Performance Analysis of GNSS/MIMU Tight Fusion Positioning Model with Complex Scene Feature Constraints

In order to meet the requirements of high-precision vehicle positioning in complex scenes,an observation noise adaptive robust GNSS/MIMU tight fusion model based on the gain matrix is proposed considering static zero speed,non-integrity,attitude,and odometer constraint models.In this model,the robust equivalent gain matrix is constructed by the IGG-Ⅲmethod to weaken the influence of gross error,and the on-line adaptive update of observation noise matrix is carried out according to the change of actual observation environment,so as to improve the solution performance of filtering system and realize high-precision position,attitude and velocity measurement when GNSS signal is unlocked.A real test on a road over 600 km demonstrates that,in about 100 km shaded environment,the fixed rate of GNSS ambiguity resolution in the shaded road is 10%higher than that of GNSS only ambiguity resolution.For all the test,the positioning accuracy can reach the centimeter level in an open environment,better than 0.6 m in the tree shaded environment,better than 1.5 m in the three-dimensional traffic environment,and can still maintain a positioning accuracy of 0.1 m within 10 s when the satellite is unlocked in the tunnel scene.The proposal and verification of the algorithm model show that low-cost MIMU equipment can still achieve high-precision positioning when there are scene feature constraints,which can meet the problem of high-precision vehicle navigation and location in the urban complex environment.

Communication-based positioning systems:past,present and prospects

This paper reviews positioning systems in the context of communication systems. First, the basic positioning technique is described for location based ser- vice （LBS） in mobile communication systems. Then the high integrity global posi- tioning system （iGPS） is introduced in terms of aspects of what it is and how the low Earth orbit （LEO） Iridium telecommunication satellites enhance the global posi- tioning system （GPS）. Emphasis is on the Chinese Area Positioning System （CAPS） which is mainly based on commercial geostationary （GEO） communication satellites, including decommissioned GEO and inclined geosynchronous communication satel- lites. Characterized by its low cost, high flexibility, wide-area coverage and ample frequency resources, a distinctive feature of CAPS is that its navigation messages are generated on the ground, then uploaded to and forwarded by the communication satellites. Fundamental principles and key technologies applied in the construction of CAPS are presented in detail from the CAPS validation phase to its experimental system setup. A prospective view of CAPS has concluded it to be a seamless, high ac- curacy, large capacity navigation and communication system which can be achieved by expanding it world wide and enhancing it with LEO satellites and mobile base stations. Hence, this system is a potential candidate for the next generation of radio navigation after GPS.

Reference satellite selection method for GNSS high-precision relative positioning

Selecting the optimal reference satellite is an important component of high-precision relat/ve positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision （PDOP） value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.

Random Weighting Estimation Method for Dynamic Navigation Positioning

This paper presents a new random weighting estimation method for dynamic navigation positioning. This method adopts the concept of random weighting estimation to estimate the covariance matrices of system state noises and observation noises for controlling the disturbances of singular observations and the kinematic model errors. It satisfies the practical requirements of the residual vector and innovation vector to sufficiently utilize observation information, thus weakening the disturbing effect of the kinematic model error and observation model error on the state parameter estimation. Theories and algorithms of random weighting estimation are established for estimating the covariance matrices of observation residual vectors and innovation vec- tors. This random weighting estimation method provides an effective solution for improving the positioning accuracy in dynamic navigation. Experimental results show that compared with the Kalman filtering, the extended Kalman filtering and the adaptive windowing filtering, the proposed method can adaptively determine the covariance matrices of observation error and state error, effectively resist the disturbances caused by system error and observation error, and significantly improve the positioning accu- racy for dynamic navigation.

GRACE time-varying gravity field solutions based on PANDA software

The conventional dynamic approach for gravity filed modelling has been implemented in the PANDA(Position and Navigation Data Analyst) software. A variant of the so-called ’two-step’ method for gravity field modelling is adopted for this purpose, where the GRACE(Gravity Recovery and Climate Experiment)orbits are derived from the GPS(Global Positioning System) data in a first step followed by a simultaneous determination of dynamic orbit and gravity filed from the GPS-derived orbits and K-band rangerate measurements in a second step. In this way, the monthly gravity field solutions complete to degree and order 96 are produced for the period Jan. 2005 to Dec. 2010. Their performance is assessed by comparing them with the official solutions, i.e., CSR RL05, GFZ RL05 a and JPL RL05. A comparison in the spectral domain in terms of geoid heights reveals that the obtained solutions present the smallest degree amplitudes at degree 30-75. A further analysis of mass changes in the spatial domain demonstrates that the main signals observed from the obtained solutions are in great agreement with those from the official solutions. Remarkably, the correlation coefficients of mass changes in large river basins from the official solutions with respect to those from the obtained solutions are all above 0.97. These results demonstrate that the obtained solutions are comparable to the official solutions.

Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration

Traditional cubature Kalman filter(CKF)is a preferable tool for the inertial navigation system(INS)/global positioning system(GPS)integration under Gaussian noises.The CKF,however,may provide a significantly biased estimate when the INS/GPS system suffers from complex non-Gaussian disturbances.To address this issue,a robust nonlinear Kalman filter referred to as cubature Kalman filter under minimum error entropy with fiducial points(MEEF-CKF)is proposed.The MEEF-CKF behaves a strong robustness against complex nonGaussian noises by operating several major steps,i.e.,regression model construction,robust state estimation and free parameters optimization.More concretely,a regression model is constructed with the consideration of residual error caused by linearizing a nonlinear function at the first step.The MEEF-CKF is then developed by solving an optimization problem based on minimum error entropy with fiducial points(MEEF)under the framework of the regression model.In the MEEF-CKF,a novel optimization approach is provided for the purpose of determining free parameters adaptively.In addition,the computational complexity and convergence analyses of the MEEF-CKF are conducted for demonstrating the calculational burden and convergence characteristic.The enhanced robustness of the MEEF-CKF is demonstrated by Monte Carlo simulations on the application of a target tracking with INS/GPS integration under complex nonGaussian noises.

A New Independent GPS-Free System for Geo-Referencing from Space

A new system’s geo-referencing from space is entirely free from any GNSS (GPS or equivalent) systems. The system addresses to various strategic and economic applications such as in remote clock synchronism, aircraft and balloon navigation, missile and smart bombs tracking, satellite orbital determination and remote target geo-positioning. The new geometry concept corresponds to an “inverted GPS” configuration, utilizing four ground-based reference stations, synchronized in time, installed at well known geodesic coordinates and a repeater in space, carried by an aircraft, balloon, satellite, etc. Signal transmitted by one of the reference bases is retransmitted by the transponder, received back by the four bases, producing four ranging measurements which are corrected for the time delays undergone in every retransmission. A minimization function was derived to compare the repeater’s positions referred to at least two groups of three reference bases, to correct for the signal transit time at the repeater and propagation delays, and consequently to provide the accurate repeater position for each time interaction. Once the repeater’s coordinates are known, the other determinations and applications become straightforward. The system solving algorithm and process performance has been demonstrated by simulations adopting a practical example with the transponder carried by an aircraft moving over bases and a target on the ground. Effects produced by reference clock synchronism uncertainties at the four bases on the measurements are reviewed.

综合时空体系网络管理系统内涵及框架分析

针对综合时空体系成为中国面向2035年在定位、导航、授时领域奋斗目标的要求,分析了国际上相对应的定位导航授时(positioning navigation timing,PNT)体系以及已取得部分成果,认为要实现高质量服务的系统,除了已强调的信号融合和终端集成等工作之外,还需要加强从信号源到终端用户网络的管理,建设网络管理系统。提出了综合时空体系网络管理系统是实现可信可靠安全服务的核心内容,建立了由7个单元组成的网管框架,论述了各单元任务功能。通过网络管理系统,将建立信号-网管-终端的完整链条,奠定综合时空体系核心技术基础,推动定位、导航、授时服务的泛在智能规模化发展。

Space time clock:An on-chip clock with 10^(-12) instability

High precision and stable clock is extremely important in communication and navigation.The miniaturization of the clocks is considered to be the trend to satisfy the demand for5G and the next generation communications.Based on the concept of meter bar and the principle of the constancy of light velocity,we designed a micro clock,Space Time Clock(STC),with the size smaller than 1 mm×1 mm and the power dissipation less than 2 m W.Designed in integrated circuit of 0.18μm technology,the instability of STC is assessed to be 2.23×10^(-12)and the trend of the instability is reversely proportional toτ.With the potential ability to reach the level of 10instability on chip in the future,the period of the STC’s signal is locked on the delay time defined by the meter bar which keeps the time reference constant.Because of its superior performance,the STC is more suitable for mobile communication,PNT(Positioning,Navigation and Timing),embedded processor and deep space application,and becomes the main payload of the ASRTU satellite scheduled to launch next year and investigate in space environment.

A New Approach to Estimate True Position of Unmanned Aerial Vehicles in an INS/GPS Integration System in GPS Spoofing Attack Conditions

This paper presents a new approach to estimate the true position of an unmanned aerial vehicle （UAV） in the conditions of spoofing attacks on global positioning system （GPS） receivers. This approach consists of two phases, the spoofing detection phase which is accomplished by hypothesis test and the trajectory estimation phase which is carried out by applying the adapted particle filters to the integrated inertial navigation system （INS） and GPS. Due to nonlinearity and unfavorable impacts of spoofing signals on GPS receivers, deviation in position calculation is modeled as a cumulative uniform error. This paper also presents a procedure of applying adapted particle swarm optimization filter （PSOF） to the INS/GPS integration system as an estimator to compensate spoofing attacks. Due to memory based nature of PSOF and benefits of each particle＇s experiences, application of PSOF algorithm in the INS/GPS integ- ration system leads to more precise positioning compared with general particle filter （PF） and adaptive unscented particle filer （AUPF） in the GPS spoofing attack scenarios. Simulation results show that the adapted PSOF algorithm is more reliable and accurate in estim- ating the true position of UAV in the condition of spoofing attacks. The validation of the proposed method is done by root mean square error （RMSE） test.

Indirect-Inversion A lgorithm via Precise Integration for Ill-Conditioned Matrix in Ambiguity Resolution

Global navigation satellite system(GNSS)positioning depends on the correct integer ambiguity resolu-tion(AR).If the double difference equation for solving the float solution remains il-conditioned,often happening due to the environment complexity and the equipment mobility,the corrcct AR is difficult to achieve.Concern-ing the il-conditioned problem,methods of modifying the equation cofficient matrix are widely applied,whose effects are heavily dependent on modifying parameters.Besides,the direct inversion of the il-conditioned coef-ficient matrix can lead to a reduction in the accuracy and stability of the float solution.To solve the problem of il-conditioned matrix inversion and further improve the accuracy,the present study for the first time proves the positive definite symmetry of the coefficient matrix in AR model and employs precise integration method to the indirect inverse of cofficient matrix.AR model for the GNSS positioning and the general resolving strate-gies introduction are briefly introduced.An indirect-inversion algorithm via precise integration for il-conditioned coefficient matrix is proposed.According to the simulations and comparisons,the proposed strategy has higher precision and stability on foat solution,and less dependence on modifying parameters.