Fast Positioning Research Articles

Ionospheric corrections tailored to the Galileo High Accuracy Service

The Galileo High Accuracy Service (HAS) is a new capability of the European Global Navigation Satellite System that is currently under development. The Galileo HAS will start providing satellite orbit and clock corrections (i.e. non-dispersive effects) and soon it will also correct dispersive effects such as inter-frequency biases and, in its full capability, ionospheric delay. We analyse here an ionospheric correction system based on the fast precise point positioning (Fast-PPP) and its potential application to the Galileo HAS. The aim of this contribution is to present some recent upgrades to the Fast-PPP model, with the emphasis on the model geometry and the data used. The results show the benefits of integer ambiguity resolution to obtain unambiguous carrier phase measurements as input to compute the Fast-PPP model. Seven permanent stations are used to assess the errors of the Fast-PPP ionospheric corrections, with baseline distances ranging from 100 to 1000 km from the reference receivers used to compute the Fast-PPP corrections. The 99% of the GPS and Galileo errors in well-sounded areas and in mid-latitude stations are below one total electron content unit. In addition, large errors are bounded by the error prediction of the Fast-PPP model, in the form of the variance of the estimation of the ionospheric corrections. Therefore, we conclude that Fast-PPP is able to provide ionospheric corrections with the required ionospheric accuracy, and realistic confidence bounds, for the Galileo HAS.

Dual-Rate Extended Kalman Filter Based Path-Following Motion Control for an Unmanned Ground Vehicle: Realistic Simulation.

In this paper, a two-wheel drive unmanned ground vehicle (UGV) path-following motion control is proposed. The UGV is equipped with encoders to sense angular velocities and a beacon system which provides position and orientation data. Whereas velocities can be sampled at a fast rate, position and orientation can only be sensed at a slower rate. Designing a dynamic controller at this slower rate implies not reaching the desired control requirements, and hence, the UGV is not able to follow the predefined path. The use of dual-rate extended Kalman filtering techniques enables the estimation of the fast-rate non-available position and orientation measurements. As a result, a fast-rate dynamic controller can be designed, which is provided with the fast-rate estimates to generate the control signal. The fast-rate controller is able to achieve a satisfactory path following, outperforming the slow-rate counterpart. Additionally, the dual-rate extended Kalman filter (DREKF) is fit for dealing with non-linear dynamics of the vehicle and possible Gaussian-like modeling and measurement uncertainties. A Simscape Multibody™ (Matlab®/Simulink) model has been developed for a realistic simulation, considering the contact forces between the wheels and the ground, not included in the kinematic and dynamic UGV representation. Non-linear behavior of the motors and limited resolution of the encoders have also been included in the model for a more accurate simulation of the real vehicle. The simulation model has been experimentally validated from the real process. Simulation results reveal the benefits of the control solution.

Comparative Analysis of Non-Full and Full Endoscopic Spine Technique via Interlaminar Approach for the Treatment of Degenerative Lumbar Spinal Stenosis: A Retrospective, Single Institute, Propensity Score-Matched Study.

Retrospective study. To compare the clinical efficacy of posterior lumbar laminectomy decompression under full endoscopic technique (Endo-LOVE) and percutaneous endoscopic medial foraminal decompression (PE-MFD) in the treatment of degenerative lumbar spinal stenosis (DLSS). Between April 2017 and April 2018, 96 patients with DLSS underwent Endo-LOVE or PE-MFD, including 58 with Endo-LOVE and 38 with PE-MFD. After propensity score matching (PSM), patient characteristics, operation time, intraoperative fluoroscopy times, postoperative bedridden time, hospital stay and postoperative complications were recorded and compared. The clinical efficacy was evaluated according to Oswestry disability index (ODI), visual analogue scale (VAS), lumbar disease JOA and modified MacNab criteria. A total of 96 patients with DLSS were included in the study. After PSM, the 2 groups were comparable in patient demographic and baseline characteristics. The operation time and intraoperative fluoroscopy times in PE-MFD group were significantly more than those in Endo-LOVE group (P < .05). The operation time in PE-MFD group was significantly less than that in Endo-LOVE group (P < .05).The intraoperative fluoroscopy times in PE-MFD group were significantly more than that in Endo-LOVE group (P < .05). The ODI, VAS and lumbar disease JOA in the 2 groups were significantly improved comparing with those before operation (P < .05). According to the modified MacNab criteria, the excellent and good rates of the 2 groups were 93.5% in Endo-LOVE group and 87.1% in PE-MFD group (P > .05). Endo-LOVE and PE-MFD technique can both effectively treat DLSS, and the short-term follow-up results are positive. Endo-LOVE technique has the advantages of fast puncture positioning, less radiation exposure and wider indications. However, PE-MFD needs more radiation exposure and has the possibility of incomplete decompression for complex multiplanar spinal stenosis.

A Novel Method for Fast Positioning of Non-Standardized Ground Control Points in Drone Images

Positioning the pixels of ground control points (GCPs) in drone images is an issue of great concern in the field of drone photogrammetry. The current mainstream automatic approaches are based on standardized markers, such as circular coded targets and point coded targets. There is no denying that introducing standardized markers improves the efficiency of positioning GCP pixels. However, the low flexibility leads to some drawbacks, such as the heavy logistical input in placing and maintaining GCP markers. Especially as drone photogrammetry steps into the era of large scenes, the logistical input in maintaining GCP markers becomes much more costly. This paper proposes a novel positioning method applicable for non-standardized GCPs. Firstly, regions of interest (ROIs) are extracted from drone images with stereovision technologies. Secondly, the quality of ROIs is evaluated using image entropy, and then the outliers are filtered by an adjusted boxplot. Thirdly, pixels of interest are searched with a corner detector, and the precise imagery coordinates are obtained by subpixel optimization. Finally, the verification was carried out in an urban scene, and the results show that this method has good applicability to the GCPs on road traffic signs, and the accuracy rate is over 95%.

Acoustic Simulation for Performance Evaluation of Ultrasonic Ranging Systems

The recent growing interest in indoor positioning applications has paved the way for the development of new and more accurate positioning techniques. The envisioned applications, include people and asset tracking, indoor navigation, as well as other emerging market applications, require fast and precise positioning. To this end, the effectiveness and high accuracy and refresh rate of positioning systems based on ultrasonic signals have been already demonstrated. Typically, positioning is obtained by combining multiple ranging. In this work, it is shown that the performance of a given ultrasonic airborne ranging technique can be thoroughly analyzed using renowned academic acoustic simulation software, originally conceived for the simulation of echographic transducers and systems. Here, in order to show that the acoustic simulation software can be profitably applied to ranging systems in air, an example is provided. Simulations are performed for a typical ultrasonic chirp, from an ultrasound emitter, in a typical office room. The ranging performances are evaluated, including the effects of acoustic diffraction and air frequency dependent absorption, when the signal-to-noise ratio (SNR) decreases from 30 to −20 dB. The ranging error, computed over a point grid in the space, and the ranging cumulative error distribution is shown for different SNR levels. The proposed approach allowed us to estimate a ranging error of about 0.34 mm when the SNR is greater than 0 dB. For SNR levels down to −10 dB, the cumulative error distribution shows an error below 5 mm, while for lower SNR, the error can be unlimited.

A Comparison of Orthometric Heights Calculated from (GPS/Leveling) and (EGM08) Methods Based–GIS

Interest in the study of global gravitational models has increased recently all over the world because it is necessary for height datum transformations. Today the International Center for Global Earth Models (ICGEM) provides the largest collection in the world produced through gravitational data from the gravitational satellite’s missions CHAMP, GRACE, and GOCE … Etc. To allow easy access through the internet with its more intelligent technologies, it is one of the International Gravity Organization’s services. While the Global Positioning System (GPS) has become one of the most preferred technologies in engineering surveying, a major dilemma in GPS survey lies in oval-based elevations. At the same time, orthometric heights are commonly used in the engineering field. Therefore, it is necessary to convert the measured heights by satellites assigned to the elliptical surface into orthometric heights and supported to the geoid surface (mean sea level) through an accurate geodetic model. The differences between orthometric measurement heights from DGPS/leveling data (obtained from 57 points in the study area) are increasingly used by professionals geographical information systems(GIS). However, the local determination of Geoid is necessary for better accuracy of the orthometric height from DGPS. This paper aims to introduce a modern technique for determining elevation, avoiding cumbersome and time-consuming spirit leveling operations. Fast vertical positioning can be obtained using DGPS with geoid models. The Root Mean Square Error (RMSE) is ± 0.19 m with high precision of DGPS derived with EGM08; thus, the more it describes the Earth’s gravitational field in more detail.

Wasserstein Metric-Based Location Spoofing Attack Detection in WiFi Positioning Systems

WiFi positioning systems (WPS) have been introduced as parts of 5G location services (LCS) to provide fast positioning results of user devices in urban areas. However, they are prominently threatened by location spoofing attacks. To end this, we present a Wasserstein metric-based attack detection scheme to counter the location spoofing attacks in the WPS. The Wasserstein metric is used to measure the similarity of each two hotspots by their signal’s frequency offset distribution features. Then, we apply the clustering method to find the fake hotspots which are generated by the same device. When applied with WPS, the proposed method can prevent location spoofing by filtering out the fake hotspots set by attackers. We set up experimental tests by commercial WiFi devices, which show that our method can detect fake devices with 99% accuracy. Finally, the real-world test shows our method can effectively secure the positioning results against location spoofing attacks.

OPTIMAL CONTROL OF AN ACTUATOR OF A ROBOTIC GEARBOX

Problem. Despite the vigorous development of electric vehicles, the task of facilitating the driver to handle with elements of mechanical transmission remains relevant. For this purpose, the automation of mechanical transmission units is performed. For instance, so-called robotic gearboxes are widespread. The principle of operation of such gearboxes is similar to mechanical ones, but special separate actuators carry out the selection and shifting into the desired gear. The design of a robotic gearbox was proposed at the Automobile Department of Kharkiv National Automobile and Highway University. At this gearbox, two DC motors are used as actuators. The efficiency of this gearbox largely depends on the efficiency of the DC motors control system, which should provide smooth but at the same time fast and accurate positioning of their shafts. In previous works, PID controllers were used to controlling the actuator of the gearbox. However, although the PID controller provides satisfactory quality of the control system, it is not an optimal controller. Goal. The goal of this paper is to develop an optimal controller for the actuators of the robotic gearbox mentioned above. Methodology. To meet this goal, it was proposed to use a linear-quadratic controller (LQR). The analysis of the impact on transient processes in the control system of the values of the weighting factors in the quadratic performance criterion is performed. Results. The LQR synthesized provides high speed of response (within of 0.5 s) at the desired gear selecting and more than two times less overshoot compared to the PID regulator. Originality. The regularities in the gearbox drive performance when changing the values of the weighting factors in the performance criterion have been established. An optimal control system for the robotic gearbox actuator has been developed. Practical value. The implementation of the designed controller will increase the efficiency of the gearbox under consideration.

Laser Beam Pointing Stabilization Control through Disturbance Classification

In laser systems, beam pointing usually drifts as a consequence of various disturbances, e.g., inherent drift, airflow, transmission medium variation, mechanical vibration, and elastic deformation. In this paper, we develop a laser beam pointing control system with Fast Steering Mirrors (FSMs) and Position Sensitive Devices (PSDs), which is capable of stabilizing both the position and angle of a laser beam. Specifically, using the ABCD matrix, we analyze the kinematic model governing the relationship between the rotation angles of two FSMs and the four degree-of-freedom (DOF) beam vector. Then, we design a Jacobian matrix feedback controller, which can be conveniently calibrated. Since disturbances vary significantly in terms of inconsistent physical characteristics and temporal patterns, great challenges are imposed to control strategies. In order to improve beam pointing control performance under a variety of disturbances, we propose a data-driven disturbance classification method by using a Recurrent Neural Network (RNN). The trained RNN model can classify the disturbance type in real time, and the corresponding type can be subsequently used to select suitable control parameters. This approach can realize the universality of the beam stabilization pointing system under various disturbances. Experiments on beam pointing control under several typical external disturbances are carried out to verify the effectiveness of the proposed control system.

Analisis Strategi Pemasaran Pada Lembaga Kursus dan Bimbingan Belajar Education Zone

Marketing activities determine the Education Zone Course and Tutoring Institute (E-Zone LKBB) in selling products as the spearhead set by the E-Zone management LKBB and its marketing strategy. In determining the marketing strategy, environmental analysis is critical because it includes analyzing the internal and external environment. The research problem is about the service marketing strategy in the E-Zone LKBB. Therefore the research questions in this research are: 1) What are the strengths and weaknesses in improving LKBB E-Zona services. 2) What are the opportunities and threats in increasing the marketing strategy of LKBB E-Zone services? 3) What are the formulations of marketing strategies in improving marketing LKBB E-Zone services? This study aims to identify the strengths and weaknesses in the LKBB E-Zone as well as the opportunities and threats of the E-Zone LKBB and formulate a marketing strategy for LKBB E-Zone. The unit of analysis in this research is the Education Zone Course and Tutoring Institution. The observation unit is the marketing and sales management and the students who have studied at LKBB E-Zone for approximately six months. The data analysis method used in this study is the SWOT analysis (Strength, Weakness, Opportunity, Threat), which is an analysis that aims to analyze the strengths and weaknesses as well as opportunities and threats. The result shows that the E-Zone LKBB is in the Fast Growth Strategy quadrant position, between Strength (Strength) and opportunity (Opportunity) in the SWOT diagram. LKBB E-Zone has strengths and opportunities that are greater than weaknesses and threats. So that LKBB E-Zone can take full advantage of all the potential strengths and opportunities by using elements of marketing strategies, namely: market segmentation, target market determination, product placement, timing, marketing mix, and its essential 7 P elements, namely: Promotion, Product, Price, Place, People, Physical Evidence, and Process

Gene Position Index Mutation Detection Algorithm Based on Feedback Fast Learning Neural Network.

In the detection of genome variation, the research on the internal correlation of reference genome is deepening; the detection of variation in genome sequence has become the focus of research, and it has also become an effective path to find new genes and new functional proteins. The targeted sequencing sequence is used to sequence the exon region of a specific gene in cancer gene detection, and the sequencing depth is relatively large. Traditional alignment algorithms will lose some sequences, which will lead to inaccurate mutation detection. This paper proposes a mutation detection algorithm based on feedback fast learning neural network position index. By establishing a position index relationship for ACGT in the DNA sequence, the subsequence is decomposed into the position relationship of different subsequences corresponding to the main sequence. The positional relationship of the subsequence in the main sequence is determined by the positional relationship. Analyzing SNP and InDel mutations, even structural mutations, through the position correlation of sequences has the advantages of high precision and easy implementation by personal computers. The feedback fast learning neural network is used to verify whether there is a linear relationship between two or more positions. Experimental results show that the mutation points detected by position index are more than those detected by Bcftools, Freebye, Vanscan2, and Gatk.

Fast position tracking control of PMSM under high frequency and variable load

Fast position tracking control of PMSM under high frequency and variable load

Fast position tracking control of PMSM under high frequency and variable load

Based on the force and deflection characteristics of the rudder of supercavitating vehicle, this paper presents a motor control problem: 'Fast position Tracking control of PMSM Under High Frequency and variable Load' (simplified as 'FTUHFL'). However, 'Traditional PID' (simplified as 'TPID') position tracker cannot solve the 'FTUHFL' problem very well, its position tracking effect is poor. In order to solve the 'FTUHFL' problem and improve the position tracking effect of PMSM, this paper, based on the 'TPID' position tracker, proposes the 'Traditional PID + Speed Fuzzy Feedforward Compensation + Current Feedforward Compensation' (simplified as 'TPID + SFFC + CFC') position tracker. Firstly, the design method of 'SFFC' and 'CFC' feedforward controllers is given. Then theoretical analysis shows that the stability will not be changed after introducing 'SFFC' and 'CFC' on the basis of 'TPID'. Finally, the effectiveness of the proposed 'TPID + SFFC + CFC' position tracker in solving the 'FTUHFL' problem is further verified by simulation experiments. Compared with 'TPID', 'TPID + SFFC + CFC' position tracker has better response speed, position tracking accuracy and anti-load-disturbance performance.

Load Adaptive PMSM Drive System Based on an Improved ADRC for Manipulator Joint

High-speed and high-precision position servo system of permanent magnet synchronous motor (PMSM) is the key part of the research and development of the manipulator’s joint. The active disturbance rejection control (ADRC) is one of the commonly used methods in the position servo system, which has the advantages of fast speed and easy physical realization. However, the existing ADRC mostly adopts the three-loop structure of position-speed-current, which has some problems such as slow positioning response, poor positioning accuracy, and poor load adaptability caused by difficult parameter tuning. Therefore, a new load adaptive two-loop drive system based on an improved position-speed integrated ADRC with a parameter fuzzy self-tuning method is proposed. In order to verify the effectiveness of the scheme, a test platform for a Selective Compliance Assembly Robot Arm (SCARA) is established. The results show that the drive system designed by the proposed method has high positioning accuracy, fast positioning response, and adaptability to load changes.

Factor-Graph-Aided Three-Dimensional Faster Cooperative Positioning Algorithm

With the development of smart cities and 5G applications, there is an increasingly urgent need for cooperative positioning among all kinds of intelligent terminals. Existing cooperative positioning technology is primarily designed for two-dimensional positions, and the computing speed and positioning accuracy cannot meet the needs of smart cities. To solve these problems, this paper proposes a factor-graph-aided three-dimensional faster cooperative positioning algorithm (FG-3DCP) that combines a factor graph and sum product theory to establish a cooperative localization model with many nodes. To reduce computational complexity and describe fast positioning, the parameter independence of the factor graph is used, and the positioning data of each node coordinate axis are calculated independently. Then, the positioning result is obtained by fusion, and the computing speed is markedly improved. The proposed algorithm was simulated and analyzed in terms of ranging error, position ambiguity, network topology and the number of nodes. When the proposed algorithm was compared to the existing non-Bayesian estimation cooperative position methods, the position performance improved more than 20%, and the convergence rate was the fastest in the 3D environment.

Synthetic Hybrid-Integral-Threshold Logic-Based Position Fault Diagnosis Scheme for SRM Drives

Reliable rotor position measurement is quite necessary for ensuring accurate commutation control in many kinds of motor drives, such as switched reluctance motor (SRM) and brushless dc motor (BLDC). Traditionally, the Hall sensors and photoelectric switch sensors are widely used in most of these low-cost motor drive systems. In these systems, the rotor position needs to be decoded from the discrete voltage pulses measured by the sensors. Thus, to develop an online position pulse signal fault diagnosis scheme with fast fault-monitoring capability is quite vital for avoiding the abnormal driving control and improving the overall system reliability. In this article, a position pulse signal fault diagnosis scheme based on synthetic hybrid-integral-threshold logic is proposed for SRM drives. In this method, the complementary position pulse signals of each sensor are used as the independent reference signals. By applying special integral calculations on each reference signals and capturing their rising and falling edges, the position pulse fault cases like high-level and low-level faults can be diagnosed immediately with the synthetic thresholds’ comparison logic, respectively. To verify the validity of the proposed method, a 1-kW 12/8 structure SRM prototype with three independent Hall sensors installed is used as a test machine. The experimental results show that this method can diagnose the position fault of each position sensor independently and ensure very fast position fault detection even under dynamic operations with speed transients. Furthermore, the method can be implemented without additional hardware and complex computation, which is quite suitable for constructing a reliable position measurement module to assist the rotor position sensors.

Fast and Accurate Hop-based Positioning based on Anchor-skeleton for Anisotropic Networks

Background: The hop-based positioning method is a straightforward, low-cost, and feasible positioning method. Methods: Most previous hop-based algorithms assume that the network is isotropic and uniformly distributed, which often does not reflect real-world conditions. In practice, the network may be anisotropic, which makes the hop count between nodes may not match the real distance well. Results: As a result of this issue for hop-based positioning methods, in this paper, we propose a novel scheme that builds a skeleton model between anchor nodes to represent the anisotropy of a network. During the process of building the skeleton model, we use the corrected Akaike's Information Criterion (AICc), which can assist in the construction of a reliable and high accuracy skeleton model. With the help of the skeleton model with AICc, an unknown node can get a more accurate and reliable estimated position. Conclusion: The results of both theoretical analysis and experimental simulation show that the optimal hop-distance conversion model can be achieved, and compared to other similar algorithms, the proposed algorithm can obtain the position estimation result in a fast and accurate manner.

LMI based antiswing adaptive controller for uncertain overhead cranes

This paper proposes an adaptive anti-sway controller for uncertain overhead cranes. The state-space model of the 2D overhead crane with the system parameter uncertainties is shown firstly. Next, the adaptive controller which can adapt with the system uncertainties and input disturbances is established. The proposed controller has ability to move the trolley to the destination in short time and with small oscillation of the load despite the effect of the uncertainties and disturbances. Moreover, the controller has simple structure so it is easy to execute. Also, the stability of the closed-loop system is analytically proven. The proposed algorithm is verified by using Matlab/Simulink simulation tool. The simulation results show that the presented controller gives better performances (i.e., fast transient response, position tracking, and low swing angle) than the state feedback controller when there exist system parameter variations as well as input disturbances.

A new method to improve the real-time performance of aero-engine component level model

Abstract In order to improve the real-time performance of aero-engine component-level models, an automatic fast positioning interpolation method is proposed. Based on the maximum parameter slope, this method can automatically determine the interpolation cut in point, change the disadvantage of low efficiency of traditional sequential interpolation from the starting point, effectively reduce the interpolation interval, thus greatly improving the efficiency of interpolation. The method is applied to the calculation of gas thermodynamic parameters and the interpolation of the characteristic of rotating parts ,so as to ameliorate the real-time performance of the single-stage flow path calculation of the component-level model. Simulation results show that, compared with the traditional method, the method proposed in this paper improves the fan characteristic calculation efficiency by 47.5%, reduces the time of single complete flow calculation by 74.3% when the dynamic and steady-state accuracy changes are less than 0.4%, which greatly improves the real-time performance of the component-level model.

A new method to improve the real-time performance of aero-engine component level model

Abstract In order to improve the real-time performance of aero-engine component-level models, an automatic fast positioning interpolation method is proposed. Based on the maximum parameter slope, this method can automatically determine the interpolation cut in point, change the disadvantage of low efficiency of traditional sequential interpolation from the starting point, effectively reduce the interpolation interval, thus greatly improving the efficiency of interpolation. The method is applied to the calculation of gas thermodynamic parameters and the interpolation of the characteristic of rotating parts ,so as to ameliorate the real-time performance of the single-stage flow path calculation of the component-level model. Simulation results show that, compared with the traditional method, the method proposed in this paper improves the fan characteristic calculation efficiency by 47.5%, reduces the time of single complete flow calculation by 74.3% when the dynamic and steady-state accuracy changes are less than 0.4%, which greatly improves the real-time performance of the component-level model.