Application of interacting multiple model in integrated positioning system of vehicle

To solve low precision and poor stability of the extended Kalman filter （EKF） in the vehicle integrated positioning system owing to acceleration, deceleration and turning （hereinafter referred to as maneuvering） , the paper presents an adaptive filter algorithm that combines interacting multiple model （IMM） and non linear Kalman filter. The algorithm describes the motion mode of vehicle by using three state spacemode]s. At first, the parallel filter of each model is realized by using multiple nonlinear filters. Then the weight integration of filtering result is carried out by using the model matching likelihood function so as to get the system positioning information. The method has advantages of nonlinear system filter and overcomes disadvantages of single model of filtering algorithm that has poor effects on positioning the maneuvering target. At last, the paper uses IMM and EKF methods to simulate the global positioning system （OPS）/inertial navigation system （INS）/dead reckoning （DR） integrated positioning system, respectively. The results indicate that the IMM algorithm is obviously superior to EKF filter used in the integrated positioning system at present. Moreover, it can greatly enhance the stability and positioning precision of integrated positioning system.

Integrity assurance of GNSS-based train integrated positioning system

This paper presents a novel Autonomous Integrity Monitoring and Assurance （AIMA） scheme for integrity assurance of the GNSS-based train integrated positioning system. In this scheme, integrity assurance strategies are combined with a three-stage hierarchical architecture, considering the coupling effects among sensor collection, sensor fusion and matching decision level in train integrated positioning. In sensor collecting stage, the AIMA scheme deals with sensor faults and failures with a PCA-based fault detection, diagnosis and isolation approach. In multi-sensor fusion stage, a novel cubature point H0o filter is presented to enhance the fault tolerance capability, and a hybrid approach is applied to indicating and monitoring the protection level of position estimation, concerning both the estimating covariance and measurement slopes. In map matching stage, hypothesis testing with specific test statistic is carried out to determine effectiveness of positioning results. Position calculation will be invalid with an alarm triggered if the specific integrity criterion is not satisfied in any stage. Since independent solutions are applied in AIMA, integrity assurance is closely coupled with information processing in train integrated positioning. Numerical results of the three cases correspond to the hierarchical architecture with field data and simulations are presented to illustrate features and applicability of the proposed AIMA scheme and specific solutions.

Fuzzy adaptive Kalman filter for indoor mobile target positioning with INS/WSN integrated method

Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.

Performance Trade-off for Integrated Communication and Data-Assisted Positioning in MIMO-OFDM System

Communication and positioning,the two pillars of mobile communication systems,are currently being integrated together.The development of communication technologies is the driving force of the positioning progress.In turn,the location information provided by positioning improves the communication performance in various ways.However,the competition of these two functions in terms of resource allocation is a critical issue hindering their integration.In this article,we investigate the trade-off for the integrated communication and data-assisted positioning in multiple-input multiple-output orthogonal frequency division multiplexing systems.A data-assisted positioning method is designed first,which uses both positioning reference signals(PRSs)and data signals for positioning.The positioning and communication performance are theoretically evaluated respectively,then combined to obtain an integrated performance metric.The trade-off is analyzed and the integrated performance is optimized considering the priority of different functions.Numerical simulations show that the data-assisted positioning can not only improve the positioning accuracy,but also reduce the PRS overhead.And the established integrated performance metric can identify the optimal performance and the corresponding resource allocation schemes.

Coupled Dynamics and Integrated Control for Position and Attitude Motions of Spacecraft:A Survey

Inspired by the integrated guidance and control design for endo-atmospheric aircraft,the integrated position and attitude control of spacecraft has attracted increasing attention and gradually induced a wide variety of study results in last over two decades,fully incorporating control requirements and actuator characteristics of space missions.This paper presents a novel and comprehensive survey to the coupled position and attitude motions of spacecraft from the perspective of dynamics and control.To this end,a systematic analysis is firstly conducted in details to show the position and attitude mutual couplings of spacecraft.Particularly,in terms of the time discrepancy between spacecraft position and attitude motions,space missions can be categorized into two types:space proximity operation and space orbital maneuver.Based on this classification,the studies on the coupled dynamic modeling and the integrated control design for position and attitude motions of spacecraft are sequentially summarized and analyzed.On the one hand,various coupled position and dynamic formulations of spacecraft based on various mathematical tools are reviewed and compared from five aspects,including mission applicability,modeling simplicity,physical clearance,information matching and expansibility.On the other hand,the development of the integrated position and attitude control of spacecraft is analyzed for two space missions,and especially,five distinctive development trends are captured for space operation missions.Finally,insightful prospects on future development of the integrated position and attitude control technology of spacecraft are proposed,pointing out current primary technical issues and possible feasible solutions.

Double Position Servo Synchronous Drive System Based on Cross-Coupling Integrated Feedforward Control for Broacher

Synchronization errors directly deteriorate the machining accuracy of metal parts and the existed method cannot keep high synchronization precision because of external disturbances. A new double position servo synchronous driving scheme based on semi-closed-loop cross- coupling integrated feedforward control is proposed. The scheme comprises a position error cross-coupling feedfor-ward control and a load torque identification with feed- forward control. A digital integrated simulation system for the dual servo synchronous drive system is established. Using a 20 t servo broacher, performance analysis of the scheme is conducted based on this simulation system and the simulation results show that systems with traditional parallel or single control have problems when the work- table works with an unbalanced load. However, the system with proposed scheme shows good synchronous perfor- mance and positional accuracy. Broaching tests are performed and the experimental results show that the maximum dual axis synchronization error of the system is only 8μm during acceleration and deceleration processes and the error between the actual running position and the given position is almost zero. A double position servo synchronous driving scheme is presented based on crosscoupled integrated feedforward compensation control, which can improve the synchronization precision.

BeiDou-GPS integrated dual-system with multi-satellites for positioning and navigating farm vehicles

In order to improve the positioning accuracy of self-propelled farm vehicles and to meet the requirements of precision agriculture on the accuracy of machines,a positioning method was proposed based on BeiDou satellite navigation system(BDS)and GPS dual systems with four satellites.The time base and reference coordinates system of BDS and GPS,as well as the transformation between them were discussed in this paper.Two kinds of mathematical models were proposed for the dual-system multi-satellite positioning and dual-system four-satellite positioning.The solution strategies of the proposed model were detailed,and an improved position calculation model of the dual system was developed with modified models.Experimental results demonstrated that the integrated system could enhance the number of visible satellites,expand the scale of the satellite constellation,increase the number of available satellites and improve the positioning accuracy.Besides,the positioning reliability and continuity were also greatly improved.

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.

UNIQUENESS OF SOLUTIONS FOR A CLASS OF NON-LINEAR VOLTERRAINTEGRAL EQUATIONS WITHOUT CONTINUITY

In this paper. the fixed point theorem of increasing opera for with non-continuityis uilized to discuss foe exislence and uniqueness of positire solution for a class of nonlinear Volterra integral equations. An important condition of continuity can bereplaced by weak condition.

Detection and Analysis of Strong Ionospheric Scintillation in Equatorial Region

To detect the occurrence of ionospheric scintillation in the equatorial region,a coherent/non-coherent integration method is adopted on the accumulation of intermediate frequency(IF)signal and local code,in the process of signal acquisition based on software receiver.The processes of polynomial fitting and sixth-order Butterworth filtering are introduced to detrend the tracking results.Combining with ionospheric scintillation detection algorithm and preset thresholds,signal acquisition and tracking,scintillation detection,positioning solution are realized under the influence of strong ionospheric scintillation.Under the condition that the preset threshold of amplitude and carrier phase scintillation indices are set to 0.5 and 0.15,and the percentage of scin-tillation occurrence is 50%,respectively,PRN 12 and 31 affected by strong amplitude scintillation are detected effectively.Results show that the positioning errors in the horizontal direction are below 5m approximately.The software receiver holds performances of accurate acquisition,tracking and positioning on the strong ionospheric scintillation conditions,which can provide important basis and helpful guidance for relevant research on ionospheric scintillation,space weather and receiver design with high performance.

Unmanned aerial vehicle positioning based on multi-sensor information fusion

Unmanned aerial vehicle(UAV)positioning is one of the key techniques in the field of UAV navigation.Although the high positioning precision of UAV can be achieved through global positioning system(GPS),the frequency of updating signal in GPS is low and the energy consumption of GPS module is huge,which does not satisfy the real-time demand of UAV positioning.In this paper,a multi-sensor information fusion method based on GPS,inertial navigation system(INS),and the visible light sensors is proposed for UAV positioning.The Kalman filter combining with simulated annealing algorithm is used to estimate the position error between GPS or INS and the visible light sensors,and then the motion trajectory is corrected according to this position error information.Therefore,the positioning accuracy of UAV can be improved in case of only INS being available.Experimental results demonstrate that the proposed method can remarkably improve the positioning accuracy and greatly reduce the energy consumption.

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.

ITERATIVE POSITIVE SOLUTIONS FOR SINGULAR RIEMANN-STIELTJES INTEGRAL BOUNDARY VALUE PROBLEM

By applying iterative technique,we obtain the existence of positive solutions for a singular Riemann-Stieltjes integral boundary value problem in the case that f（t,u） is non-increasing respect to u.