comparable to polynomial fitting and LSC. The main advantage of the ANN-based surfaces seems to be the low deviations from the GPS/levelling data surface, which is particularly important for distorted levelling networks.     

Precision spacecraft navigation using a low-cost GPS receiver

Within the PROBA-2 microsatellite mission, a miniaturized single-frequency GPS receiver based on commercial-off-the-shelf (COTS) technology is employed for onboard navigation and timing. A rapid electronic fuse protects against destructive single-event latch-ups (SEL) and enables a quasi-continuous receiver operation despite the inherent sensitivity to space radiation. While limited to single-frequency C/A-code tracking with a narrow-band frontend, the receiver is able to provide precision navigation services through processing of raw GPS measurements on ground as well as a built-in real-time navigation system. In both cases, ionospheric path delays are eliminated through a combination of L1 pseudorange and carrier phase measurements, which also offers a factor-of-two noise reduction relative to code-only processing. By comparison with satellite laser ranging (SLR) measurements, a 0.3-m (3D rms) accuracy is demonstrated for the PROBA-2 reduced dynamic orbit determinations using post-processed GPS orbit and clock products. Furthermore, the experimental onboard navigation system is shown to provide real-time position information with a 3D rms accuracy of about 1?m, which notably outperforms the specification of the Standard Positioning Service (SPS). In view of their lower hardware complexity, mass budget and power requirements as well as the reduced interference susceptibility, legacy C/A-code receivers can thus provide an attractive alternative to dual-frequency receivers even for demanding navigation applications in low Earth orbit.     

GPS navigation processing using the quaternion-based divided difference filter

Divided difference filter (DDF) with quaternion-based dynamic process modeling is applied to global positioning system (GPS) navigation. Using techniques similar to those of the unscented Kalman filter (UKF), the DDF uses divided difference approximations of derivatives based on Stirling’s interpolation formula which results in a similar mean but different posterior covariance compared to the extended Kalman filter (EKF) solutions. The second-order divided difference is obtained from the mean and covariance in second-order polynomial approximation. The quaternion-based dynamic model is adopted for avoiding the singularity problems encountered in the Euler angle method and enhancing the computational efficiency. The proposed method is applied to GPS navigation to increase the navigation estimation accuracy at high-dynamic regions while preserving (without sacrificing) the precision at low-dynamic regions. For the illustrated example, the second-order DDF can deliver about 41–82% accuracy improvement as compared to the EKF. Some properties and performance are assessed and compared to those of the EKF and UKF approaches.     

Improving performance of GPS satellite DCB estimation for regional GPS networks using long-term stability

Compensation for differential code bias (DCB) is necessary because it is the major source of errors in total electron content (TEC) measurements. The DCB estimation performance is degraded when only the regional GPS network is used. Because DCB estimation is highly correlated with ionospheric modeling, this degradation is particularly evident for measurements concentrated in an area of high TEC concentration. This study proposes a DCB estimation method that uses the long-term stability of the DCB to improve the estimation performance of the regional GPS network. We estimate satellite DCBs by assuming their constancy over seven months. This extended period increases the number of measurements used in DCB estimation and changes the local time distribution of collected measurements. As a result, the unbalanced distribution of specific ionospheric conditions disappears. Tests are performed using both global and regional networks, and the estimation performance is evaluated based on the position error and pseudorange residuals. First, the difference between the global and regional networks when using the conventional method is analyzed. Second, proposed methods are applied to regional networks. The proposed method can improve the DCB estimation performance, and the results are similar to those obtained using one-day global network data.     

超轻型飞机GPS导航与摄影控制

低空超轻型飞机可以实现云下飞行,为大比例尺低空数码航空摄影测量提供了航空平台。本文将基于我国的超轻型飞机平台,设计机载低空数码航摄GPS导航和定点曝光控制系统,详细阐述了导航算法,并对"一机两屏"的方案进行了分析。通过自动定点曝光控制,保证航摄影像的前后、左右重叠度,试验结果显示该系统稳定可靠。     

Adaptive GPS/INS integration for relative navigation

Relative navigation based on GPS receivers and inertial measurement units is required in many applications including formation flying, collision avoidance, cooperative positioning, and accident monitoring. Since sensors are mounted on different vehicles which are moving independently, sensor errors are more variable in relative navigation than in single-vehicle navigation due to different vehicle dynamics and signal environments. In order to improve the robustness against sensor error variability in relative navigation, we present an efficient adaptive GPS/INS integration method. In the proposed method, the covariances of GPS and inertial measurements are estimated separately by the innovations of two fundamentally different filters. One is the position-domain carrier-smoothed-code filter and the other is the velocity-aided Kalman filter. By the proposed two-filter adaptive estimation method, the covariance estimation of the two sensors can be isolated effectively since each filter estimates its own measurement noise. Simulation and experimental results demonstrate that the proposed method improves relative navigation accuracy by appropriate noise covariance estimation.     

卷积神经网络的PM2.5预报模型

针对目前基于机器学习的PM2.5预报模型无法充分利用研究区域内其他相关站点的数据问题,该文提出了一种区域时空点数据的表示方法,并在此基础上提出了基于卷积神经网络的PM2.5预报模型。该模型利用了区域内多站点的历史PM2.5实测数据以及相应的气象预报数据,对区域内任一站点PM2.5浓度进行预报。实验结果显示,该模型在京津冀区域内能对未来至少3d内的PM2.5浓度进行较高精度的预报。与基于单站点的前馈神经网络预报结果对比表明,对区域整体污染及气象状况建模的卷积神经网络模型预报精度更高。该模型对区域内所有站点的预测结果与地面实测值的分布基本一致,表明了该模型具有对区域内PM2.5浓度进行时空预报的能力。     

A new algorithm of energy suppression for satellite navigation

The satellite navigation anti-interference technique, especially space anti-interference technique, is subjected to many restrictions, such as cost, energy depletion, and so on, and the satellite signal strength is limited by the International Radio Advisory Committee, the International Telecommunication Union (ITU) and satellite companies. This paper focuses on satellite navigation systems, especially satellite navigation systems adopting direct sequence spread spectrum (DSSS). The notch filter is used to ...     

基于神经网络的GPS周跳探测的新方法

为了用GPS获得高精度的定位结果,周跳必须在数据处理过程中被检测和修复。通过对周跳产生原因和特点的分析,提出神经网络方法,并与传统方法进行比较。用神经网络建立模型对周跳进行预测。通过对比预测值的不同来确定周跳的大小,从而实现周跳的修复。此外,还利用实测的相位数据,验证方法的可行性与有效性。     

GPS射频干扰浅析

由于GPS接收机的工作有赖于GPS卫星信号,所以易受射频干扰(RFI)的影响。射频干扰可能会引起导航精度的降低或接收机跟踪的丢失。本文论述了信号噪声比和信号噪声密度比的概念,分析了射频干扰对GPS接收的影响,最后说明了直接检测RFI的方法以及RFI源的定位。     

一种车辆GPS/DR/DMAP组合导航系统

车辆导航系统常采用GPS/DR组合导航方式,在实际使用中若采用联邦滤波器,由于设计结构复杂,各种参数选取对滤波器的性能影响较大,选取不当反而引起导航精度的降低。本文设计了一种GPS/DR滤波器,这种滤波器当GPS接收机在失锁时仍能够为用户导航,并且该滤波器结构简单,设计简易。本文采用了DMAP,纠正了车辆相对于道路的偏差。实测导航实验验证了该滤波器能够满足导航精度要求,适用于城市中车辆导航应用。     

GPS inferred geocentric reference frame for satellite positioning and navigation

Accurate geocentric three dimensional positioning is of great importance for various geodetic and oceanographic applications. While relative positioning accuracy of a few centimeters has become a reality using Very Long Baseline Interferometry (VLBI), the uncertainty in the offset of the adopted coordinate system origin from the geocenter is still believed to be of the order of one meter. Satellite Laser Ranging (SLR) is capable of determining this offset to better than10 cm, though, because of the limited number of satellites, this requires a long arc of data. The Global Positioning System (GPS) measurements provide a powerful alternative for an accurate determination of this origin offset in relatively short period of time. Two strategies are discussed, the first utilizes the precise relative positions predetermined byVLBI, where as the second establishes a reference frame by holding only one of the tracking sites longitude fixed. Covariance analysis studies indicate that geocentric positioning to an accuracy of a few centimeters can be achieved with just one day of preciseGPS pseudorange and carrier phase data.     

GPS车载导航定位技术研究

介绍车载导航定位系统的组成,比较几种导航方法的优缺点,得出几种较为合理、精度较高的组合定位方法.GPS卫星信号所包含的定位信息有其特定的格式,通过编写程序将其中所需的定位信息提取出来,并利用七参数转换方法将GPS定位系统应用的WGS-84坐标系转换成国家大地坐标系.通过车载导航试验实例分析表明,利用最短距离投影法得到的电子地图精度较高.     

A data archive of GPS navigation messages

Since 18 June 2007 navigation data messages transmitted by the GPS constellation are recorded by five receivers within GeoForschungsZentrum’s global groundstation network. We describe the recording, processing, validation, analysis and archiving of the navigation data. During the 197 days between 18 June 2007 and 31 December 2007 a total of 125,723,666 subframes were collected. By taking into consideration that the same data set frequently is observed by two or more receivers concurrently, 65,153,955 unique subframes could be extracted from the observations. With an estimated 88,099,200 subframes transmitted by the constellation during this time period a data yield of about 74% was achieved. Simulation studies suggest that with two additional GPS receivers, which are scheduled for addition to the network in 2008, about 95% of the transmitted subframes will be retrieved. The message data archive is open to the scientific community for non-commercial purposes and may be accessed through GFZ’s Information System and Data Center ().

Efficient collection of training data for sub-pixel land cover classification using neural networks

Artificial neural networks (ANNs) are a popular class of techniques for performing soft classifications of satellite images. They have successfully been applied for estimating crop areas through sub-pixel classification of medium to low resolution images. Before a network can be used for classification and estimation, however, it has to be trained. The collection of the reference area fractions needed to train an ANN is often both time-consuming and expensive. This study focuses on strategies for decreasing the efforts needed to collect the necessary reference data, without compromising the accuracy of the resulting area estimates. Two aspects were studied: the spatial sampling scheme (i) and the possibility for reusing trained networks in multiple consecutive seasons (ii). Belgium was chosen as the study area because of the vast amount of reference data available. Time series of monthly NDVI composites for both SPOT-VGT and MODIS were used as the network inputs. The results showed that accurate regional crop area estimation (R² > 80%) is possible using only 1% of the entire area for network training, provided that the training samples used are representative for the land use variability present in the study area. Limiting the training samples to a specific subset of the population, either geographically or thematically, significantly decreased the accuracy of the estimates. The results also indicate that the use of ANNs trained with data from one season to estimate area fractions in another season is not to be recommended. The interannual variability observed in the endmembers’ spectral signatures underlines the importance of using up-to-date training samples. It can thus be concluded that the representativeness of the training samples, both regarding the spatial and the temporal aspects, is an important issue in crop area estimation using ANNs that should not easily be ignored.     

GPS vector configuration design for monitoring deformation networks

 The performance of geodetic monitoring networks is heavily influenced by the configuration of the measured GPS vectors. As an effective design of the GPS measurements will decrease GPS campaign costs and increase the accuracy and reliability of the entire network, the identification of the preferred GPS vectors for measurement has been highlighted as a core problem in the process of deformation monitoring. An algorithm based on a sensitivity analysis of the network, as dependent upon a postulated velocity field, is suggested for the selection of the optimal GPS vectors. Relevant mathematical and statistical concepts are presented as the basis for an improved method of vector configuration design. A sensitivity analysis of the geodetic geodynamic network in the north of Israel is presented, where the method is examined against two deformation models, the Simple Transform Fault and the Locked Fault. The proposed method is suggested as a means for the improvement of the design of monitoring networks, a common practice worldwide. Received: 30 July 2001 / Accepted: 3 June 2002 Acknowledgments. It is my pleasant duty to thank the Survey of Israel and Dr. E. Ostrovsky for providing the variance–covariance matrix of the G1 network in northern Israel. I would like to thank the reviewers of this paper for their constructive and helpful remarks.