Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

An RGB-D Camera Based Visual Positioning System for Assistive Navigation by a Robotic Navigation Aid

There are about 253 million people with visual impairment worldwide.Many of them use a white cane and/or a guide dog as the mobility tool for daily travel.Despite decades of efforts,electronic navigation aid that can replace white cane is still research in progress.In this paper,we propose an RGB-D camera based visual positioning system(VPS)for real-time localization of a robotic navigation aid(RNA)in an architectural floor plan for assistive navigation.The core of the system is the combination of a new 6-DOF depth-enhanced visual-inertial odometry(DVIO)method and a particle filter localization(PFL)method.DVIO estimates RNA’s pose by using the data from an RGB-D camera and an inertial measurement unit(IMU).It extracts the floor plane from the camera’s depth data and tightly couples the floor plane,the visual features(with and without depth data),and the IMU’s inertial data in a graph optimization framework to estimate the device’s 6-DOF pose.Due to the use of the floor plane and depth data from the RGB-D camera,DVIO has a better pose estimation accuracy than the conventional VIO method.To reduce the accumulated pose error of DVIO for navigation in a large indoor space,we developed the PFL method to locate RNA in the floor plan.PFL leverages geometric information of the architectural CAD drawing of an indoor space to further reduce the error of the DVIO-estimated pose.Based on VPS,an assistive navigation system is developed for the RNA prototype to assist a visually impaired person in navigating a large indoor space.Experimental results demonstrate that:1)DVIO method achieves better pose estimation accuracy than the state-of-the-art VIO method and performs real-time pose estimation(18 Hz pose update rate)on a UP Board computer;2)PFL reduces the DVIO-accrued pose error by 82.5%on average and allows for accurate wayfinding(endpoint position error≤45 cm)in large indoor spaces.

Hybrid Navigation System Based Autonomous Positioning and Path Planning for Mobile Robots

Positioning and navigation technology is a new trend of research in mobile robot area.Existing researches focus on the indoor industrial problems,while many application fields are in the outdoor environment,which put forward higher requirements for sensor selection and navigation scheme.In this paper,a complete hybrid navigation system for a class of mobile robots with load tasks and docking tasks is presented.The work can realize large-range autonomous positioning and path planning for mobile robots in unstructured scenarios.The autonomous positioning is achieved by adopting suitable guidance methods to meet different application requirements and accuracy requirements in conditions of different distances.Based on the Bezier curve,a path planning scheme is proposed and a motion controller is designed to make the mobile robot follow the target path.The Kalman filter is established to process the guidance signals and control outputs of the motion controller.Finally,the autonomous positioning and docking experiment are carried out.The results of the research verify the effectiveness of the hybrid navigation,which can be used in autonomous warehousing logistics and multi-mobile robot system.

AN ADVANCED DUAL-FREQUENCY POSITIONING ALGORITHM FOR SATELLITE NAVIGATION RECEIVERS

With the development of the Ground Positioning System (GPS) modernization and the expectable implementation of Galileo, people pay more and more attention to civil applications on multi-frequency signals. This paper proposes a new and advanced positioning algorithm for the dual-frequency satellite navigation receivers, concerning the various influences of all the ranging error sources and taking advantage of the Klobuchar single-frequency ionospheric model. The paper also presents positioning precision provided by the new algorithm. Theoretical analysis and experimental results show that, the new dual-frequency positioning algorithm can achieve higher positioning accu- racy than the single-frequency positioning algorithm and the traditional dual-frequency positioning algorithm.

Resilient tightly coupled INS/UWB integration method for indoor UAV navigation under challenging scenarios

Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are easy to be blocked or reflected by obstacles such as walls and furniture.A resilient tightly-coupled inertial navigation system(INS)/UWB integration is proposed and implemented for indoor UAV navigation in this paper.A factor graph optimization(FGO)method enhanced by resilient stochastic model is established to cope with the indoor challenging scenarios.To deal with the impact of UWB non-line-of-sight(NLOS)signals and noise uncertainty,the conventional neural net-works(CNNs)are introduced into the stochastic modelling to improve the resilience and reliability of the integration.Based on the status that the UWB features are limited,a‘two-phase'CNNs structure was designed and implemented:one for signal classification and the other one for measurement noise prediction.The proposed resilient FGO method is tested on flighting UAV platform under actual indoor challenging scenario.Compared to classical FGO method,the overall positioning errors can be decreased from about 0.60 m to centimeter-level under signal block and reflection scenarios.The superiority of resilient FGO which effectively verified in constrained environment is pretty important for positioning accuracy and integrity for indoor navigation task.

Position and complications of pedicle screw insertion with or without image-navigation techniques in the thoracolumbar spine:a meta-analysis of comparative studies

Computer-navigated pedicle screw insertion is applied to the thoracic and lumbar spine to attain high insertion accuracy and a low rate of screw-related complications.However,some in vivo and in vitro studies have shown that no advantages are gained with the use of navigation techniques compared to conventional techniques.Additionally,inconsistent conclusions have been drawn in various studies due to different population characteristics and methods used to assess the accuracy of screw placement.Moreover,it is not clear whether pedicle screw insertion with navigation techniques decreases the incidence of screw-related complications.Therefore,this study was sought to perform a meta-analysis of all available prospective evidence regarding pedicle screw insertion with or without navigation techniques in human thoracic and lumbar spine.We considered in vivo comparative studies that assessed the results of pedicle screw placement with or without navigation techniques.PubMed,Ovid MEDLINE and EMBASE databases were searched.Three published randomized controlled trials（RCTs） and nine retrospective comparative studies met the inclusion criteria.These studies included a total of 732 patients in whom 4,953 screws were inserted.In conclusion,accuracy of the position of grade I,II,III and IV screws and complication rate related to pedicle screw placement were significantly increased when navigation techniques were used in comparison to conventional techniques.Future research in this area should include RCTs with well-planned methodology to limit bias and report on validated,patient-based outcome measures.

Local Scenario Perception and Web AR Navigation

This paper proposes a local point cloud map-based Web augmented reality(AR)indoor navigation system solution.By delivering the local point cloud map to the web front end for positioning,the real-time positioning can be implemented only with the help of the computing power of the web front end.In addition,with the characteristics of short time consumption and accurate positioning,an optimization solution to the local point cloud map is proposed,which includes specific measures such as descriptor de-duplicating and outlier removal,thus improving the quality of the point cloud.In this document,interpolation and smoothing effects are introduced for local map positioning,enhancing the anchoring effect and improving the smoothness and appearance of user experience.In small-scale indoor scenarios,the positioning frequency on an iPhone 13 can reach 30 fps,and the positioning precision is within 50 cm.Compared with an existing mainstream visual-based positioning manner for AR navigation,this specification does not rely on any additional sensor or cloud computing device,thereby greatly saving computing resources.It takes a very short time to meet the real-time requirements and provide users with a smooth positioning effect.

An Improved Particle Filter Map Matching Algorithm for Personal Inertial Positioning

The current particle filtering map matching algorithm has problems such as low map utilization and poor accuracy of turnoff positioning, etc. This paper proposed an improved particle filtering-based map-matching algorithm for the inertial positioning of personnel. The historical moment position constraint and feasible region constraint of particles were introduced in this paper. A resampling method based on multi-stage backtracking of particles was proposed. Therefore, the effectiveness of newly generated particles could be guaranteed. The utilization rate of map information could be improved, thus enhancing the accuracy of personnel localization. The walking experiment results showed that, compared with the traditional PDR algorithm, the proposed method had higher localization accuracy and better repeatability of the localization trajectory for multi-turn paths. Under the total travel of 480 meters, the deviation of the starting end point was less than 2 meters, which was about 0.4% of the total travel.

Topology and Position Aware Overlay Network Construction Protocol for Augmentation Information of Satellite Navigation System

It is an effective method to broadcast the augmentation information of satellite navigation system using GEO technology.However,it becomes difficult to receive GEO signal in some special situation,for example in cities or canyons,in which the signal will be sheltered by big buildings or mountains.In order to solve this problem,an Internet-based broadcast network has been proposed to utilize the infrastructure of the Internet to broadcast the augmentation information of satellite navigation system,which is based on application-layer multicast protocols.In this paper,a topology and position aware overlay network construction protocol is proposed to build the network for augmentation information of satellite navigation system.Simulation results show that the new algorithm is able to achieve better performance in terms of delay,depth and degree utilization.

IAE-adaptive Kalman filter for INS/GPS integrated navigation system

A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.

GPS/VISNAV integrated relative navigation and attitude determination system for ultra-close spacecraft formation flying

For the improvement of accuracy and better fault-tolerant performance, a global position system （GPS）/vision navigation （VISNAV） integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying. Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design. Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.

Analysis and Comparison of Range-Range Positioning Mode and Hyperbolic Positioning Mode

Three key factors are discussed, which affect positioning accuracy of range-range positioning mode and hyperbolicpositioning mode.Based on the error elliptical theory, the expressions of positioning error and of positioning geometric factor ofrange-range positioning mode and hyperbolic positioning mode are derived, and the positioning error and the blind positioningarea of two different positioning modes are analyzed. According to the requirement of navigation area, an optimum

The Quality Assessment of Non-Integer-Hour Data in GPS Broadcast Ephemerides and Its Impact on the Accuracy of Real- Time Kinematic Positioning Over the South China Sea

Abnormal effects in GPS broadcast ephemerides can have a significant effect on real-time navigation and positioning solutions that use the orbit and clock error data provided by GPS broadcast ephemerides.This paper describes three types of non-integerhour navigation data in GPS broadcast ephemeris data.Compared with GPST integer hour data,we find that there are two types of data blocks for non-integer-hour navigation containing gross errors with different levels of precision,which is reflected in the user range accuracy(URA)of the broadcast ephemeris.These gross errors can cause large deviations when using the GPS broadcast ephemeris for orbit calculation and lead to a decrease in the kinematic positioning accuracy.An improved weighting method which is based on the consistency relationship between the URA value and the orbital precision is proposed to improve the positioning accuracy by controlling the effect of gross errors in the broadcast ephemerides.The correction algorithm proposed in this paper was applied to real-time kinematic positioning with shipborne GPS data over the South China Sea.The results showed that the proposed positioning algorithm can effectively reduce the effects of gross errors in the broadcast ephemeris,and significantly improve the accuracy of the navigation and positioning.

A Dual-Satellite GNSS Positioning Algorithm of High Accuracy in Incomplete Condition

Global navigation satellite system could provide accurate positioning results in signal complete condition. However, the performance is severe when signal denied, especially for the single-mode Bei Dou receiver. This paper proposes a dual-satellite positioning algorithm to promote the positioning performance in the satellite signal gap. The new algorithm utilizes the previous positioning data stored in complete condition to simplify the positioning equations. As the clock bias persists for a short period, this proposed method could work out accurate positioning results by only two visible satellites, without the need of computing the clock bias. Also, the Kalman filtering algorithm is used to smooth the trajectories, and improve the positioning results. During the incomplete period, only two satellites for 30 seconds and three satellites for 60 seconds, the preliminary experiment result shows that, the presented method could provide almost the same positioning results as in complete condition.

New Regional Satellite Positioning Constellation Scheme Discussion

The characteristics of present “Beidou” satellite positioning system are analyzed. In order to perfect our country regional satellite positioning system, the idea of “Beidou” geosychronous earth orbit （GEO） satellites combined with some middle earth orbit （MEO） satellites constellation is put forward. The details of general satellite constellation optimized method are described, using this method the multiple positioning constellation design results are gained. And those results belong to two type of sehems, one is 2 GEO plus some MEO satellites and the other is 3 GEO plus some MEO satellites. Through simulation and comparison, among those multiple design results, final optimized regional positioning constellation is given. In order to check the chosen constellation cover performance, the position dilution of preeision（PDOP） is calculated, and with ,satellite constellation simulation software Satlab many coverage performances of the chosen constellation substellar point track, elevation, azimuth and visible satellites number changing situation are also simulated.

A Novel Edge Computing Based Area Navigation Scheme

The area navigation system,discussed in this paper,is composed of ground responders and a navigation terminal and can position a high-velocity aircraft and measure its velocity.This navigation system is silent at ordinary times.It sends out a request signal when positioning is required for an aircraft,and then the ground responders send a signal for resolving the aircraft.Combining the direct sequence spread spectrum and frequency hopping,the concealed communication mode is used in the whole communication process,with short communication pulses as much as possible,so the system has strong concealment and anti-interference characteristics.As the transmission delay is apparent in the response communication mode,there is a big error where the common navigation algorithm is used for the positioning and velocity measurement of a high-velocity aircraft.In this paper,a new algorithm is proposed,which can eliminate the influence of response communication delay on the positioning of a high-velocity moving target to realize the precise positioning and velocity measurement of a high-velocity aircraft.

A GPS/BDS dual-mode positioning algorithm for a train based on CIPSO_EKF

When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the features of the dual-mode observation.Due to multipath effect,positioning accuracy of present Kalman filter algorithm is really low.To solve this problem,a chaotic immune-vaccine particle swarm optimization_extended Kalman filter(CIPSO_EKF)algorithm is proposed to improve the output accuracy of the Kalman filter.By chaotic mapping and immunization,the particle swarm algorithm is first optimized,and then the optimized particle swarm algorithm is used to optimize the observation error covariance matrix.The optimal parameters are provided to the EKF,which can effectively reduce the impact of the observation value oscillation caused by multipath effect on positioning accuracy.At the same time,the train positioning results of EKF and CIPSO_EKF algorithms are compared.The eastward position errors and velocity errors show that CIPSO_EKF algorithm has faster convergence speed and higher real-time performance,which can effectively suppress interference and improve positioning accuracy.

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.

Progresses and Prospects of Marine Geodetic Datum and Marine Navigation in China

Territorial water is a significant part of national sovereignty of China,thus the infrastructures of national space datum and location services should cover the sea areas except for the land areas.China has established relatively complete geodetic coordinate frame in land areas over the past decades,including the lastest developed China Geodetic Coordinate System 2000(CGCS 2000)with its reference frame and the national gravity datum 2000.However,the currently used geodetic infrastructures have not well covered the sea areas of China.The marine geodetic datum and marine navigation technologies need to be further developed and extended to satisfy the national demands of marine environment and resources detection,scientific investigation as well as marine economy development in new era of China.This paper mainly reviews the development and the progress of Chinese marine geodetic datum and marine navigation,analyses related key technologies in establishing our national marine geodetic datum.Some current trends and future directions for independently developing our national marine geodetic datum and marine navigation technologies are discussed.

Signal quality analysis and quality check of BDS3 Precise Point Positioning in the Arctic Ocean

This study analyzes the signal quality and the accuracy of BeiDou 3 rd generation Satellite Navigation System(BDS3) Precise Point Positioning(PPP) in the Arctic Ocean. Assessment of signal quality of BDS3 includes signal to noise ratio(SNR), multipath(MP), dilution of precision(DOP), and code-minus-carrier combination(CC). The results show that, 5 to 13 satellites are visible at any time in the Arctic Ocean area as of September 2018, which are sufficient for positioning. In the mid-latitude oceanic region and in the Arctic Ocean, the SNR is 25–52 dB Hz and the MP ranges from-2 m to 2 m. As the latitude increases, the DOP values show large variation, which may be related to the distribution of BDS satellites. The CC values of signals B1 I and BIC range from-5 m to 5 m in the mid-latitude sea area and the Arctic Ocean, which means the effect of pseudorange noise is small. Moreover, as to obtain the external precise reference value for GNSS positioning in the Arctic Ocean region is difficult, it is hard to evaluate the accuracy of positioning results. An improved isotropy-based protection level method based on Receiver Autonomous Integrity Monitoring is proposed in the paper, which adopts median filter to smooth the gross errors to assess the precision and reliability of PPP in the Arctic Ocean. At first, the improved algorithm is verified with the data from the International GNSS Service Station Tixi. Then the accuracy of BDS3 PPP in the Arctic Ocean is calculated based on the improved algorithm. Which shows that the kinematic accuracy of PPP can reach the decimeter level in both the horizontal and vertical directions, and it meets the precision requirements of maritime navigation.