Improvement Of Positioning Accuracy Research Articles

Improvement of Positional Accuracy of Developed Dicing Machine

Improvement of Positional Accuracy of Developed Dicing Machine

Simulation Study for Controlling Direct Current Motor Position Utilising Fuzzy Logic Controller

A fuzzy logic controller (FLC) modelled with MATLAB toolbox that is implemented for position control of a direct current (DC) motor is presented in this paper. The position control is an adaptation of an assisted lifting device system. Due to the existing assisted lifting device problems that lift the load slowly and having lack of accuracy, this research is conducted to improve current assisted lifting device with the introduction of a DC motor and a fuzzy logic controller that can improve position accuracy, especially when loading the loads. The DC motor was modelled, converted to a subsystem in Simulink and then the MATLAB toolbox is used to design the FLC. The methodology covers the simulation and modelling of the DC motor, fuzzy logic controller and different transfer functions for DC motor model as a benchmark to the performance of the fuzzy system. The outcomes acquired from the scope of the simulation was analysed. Parameters such as the rise and settling time in seconds and maximum overshoot in percentage are observed to be compared with different types of transfer functions that are used for the dynamic response of the closed-loop system and system with and without a controller that was used as references. The overall performance shows that a system with FLC performs well compared to the system without FLC.

Convolutional Neural Network Based Multipath Detection Method for Static and Kinematic GPS High Precision Positioning

Global Positioning System (GPS) has been used in many aerial and terrestrial high precision positioning applications. Multipath affects positioning and navigation performance. This paper proposes a convolutional neural network based carrier-phase multipath detection method. The method is based on the fact that the features of multipath characteristics in multipath contaminated data can be learned and identified by a convolutional neural network. The proposed method is validated with simulated and real GPS data and compared with existing multipath mitigation methods in position domain. The results show the proposed method can detect about 80% multipath errors (i.e., recall) in both simulated and real data. The impact of the proposed method on positioning accuracy improvement is demonstrated with two datasets, 18–30% improvement is obtained by down-weighting the detected multipath measurements. The focus of this paper is on the development and test of the proposed convolutional neural network based multipath detection algorithm.

An Enhanced Map-Matching Algorithm for Real-Time Position Accuracy Improvement with a Low-Cost GPS Receiver.

This paper proposes a real-time position accuracy improvement method for a low-cost global positioning system (GPS), which uses geographic data for forming a digital road database in the digital map information. We link the vehicle’s location to the position on the digital map using the map-matching algorithm to improve the position accuracy. In the proposed method, we can distinguish the vehicle direction on the road and enhance the horizontal accuracy using the geographic data composed of the vector point set of the digital map. We use the iterative closest point (ICP) algorithm that calculates the rotation matrix and the translation vector to compensate for the disparity between the GPS and the digital map information. We also use the least squares method to correct the error caused by the rotation of the ICP algorithm and link on the digital map to eliminate the residual disparity. Finally, we implement the proposed method in real time with a low-cost embedded system and demonstrate the effectiveness of the proposed method through various experiments.

Evolutionary Algorithm-Based Friction Feedforward Compensation for a Pneumatic Rotary Actuator Servo System

The friction interference in the pneumatic rotary actuator is the primary factor affecting the position accuracy of a pneumatic rotary actuator servo system. The paper proposes an evolutionary algorithm-based friction-forward compensation control architecture for improving position accuracy. Firstly, the basic equations of the valve-controlled actuator are derived and linearized in the middle position, and the transfer function of the system is further obtained. Then, the evolutionary algorithm-based friction feedforward compensation control architecture is structured, including that the evolutionary algorithm is used to optimize the controller coefficients and identify the friction parameters. Finally, the contrast experiments of four control strategies (the traditional PD control, the PD control with friction feedforward compensation without evolutionary algorithm tuning, the PD control with friction feedforward compensation based on the differential evolution algorithm, and the PD control with friction feedforward compensation based on the genetic algorithm) are carried out on the experimental platform. The experimental results reveal that the evolutionary algorithm-based friction feedforward compensation greatly improves the position tracking accuracy and positioning accuracy, and that the differential evolution-based case achieves better accuracy. Also, the system with the friction feedforward compensation still maintains high accuracy and strong stability in the case of load.

Real Time Precise Relative Positioning with Moving Multiple Reference Receivers.

The stationary reference receiver with precisely known coordinates is difficult to establish in some special real-time relative positioning applications. To improve the relative position estimation accuracy and the reliability simultaneously for the RTK without a precisely known reference receiver, multiple receivers mounted on a moving platform are used as the base station. A code and phase measurement fusion model is proposed to reduce the communication burden and generate measurements at any virtual position where it is inconvenient to install the GPS receiver. To keep the integer property of the ambiguity of fused phase measurements, the RTK method with the moving reference receivers is proposed by implementing the integer ambiguity transformation and error absorption strategy based on the known geometry of multiple receivers. Static and kinematic experiments were carried out to evaluate the performance of the proposed relative positioning method. When compared with the single-receiver solution, static results have shown that the proposed method can improve position accuracy by 15.9% and 15.7% for the horizontal and the vertical component, respectively. The kinematic results have shown that the proposed method can achieve position accuracy enhancement by 26.9% for the vertical component.

Geometric Positioning Accuracy Improvement of ZY-3 Satellite Imagery Based on Statistical Learning Theory.

With the increasing demand for high-resolution remote sensing images for mapping and monitoring the Earth’s environment, geometric positioning accuracy improvement plays a significant role in the image preprocessing step. Based on the statistical learning theory, we propose a new method to improve the geometric positioning accuracy without ground control points (GCPs). Multi-temporal images from the ZY-3 satellite are tested and the bias-compensated rational function model (RFM) is applied as the block adjustment model in our experiment. An easy and stable weight strategy and the fast iterative shrinkage-thresholding (FIST) algorithm which is widely used in the field of compressive sensing are improved and utilized to define the normal equation matrix and solve it. Then, the residual errors after traditional block adjustment are acquired and tested with the newly proposed inherent error compensation model based on statistical learning theory. The final results indicate that the geometric positioning accuracy of ZY-3 satellite imagery can be improved greatly with our proposed method.

Elevation and Position Uncertainty based KF Model for Position Accuracy Improvement

This paper discusses about improvement of Global Positioning System (GPS) receiver position accuracy based on elevation angle and position uncertainty parameters. Kalman Filter method is used to estimate the receiver position which by default provides position uncertainty along with error in position. To improve accuracy, the proposed method focuses on proper selection of satellites to be considered among the visible satellites to evaluate the receiver’s position accuracy. At a particular epoch the combination of satellites with high elevation angles results in better receiver position. The analysis has been carried out by considering different combinations of satellites with high elevation angles from a number of visible satellites at a particular epoch. The results of the proposed method are very promising for precise applications of GPS particularly in the civil aviation sector.

GDOP Analysis with Optimal Satellites Using GA for Southern Region of Indian Subcontinent

The emergence of Global Positioning System (GPS) has reformed the application areas of navigation, predominantly in aviation sector. Satellite geometry plays crucial role, which indicates the geometric positions of the satellites as perceived by the GPS receiver. But, many factors affect the position accuracy of GPS. The position accuracy sustained by satellite geometry. Effect of geometry can be restrained by Geometric Dilution Of Precision (GDOP). Stronger the geometry, finer the GDOP value. In general the GDOP ranges from 2 to 6. In a GPS system, minimum of four satellites are involved while computing the user position. From the set of more visible satellites, optimal subsets with minimum number of satellites need to be selected to reduce the superfluity. This paper gives a new hybrid method for estimation of GDOP using optimum number of satellites to improve position accuracy using popular optimization technique i.e., Genetic Algorithm (GA).

High-Speed Active Release End-Effector Motions for Precise Positioning of Adhered Micro-Objects

This paper presents a release method for micro-objects. To improve position accuracy after release, we propose 3D high-speed end-effector motions. The classical release task focuses on the detachment of a micro-object from an end-effector. The technique utilizes merely the vibration of the end-effector regardless of the pattern of movement. To release different sizes of micro- objects and place them precisely at the desired locations in both air and liquid media, in this paper, we propose high-speed motions by analyzing the adhesion force and movement of micro-objects after separation. To generate high end-effector acceleration, many researchers have applied simple vibration by using an additional actuator. However, in our research, 3D high-speed motion with apt amplitude is accomplished by using only a compact parallel mechanism. To verify the advantages of the proposed motion, we compare five motions, 1D motions (in X-, Y-, and Z-directions) and circular motions (clockwise and counterclockwise directions), by changing the frequency and amplitude of the end-effector. Experiments are conducted with different sizes of microbeads and NIH3T3 cells. From these experiments, we conclude that a counterclockwise circular motion can release the objects precisely in air, while 1D motion in the Y direction and two circular motions can detach the objects at the desired positions after release in a liquid environment.

Simultaneous estimation of GLONASS pseudorange inter-frequency biases in precise point positioning using undifferenced and uncombined observations

GLONASS precise point positioning (PPP) performance is affected by the inter-frequency biases (IFBs) due to the application of frequency division multiple access technique. In this contribution, the impact of GLONASS pseudorange IFBs on convergence performance and positioning accuracy of GLONASS-only and GPS + GLONASS PPP based on undifferenced and uncombined observation models is investigated. Through a re-parameterization process, the following four pseudorange IFB handling schemes were proposed: neglecting IFBs, modeling IFBs as a linear or quadratic polynomial function of frequency number, and estimating IFBs for each GLONASS satellite. One week of GNSS observation data from 132 International GNSS Service stations was selected to investigate the contribution of simultaneous estimation of GLONASS pseudorange IFBs on GLONASS-only and combined GPS + GLONASS PPP in both static and kinematic modes. The results show that considering IFBs can speed up the convergence of PPP using GLONASS observations by more than 20%. Apart from GLONASS-only kinematic PPP, the positioning accuracy of GLONASS-only and GPS + GLONASS PPP is comparable among the four schemes. Overall, the scheme of estimating IFBs for each GLONASS satellite outperforms the other schemes in both convergence time reduction and positioning accuracy improvement, which indicates that the GLONASS IFBs may not strictly obey a linear or quadratic function relationship with the frequency number.

CADASTRAL DATABASE POSITIONAL ACCURACY IMPROVEMENT

Abstract. Positional Accuracy Improvement (PAI) is the refining process of the geometry feature in a geospatial dataset to improve its actual position. This actual position relates to the absolute position in specific coordinate system and the relation to the neighborhood features. With the growth of spatial based technology especially Geographical Information System (GIS) and Global Navigation Satellite System (GNSS), the PAI campaign is inevitable especially to the legacy cadastral database. Integration of legacy dataset and higher accuracy dataset like GNSS observation is a potential solution for improving the legacy dataset. However, by merely integrating both datasets will lead to a distortion of the relative geometry. The improved dataset should be further treated to minimize inherent errors and fitting to the new accurate dataset. The main focus of this study is to describe a method of angular based Least Square Adjustment (LSA) for PAI process of legacy dataset. The existing high accuracy dataset known as National Digital Cadastral Database (NDCDB) is then used as bench mark to validate the results. It was found that the propose technique is highly possible for positional accuracy improvement of legacy spatial datasets.

Contribution of BeiDou Positioning System for Accuracy Improvement: A Perspective from Bandung, Indonesia

Currently, BeiDou Navigation Satellite System (BDS) has been operating in Asia-Pacific especially in Indonesia Region. BDS is expected to enhance the accuracy of positioning, include for static survey. Aim of this research is to estimate the positioning accuracy improvement for static survey in Bandung Indonesia. The methodology applied in this research are the GNSS data collecting using COMNAV T300 GNSS receivers from 13 GPS stations using network design, data processing by using GPS only and combined used of GPS and BeiDou data, and analyzing of accuracy improvement. The result indicates that the combination of BDS data (B1 and B2) with GPS (L1 and L2), compared with GPS (L1 and L2) only, provides a better accuracy by 31.3% in easting, 49.9% in northing and 13.6% in height components, and in precision by 20.1% in easting, 30.7% in northing and 32.7% in height. Finally, it can be expected to improve positioning accuracy by using BeiDou system for static survey in Bandung region.

Lane Determination With GPS Precise Point Positioning

Modern intelligent transport solutions can achieve an improvement of traffic flow on motorways. With lane-specific measurements and lane-specific control, more measures are possible. Single frequency precise point positioning (PPP) is a newly developed and affordable technique to achieve an improved position accuracy compared with global positioning system (GPS) standalone positioning. GPS-PPP allows for sub-meter accurate positioning, in real time, of vehicles on a motorway. This paper tests this technique in real life; moreover, it presents a methodology to map the lanes on a motorway using data collected by this technique. The methodology exploits the high accuracy and the fact that the most driving is within a lane. In a field test, a GPS-PPP equipped vehicle drives a specific motorway stretch 100 times, for which the GPS-PPP trajectory data are collected. Using these data, the positions and the widths of different lanes are successfully estimated. Comparison with the ground truth shows a dm accuracy. With the parametrized lanes, vehicles can be tracked down to a lane with the GPS-PPP device.

Kinematic calibration and investigation of the influence of universal joint errors on accuracy improvement for a 3-DOF parallel manipulator

This paper focuses on the accuracy enhancement of a 3-PRRU parallel manipulator and the influence of imperfect universal joints on calibration result through kinematic calibration. The error model of the PRRU limb that contains all of the identifiable kinematic errors is established based on modified Denavit–Hartenberg method and Hayati convention. By eliminating the motion errors of passive joints and combining all of the limbs’ error models, the calibration model of the parallel manipulator is obtained. To verify the effectiveness of the error model and investigate the influence of the imperfect universal joints on positioning accuracy improvement, numerical simulations and experiments of kinematic calibration are respectively conducted and total least squares method is used to identify the kinematic parameters. The results of the simulations and experiments show that the defects of universal joints have smaller effect on the accuracy improvement for this manipulator when compared with the cases that the universal joints are perfectly manufactured and assembled.

Ranging Consistency Based on Ranging-Compensated Temperature-Sensing Sensor for Inter-Satellite Link of Navigation Constellation.

Global Navigation Satellite System performance can be significantly enhanced by introducing inter-satellite links (ISLs) in navigation constellation. The improvement in position, velocity, and time accuracy as well as the realization of autonomous functions requires ISL distance measurement data as the original input. To build a high-performance ISL, the ranging consistency among navigation satellites is an urgent problem to be solved. In this study, we focus on the variation in the ranging delay caused by the sensitivity of the ISL payload equipment to the ambient temperature in space and propose a simple and low-power temperature-sensing ranging compensation sensor suitable for onboard equipment. The experimental results show that, after the temperature-sensing ranging compensation of the ISL payload equipment, the ranging consistency becomes less than 0.2 ns when the temperature change is 90 °C.

An Improved Compressive Sensing and Received Signal Strength-Based Target Localization Algorithm with Unknown Target Population for Wireless Local Area Networks.

In this paper a two-phase compressive sensing (CS) and received signal strength (RSS)-based target localization approach is proposed to improve position accuracy by dealing with the unknown target population and the effect of grid dimensions on position error. In the coarse localization phase, by formulating target localization as a sparse signal recovery problem, grids with recovery vector components greater than a threshold are chosen as the candidate target grids. In the fine localization phase, by partitioning each candidate grid, the target position in a grid is iteratively refined by using the minimum residual error rule and the least-squares technique. When all the candidate target grids are iteratively partitioned and the measurement matrix is updated, the recovery vector is re-estimated. Threshold-based detection is employed again to determine the target grids and hence the target population. As a consequence, both the target population and the position estimation accuracy can be significantly improved. Simulation results demonstrate that the proposed approach achieves the best accuracy among all the algorithms compared.

Operational Temperature Effect on Positioning Accuracy of a Single-Axial Moving Carrier

This study investigated the ambient environmental temperature effect on the positioning accuracy of a periodically-moving carrier. The moving carrier was operated in an environmental chamber in which the operational temperature could be controlled by an air conditioning system. Different operational temperature modes, including a stable environment, a rise in temperature, a decline in temperature, summer daytime hours, and winter nighttime hours in terms of seasonal climate change in Taiwan, were generated within the environmental chamber by an air conditioning system to investigate the operational temperature’s effect on positioning accuracy. From the experimental measurements of a periodically-moving carrier, it is found that the operational temperature conditions can significantly affect the positioning accuracy of the moving carrier, especially in the case of an operational temperature decline. Under stable operational conditions, the positioning accuracy of the moving carrier can be considerably improved. In comparison to the case of an operational temperature decline, the positioning accuracy improvement can reach 29.6%. Moreover, the effect of the temperature distributions within the chamber on the positioning accuracy was further investigated. It was found that, with a parallel flow pattern in the chamber, the positioning accuracy can be further enhanced.

Cooperative GNSS positioning aided by road-features measurements

Cooperation between road users through V2X communication is a way to improve GNSS localization accuracy. When vehicles localization systems involve standalone GNSS receivers, the resulting accuracy can be affected by satellite-specific errors of several meters. This paper studies how road-features like lane marking detected by on-board cameras can be exploited to reduce absolute position errors of cooperative vehicles sharing information in real-time in a network. The algorithms considered in this work are based on a error bounded set membership strategy. In every vehicle, a set membership algorithm computes the absolute position and an estimation of the satellite-specific errors by using raw GNSS pseudoranges, lane boundary measurements and a 2D georeferenced road map which provides absolute geometric constraints. As lane-boundary measurements provide essentially cross-track corrections in the position estimation process, cooperation enables the vehicles to improve their own estimates thanks to the different orientation of the roads. Set-membership methods are very efficient to solve this problem since they do not involve any independence hypothesis of the errors and so, the same information can be used several times in the computation. Such class of algorithm provides a novel approach to improve position accuracy for connected vehicles guaranteeing the integrity of the computed solution which is pivoting for automated automotive systems requiring guaranteed safety-critical solutions. Results from simulations and real experiments show that sharing position corrections reduces significantly satellite-specific GNSS errors effects in both cross-track and along-track components. Moreover, it is shown that lane-boundary measurements help reducing estimation errors for all the networked vehicles even those which are not equipped with an embedded perception system.

Comparative analysis of multi-constellation GNSS single-frequency precise point positioning

We develop new single-frequency PPP models, which combine the observations of the current GNSS constellations, including GPS, GLONASS, Galileo and BeiDou. Four single-frequency GNSS PPP models are developed, namely, the undifferenced single-frequency GNSS PPP model, the undifferenced ionosphere-free (IF) code and phase model known as quasi-phase model, the between-satellite-single-difference model (BSSD) and the between-satellite-single-difference ionosphere-free (BSSDIF) model. The IGS final precise products are used to account for the orbital and clock errors. For both undifferenced and BSSD models, the IGS final global ionospheric maps (GIM) model is used to correct the ionospheric delay. The GNSS inter-system biases are treated as additional unknowns in the estimation process for the undifferenced models, while a loosely coupled technique is used for the BSSD models. Various GNSS combinations are considered in the assessment for each PPP model, including GPS/GLONASS, GPS/Galileo, GPS/BeiDou and quad-constellation GNSS observations. It is shown that the multi-GNSS observations enhance the PPP solution accuracy in comparison with the GPS-only solution. Furthermore, the use of IF-PPP technique enhances the positioning accuracy by 25, 20, 24, 20 and 19% compared with the GIM-based PPP model for the GPS-only, GPS/GLONASS, GPS/Galileo, GPS/BeiDou and quad-GNSS combinations, respectively, for 1 h of GNSS data processing. In addition, an average of 15% positioning accuracy improvement can be obtained when the BSSD techniques are used compared with the undifferenced techniques. However, for 6 h of processing, comparable positioning accuracy can be obtained from all four single-frequency models.