北斗标准化发展战略思考

鉴于全球卫星导航系统（GNSS）在军事和民用领域的巨大促进作用,世界主要国家已将卫星导航产业上升为国家战略。标准化作为抢占技术前沿、引领科技创新、开拓国际市场、谋求经济利益的有效手段,在推动卫星导航技术飞速发展和提高国际竞争力等方面的地位和作用日趋突出,促使北斗对其标准化战略的需求日益迫切。本文介绍了国内外标准化战略现状及卫星导航标准化工作情况,深入分析了北斗对标准化发展战略的需求,系统阐述了北斗标准化发展战略的重点方向和主要任务,进而提出相应的战略举措建议,为北斗标准化发展战略的研究提供借鉴。     

The performance comparison between GPs and BeiDou‐2/compass: A perspective from Asia

Abstract

The next decade promises drastic improvements to global navigation satellite systems. The USA is modernizing GPS, Russia is refreshing GLONASS, Europe is moving ahead with its own Galileo system, and The People's Republic of China is expanding its BeiDou‐1 system from a regional navigation system to a full constellation global navigation satellite system known as BeiDou‐2/Compass, which consists of thirty five satellites including geostationary satellites, MEO satellites and geosynchronous satellites in the coming year. Extra satellites will make possible improved performance for all applications, and especially where satellite signals can be obscured, such as in urban canyons, under tree canopies or in open‐pit mines. The benefits of the expected extra satellites and their signals can be evaluated in terms of availability, accuracy, continuity, and reliability issues.

The advent of a hybrid GNSS constellation has drawn a lot of attention to study compatibility and interoperability. A number of performance analyses have been conducted on a global scale with respect to availability, reliability, accuracy and integrity in different simulated scenarios (such as open sky and urban canyons) for each system individually as well as for combined systems with all the possible combinations. Since the BeiDou‐2/Compass has gained more attention from GNSS communities, the main objective of this paper is to study the performance of BeiDou‐2/Compass comparied to GPS in the greater Asia region; and also to explore whether the combination of BeiDou‐2/Compass with GPS would yield performance improvements in this region.

The performance analysis can be analyzed by either the signal or the geometrical conditions. However, the scope of this study is limited to investigating the impact of current and future GNSS based on geometrical conditions. Therefore, the satellite visibility and DOP (Dilution of Precision) values of each system or possible combinations between them are used as the major indices for performance evaluation with the emphasis on the addition of Compass. In addition, those indices are further analyzed in terms of their spatial and temporal distributions with the emphasis on the greater Asia region. Moreover, the spatial performance analyses are conducted on both global and regional scales to provide more insightful comparisons to illustrate the importance of future Compass for users in the greater Asia region.     

Performance modeling in critical engineering systems using RAM analysis

Reliability, availability and maintainability (RAM) analysis of system is helpful in carrying out design modifications, if any, required to achieve minimum failures or to increase mean time between failures (MTBF) and thus to plan maintainability requirements, optimize reliability and maximize equipment availability. To this effect, the paper presents the application of RAM analysis in a process industry. Markovian approach is used to model the system behavior. For carrying out analysis, transition diagrams for various subsystems are drawn and differential equations associated with them are formulated. After obtaining the steady state solution the corresponding values of reliability and maintainability are estimated at different mission times. The computed results are presented to plant personnel for their active consideration. The results proved helpful to them for analyzing the system behavior and thereby to improve the system performance considerably by adopting and practicing suitable maintenance policies/strategies.     

Combined hardware and software aspects of reliability

This paper presents the similarities and differences between hardware, software and system reliability. Relative contributions to system failures are shown for software and hardware and failure and recovery propensities are also discussed. Reliability, availability and maintainability (RAM) concepts have been broadly developed for software reliability than hardware reliability. Extending these software concepts to hardware and system reliability helps in examining the reliability of complex systems. The paper concludes with assurance techniques for defending against faults. Most of the techniques discussed originate in software reliability but apply to all aspects of a system. Also, the effects of redundancy on overall system availability are shown.     

RNSS射频基带一体化芯片测试方法研究

随着卫星导航产业的快速发展,导航芯片成为民用卫星导航应用的核心竞争力。拥有诸多优势的射频基带一体化芯片是导航芯片发展的主流方向之一,本文依托某应用推广项目,对国产的该类芯片进行测试验证,通过不同模态下对其定位精度和跟踪灵敏度的考核,验证了芯片的基本功能,对该类芯片的测试方法进行了初步研究。     

基于卫星导航信号模拟仿真法的北斗接收机导航精度校准测试

随着我国自主设计的北斗卫星导航系统稳步建设,北斗接收机相关技术取得突破,但当前北斗接收机校准体系尚不完善,相关测试方法亟待研究。本文提出卫星导航信号模拟测试法,通过多星座导航信号模拟器设计静态、动态等仿真场景模拟相关载体运动状态下真实的卫星信号,实现对北斗接收机在相关载体运动状态下导航精度的校准测试。该方法具有准确度高、简单易操作和重复性强等优点,可实现实验室条件下检测接收机性能。实验结果表明:北斗系统的定位和测速精度已基本接近GPS系统,但就系统的稳定性,北斗系统与GPS系统相比还存在一定差距。     

Construction of a system for precise determination of the position of users of global navigation satellite systems

An analysis of the components of the errors associated with determination of the positions of users of global satellite navigation systems is presented. Results of precision determination of position with the use of improved ephemeris-time information produced by a differential correction and monitoring system for GLONASS and GPS navigation satellites are presented. Conclusions concerning the outlook for the development of systems of precise point positioning derived from the radio signals of satellite systems are arrived at on the basis of the studies.     

Satellite and satellite subsystems reliability: Statistical data analysis and modeling

Reliability has long been recognized as a critical attribute for space systems. Unfortunately, limited on-orbit failure data and statistical analyses of satellite reliability exist in the literature. To fill this gap, we recently conducted a nonparametric analysis of satellite reliability for 1584 Earth-orbiting satellites launched between January 1990 and October 2008. In this paper, we extend our statistical analysis of satellite reliability and investigate satellite subsystems reliability. Because our dataset is censored, we make extensive use of the Kaplan–Meier estimator for calculating the reliability functions. We derive confidence intervals for the nonparametric reliability results for each subsystem and conduct parametric fits with Weibull distributions using the maximum likelihood estimation (MLE) approach. We finally conduct a comparative analysis of subsystems failure, identifying the “culprit subsystems” that drive satellite unreliability. The results here presented should prove particularly useful to the space industry for example in redesigning subsystem test and screening programs, or providing an empirical basis for redundancy allocation.     

Interferometric GPS ambiguity resolution

The Maximum a Posteriori Ambiguity Search (MAPAS) method for GPS (Global Positioning System) ambiguity resolution first introduced by Macabiau, is generalized to accommodate: (1) satellite switches caused by satellites rising or falling below the horizon or obstructing terrain, and (2) cycle slips due to temporary loss of lock on satellite signals. It is shown that MAPAS and generalized MAPAS are equivalent to Bayesian estimation. The generalized MAPAS method is successfully applied to real GPS satellite data with cycle slips and satellite switches due to satellite obstruction.     

Space-based augmentation for global navigation satellite systems

This paper describes space-based augmentation for global navigation satellite systems (GNSS). Space-based augmentations increase the accuracy and integrity of the GNSS, thereby enhancing users' safety. The corrections for ephemeris, ionospheric delay, and clocks are calculated from reference station measurements of GNSS data in wide-area master stations and broadcast via geostationary earth orbit (GEO) satellites. This paper discusses the clock models, satellite orbit determination, ionospheric delay estimation, multipath mitigation, and GEO uplink subsystem (GUS) as used in the Wide Area Augmentation System developed by the FAA.     

Kernel Entropy Based Extended Kalman Filter for GPS Navigation Processing

This paper investigates the kernel entropy based extended Kalman filter (EKF) as the navigation processor for the Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS). The algorithm is effective for dealing with non-Gaussian errors or heavy-tailed (or impulsive) interference errors, such as the multipath. The kernel minimum error entropy (MEE) and maximum correntropy criterion (MCC) based filtering for satellite navigation system is involved for dealing with non-Gaussian errors or heavy-tailed interference errors or outliers of the GPS. The standard EKF method is derived based on minimization of mean square error (MSE) and is optimal only under Gaussian assumption in case the system models are precisely established. The GPS navigation algorithm based on kernel entropy related principles, including the MEE criterion and the MCC will be performed, which is utilized not only for the time-varying adaptation but the outlier type of interference errors. The kernel entropy based design is a new approach using information from higher-order signal statistics. In information theoretic learning (ITL), the entropy principle based measure uses information from higher-order signal statistics and captures more statistical information as compared to MSE. To improve the performance under non-Gaussian environments, the proposed filter which adopts the MEE/MCC as the optimization criterion instead of using the minimum mean square error (MMSE) is utilized for mitigation of the heavy-tailed type of multipath errors. Performance assessment will be carried out to show the effectiveness of the proposed approach for positioning improvement in GPS navigation processing.     

Support Vector Machine Assisted GPS Navigation in Limited Satellite Visibility

This paper investigates performance improvement via the incorporation of the support vector machine (SVM) into the vector tracking loop (VTL) for the Global Positioning System (GPS) in limited satellite visibility. Unlike the traditional scalar tracking loop (STL), the tracking and navigation modules in the VTL are not independent anymore since the user’s position can be determined by using the information from other satellites and can be predicted on the basis of the states of the user. The method proposed in this paper makes use of the SVM to bridge the GPS signal and prevent the error growth due to signal outage. Similar to the neural network, the SVM is motivated by its ability to approximate an unknown nonlinear input-output mapping through supervised training. The SVM is employed for predicting adequate numerical control oscillator (NCO) inputs, i.e., providing better prediction of residuals for the Doppler frequency and code phase in order to maintain regular operation of the navigation system. When the navigation processing is in good condition, the SVM is at the training stage, and the output information from the discriminator and navigation filter is adopted as the inputs. Other machine learning (ML) algorithms such as the radial basis function neural network (RBFNN) and the Adaptive Network-Based Fuzzy Inference System (ANFIS) are employed for comparison. Performance evaluation for the SVM assisted architecture as compared to the RBFNN- and ANFIS-assisted methods and the un-assisted VTL will be carried out and the performance evaluation during GPS signal outage will be presented. The proposed design is very useful for navigation during the environment of limited satellite visibility to effectively overcome the problem in the environment of GPS outage.     

Production reliability in flexible manufacturing systems

A typical flexible manufacturing system, Westland Helicopters' sheet metal detail manufacturing complex, has been analysed for reliability. The techniques of fault tree analysis and event tree analysis are presented and their applicability to this study investigated. Event tree analysis has been found to be a more effective method for analysing manufacturing systems. The failure states of the system have been identified from the construction of an event tree which considers random hardware faults that influence production. Failure rate data have been used to quantify the critical production failure states in terms of machine failures. Estimates are made of the system's MTTF and percentage availability using typical MTTR figures. The probability that a selected production route fails to complete the manufacture of a set of parts is also evaluated. A dependency of systems reliability on the production demand has been discovered, and a possible method for modelling and assessing the reliability of systems capable of producing several products is proposed.     

Reliability Target Assessment Based on Integrated Factors Method (IFM): A Real Case Study of a Sintering Plant

The success of a company depends on customer’s satisfaction: quality, price, and service. These three goals depend in particular on R.A.M.S. characteristics: reliability, availability, maintainability, and safety. In the last few years, in order to guarantee high standards of reliability and maintainability, new methodologies and techniques have been developed to estimate the R.A.M.S. targets. In particular, the reliability target represents both the starting and the ending point of R.A.M.S. analysis. The design of the reliability target of a system is a crucial aspect of reliability analysis, as it affects the performance of the system and components. This paper aims to develop a new approach called “IFM Target,” to define the reliability target for complex systems through the integrated factors method, to combine the advantages of usually used approaches, and to overcome some criticalities highlighted in a careful literature analysis. The proposed method has been applied on a sintering system. The results show the effectiveness of the proposed approach.     

Precise Orbit Determination for the FY-3C Satellite Using Onboard BDS and GPS Observations from 2013, 2015, and 2017

Using the FengYun-3C (FY-3C) onboard BeiDou Navigation Satellite System (BDS) and Global Positioning System (GPS) data from 2013 to 2017, this study investigates the performance and contribution of BDS to precise orbit determination (POD) for a low-Earth orbit (LEO). The overlap comparison result indicates that code bias correction of BDS can improve the POD accuracy by 12.4%. The multi-year averaged one-dimensional (1D) root mean square (RMS) of the overlapping orbit differences (OODs) for the GPS-only solution is 2.0, 1.7, and 1.5 cm, respectively, during the 2013, 2015, and 2017 periods. The 1D RMS for the BDS-only solution is 150.9, 115.0, and 47.4 cm, respectively, during the 2013, 2015, and 2017 periods, which is much worse than the GPS-only solution due to the regional system of BDS and the few BDS channels of the FY-3C receiver. For the BDS and GPS combined solution (also known as the GC combined solution), the averaged 1D RMS is 2.5, 2.3, and 1.6 cm, respectively, in 2013, 2015, and 2017, while the GC combined POD presents a significant accuracy improvement after the exclusion of geostationary Earth orbit (GEO) satellites. The main reason for the improvement seen after this exclusion is the unfavorable satellite tracking geometry and poor orbit accuracy of GEO satellites. The accuracy of BDS-only and GC combined solutions have gradually improved from 2013 to 2017, thanks to improvements in the accuracy of International GNSS Service (IGS) orbit and clock products in recent years, especially the availability of a high-frequency satellite clock product (30 s sampling interval) since 2015. Moreover, the GC POD (without GEO) was able to achieve slightly better accuracy than the GPS-only POD in 2017, indicating that the fusion of BDS and GPS observations can improve the accuracy of LEO POD. GC combined POD can significantly improve the reliability of LEO POD, simply due to system redundancy. An increased contribution of BDS to LEO POD can be expected with the launch of more BDS satellites and with further improvements in the accuracy of BDS satellite products in the near future.     

Availability of Maintained Systems: A State-of-the-Art Survey

Availability appears to be a more appropriate measure than reliability for measuring the effectiveness of maintained systems because it includes reliability as well as maintainability. This paper is a survey and a systematic classification of the literature relevant to availability. Emphasis in this paper is centered on the current state of the art on a variety of topics related to availability. Among the topics discussed are: the definition and concepts of the availability; the probability density functions (pdf) of failure times, the pdf of repair times, system configurations, and the various approaches employed to obtain the availability models; confidence intervals of availability; effect of preventive maintenance policies on availability; availability parameters in the model; and systems optimization.     

Optimal reliability and maintainability allocation in manufacturing systems

In this article an attempt has been made to solve an important task in the reliability management of manufacturing systems: the definition of reliability and maintainability specifications of parts, the general objective being to increase productivity while maintaining costs low. An analytical approach has been considered to evaluate an average index of production capability in series-parallel systems. A heuristic optimization procedure has been developed to solve the following problems: (a) determine the optimal reliability and maintainability allocation of parts to achieve the maximum production index at a given cost; and (b) determine the optimal reliability and maintainability allocation of parts which minimizes the total cost of investments, subject to the constraint of meeting a system production requirement. Numerical examples prove the effectiveness of the proposed procedure and show that the application of optimization analyses can provide large gains in terms of either productivity or total cost.     

Analytic Critical Flow Method (ACFM): A Reliability Allocation Method Based on Analytic Hierarchy Process

RAMS is an acronym for reliability, availability, maintainability and safety. These four properties concern the application of important methodologies to design and manage complex systems. In the present research, starting from the analysis of several literature reliability allocation techniques, a reliability allocation method has been implemented called analytic critical flow method (ACFM). Critical flow method is a reliability allocation method for series-parallel configurations, based on failure analysis of each unit of the system. The new approach is based on critical flow method, whose results are matched with the analytic hierarchy process multicriteria method. The result is a dynamic model that combines the advantages of the allocation method and the multicriteria approach. The need to develop the ACFM is the outcome of a careful analysis of the current military and commercial approaches. In particular, no literature method takes into account to assign a different level of significance (weight) to the different units of the system, simultaneously to the considered factors. The proposed approach has been applied and compared with other traditional methods on an aerospace prototype (series-parallel configuration), where the reliability allocation process is rigorous. The results demonstrate the effectiveness of the new approach and its ability to overcome the criticalities highlighted in literature.     

NAROAS: a neural network-based advanced operator support system for the assessment of systems reliability

We have developed and implemented a computerized reliability monitoring system for nuclear power plant applications, based on a neural network. The developed computer program is a new tool related to operator decision support systems, in case of component failures, for the determination of test and maintenance policies during normal operation or to follow an incident sequence in a nuclear power plant. The NAROAS (Neural Network Advanced Reliability Advisory System) computer system has been developed as a modularized integrated system in a C++ Builder environment, using a Hopfield neural network instead of fault trees, to follow and control the different system configurations, for interventions as quickly as possible at the plant. The observed results are comparable and similar to those of other computer system results. As shown, the application of this neural network contributes to the state of the art of risk monitoring systems by turning it easier to perform online reliability calculations in the context of probabilistic safety assessments of nuclear power plants.