scholarly journals Real-Time Detection Method for Center and Attitude Precise Positioning of Cross Laser-Pattern

2021 ◽  
Vol 11 (20) ◽  
pp. 9362
Author(s):  
Haopeng Li ◽  
Zurong Qiu ◽  
Haodan Jiang
Keyword(s):  
Real Time ◽  
Water Mist ◽  
Least Square ◽  
Optical Metrology ◽  
Positioning Accuracy ◽  
The Real ◽  
Gaussian Fitting ◽  
Fitting Method ◽  
The Cross ◽  
Better Than

Optical metrology has experienced a fast development in recent years—cross laser-pattern has become a common cooperative measuring marker in optical metrology equipment, such as infrared imaging equipment or visual 3D measurement system. The rapid and accurate extraction of the center point and attitude of the cross-marker image is the first prerequisite to ensure the measurement speed and accuracy. In this paper, a cross laser-pattern is used as a cooperative marker, in view of the high resolution of the cross laser-pattern image in the project and the vulnerability to adverse environmental effects, such as stray light, smoke, water mist and other interference in the environment, resulting in poor contrast, low signal-to-noise ratio (SNR), uneven energy distribution. As a result, a method is proposed to detect the center point and attitude of cross laser-pattern image based on Gaussian fitting and least square fitting. Firstly, the distortion of original image is corrected in real time, the corrected image is smoothed by median filter, and the noise is suppressed while preserving the edge sharpness and detail of the image. In order to adapt to different environments, the maximum inter-class variance method of threshold automatic selection is used to determine the threshold of image segmentation to eliminate the background interference caused by different illumination intensities. To improve the real-time performance of the algorithm, the four cross laser edge pixels are obtained by line search, and then fitted by least square. With the edge lines, the transverse and portrait line of the cross-laser image are separated, then we calculate Gaussian center points of all Gaussian sections of transverse and portrait lines based on Gaussian fitting method, respectively. Based on the traditional line fitting method, the sub-pixel center of the transverse and portrait laser strip images are fitted by removing the Outlying Points, and the center coordinates and attitude information of the cross laser-pattern are calculated by using the center equation of the laser strip, realizing cross laser-pattern center and attitude accurate positioning. The results show that the method is robust, the center positioning accuracy is better than 0.6 pixels, the attitude positioning accuracy is better than ±15” under smoke and water mist environment and the processing speed is better than 0.1 s, which meets the real-time requirements of the project.

scholarly journals A Real-Time Structure of Attitude Algorithm for High Dynamic Bodies

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Xingcheng Li ◽  
Shuangbiao Zhang
Keyword(s):  
Real Time ◽  
Time Structure ◽  
Flow Diagram ◽  
The Real ◽  
Time Problem ◽  
Conventional Structure ◽  
High Dynamic ◽  
Two Stages ◽  
Better Than ◽  
Attitude Matrix

To solve the real-time problem of attitude algorithm for high dynamic bodies, a real-time structure of attitude algorithm is developed by analyzing the conventional structure that has two stages, and a flow diagram of a real-time structure for a Matlab program is provided in detail. During the update of the attitude matrix, the real-time structure saves every element of attitude matrix in minor loop in real time and updates the next attitude matrix based on the previous matrix every subsample time. Thus, the real-time structure avoids lowering updating frequency, though the multisubsample algorithms are used. Simulation and analysis show that the real-time structure of attitude algorithm is better than the conventional structure due to short update time of attitude matrix and small drifting error, and it is more appropriate for high dynamic bodies.

scholarly journals Pedestrian detection based on improved LeNet-5 convolutional neural network

2019 ◽  
Vol 13 ◽  
pp. 174830261987360 ◽  
Author(s):  
Chuan-Wei Zhang ◽  
Meng-Yue Yang ◽  
Hong-Jun Zeng ◽  
Jian-Ping Wen
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Real Time ◽  
Network Model ◽  
Pedestrian Detection ◽  
The Real ◽  
Better Than

In this article, according to the real-time and accuracy requirements of advanced vehicle-assisted driving in pedestrian detection, an improved LeNet-5 convolutional neural network is proposed. Firstly, the structure of LeNet-5 network model is analyzed, and the structure and parameters of the network are improved and optimized on the basis of this network to get a new LeNet network model, and then it is used to detect pedestrians. Finally, the miss rate of the improved LeNet convolutional neural network is found to be 25% by contrast and analysis. The experiment proves that this method is better than SA-Fast R-CNN and classical LeNet-5 CNN algorithm.

Bursts Detection in Water Distribution Networks Based on Real-Time State Simulation

2014 ◽  
Vol 1065-1069 ◽  
pp. 1692-1698
Author(s):  
Hui Zhang ◽  
Ting Lin Huang ◽  
Mei Hua Cao ◽  
Jin Lan Xu
Keyword(s):  
Real Time ◽  
Water Distribution ◽  
Distribution Networks ◽  
Least Square ◽  
Ratio Method ◽  
Detection Accuracy ◽  
The Real ◽  
Pipe Burst ◽  
Fuzzy Similarity ◽  
Similarity Ratio

Based on the improved weighted-least-square model and fuzzy similarity ratio method, a methodology is proposed to detect pipe bursts in real-time. When SCADA data is obtained DFP algorithm is used to get the real network state. Then the real values of burst characteristics are computed. And the hypothetical values assuming each pipe as the accident pipe are calculated for comparison. The fuzzy similarity ratio method is used to judge whether there is a pipe burst. If there is, the hypothetical value that is most similar to the real value is the accidental state and the corresponding assumed break is the burst location. According to the methodology a software system is developed with Delphi 7 for verification. The running results of a designed network show that the methodology is reliable and its detection accuracy is over 45%.

Design and Application of Aeolian Vibration Monitoring System for Overhead Transmission Line

2012 ◽  
Vol 239-240 ◽  
pp. 456-461
Author(s):  
Bu Sheng Tong ◽  
Yu Xiang Lv ◽  
Bei Ge Yang ◽  
Hui Xue ◽  
Shan Zhi
Keyword(s):  
Transmission Line ◽  
Real Time ◽  
Monitoring System ◽  
Theoretical Models ◽  
Correction Method ◽  
Fatigue Tests ◽  
Least Square ◽  
Vibration Monitoring ◽  
The Real ◽  
Aeolian Vibration

Aim at the shortage of traditional Aeolian vibration fatigue tests and theoretical models for transmission line, the Aeolian vibration monitoring system of transmission line based on the ZigBee wireless network was designed. The system transfer real-time field data of meteorological factors, tension of conductor and acceleration of monitoring nodes to background computer. The line vibration curve integrated directly from the acceleration sensor recorded data will present a serious problem of baseline drift. Therefore, based on least-square theory, a new baseline correction method is proposed to eliminate effect on drifts, and then obtain distortion less vibration curve of transmission line by twice integrations. The system running results show that track fitted with monitoring data is in good agreement with the real recorded trajectory. The system can satisfy the needs of the real time monitoring on transmission line site and be well applied to the calculation of conductor fatigue damage.

Real-Time Model Method Research in Ship Pipeline System Leakage Detecting

2011 ◽  
Vol 105-107 ◽  
pp. 685-688 ◽  
Author(s):  
Hong Hao Yin ◽  
Hui Chen ◽  
Zhong Bo Peng
Keyword(s):  
Experimental Data ◽  
Pressure Gradient ◽  
Real Time ◽  
Pipeline System ◽  
Safe Operation ◽  
Time Model ◽  
Positioning Accuracy ◽  
The Real ◽  
Model Method ◽  
The Difference

Leakage of ship pipeline system has become a great hidden danger, which affects safe operation of ship and causes environmental pollution. In order to isolate leaking pipeline safely in emergency conditions, Real-time monitoring of ship pipeline system leakage is very important. In this paper, the real-time models of ship isothermal and thermal pipeline were established with a set of equations which is running synchronized with the actual execution pipeline, and the real-time model method was used to monitor ship pipeline system leakage. If the difference between measured values and calculated values is greater than a certain range, pipeline leakage is identified. The location of leakage is calculated based on pressure gradient. Only pressure, flow and temperature of the first and second end of the pipeline were needed, can this method achieve leakage detecting and locating. According to the analysis and verification from the experimental data, this method has high leakage resolution and positioning accuracy.

scholarly journals An SVM Based Weight Scheme for Improving Kinematic GNSS Positioning Accuracy with Low-Cost GNSS Receiver in Urban Environments

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7265
Author(s):  
Zhitao Lyu ◽  
Yang Gao
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Urban Environments ◽  
Least Square ◽  
Single Frequency ◽  
Line Of Sight ◽  
Support Vector ◽  
Positioning Accuracy ◽  
Gnss Receiver ◽  
Gnss Positioning

High-precision positioning with low-cost global navigation satellite systems (GNSS) in urban environments remains a significant challenge due to the significant multipath effects, non-line-of-sight (NLOS) errors, as well as poor satellite visibility and geometry. A GNSS system is typically implemented with a least-square (LS) or a Kalman-filter (KF) estimator, and a proper weight scheme is vital for achieving reliable navigation solutions. The traditional weight schemes are based on the signal-in-space ranging errors (SISRE), elevation and C/N0 values, which would be less effective in urban environments since the observation quality cannot be fully manifested by those values. In this paper, we propose a new multi-feature support vector machine (SVM) signal classifier-based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The proposed new weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. To validate the performance of the newly proposed weight scheme, we have implemented it into a real-time single-frequency precise point positioning (SFPPP) system. The dynamic vehicle-based tests with a low-cost single-frequency u-blox M8T GNSS receiver demonstrate that the positioning accuracy using the new weight scheme outperforms the traditional C/N0 based weight model by 65.4% and 85.0% in the horizontal and up direction, and most position error spikes at overcrossing and short tunnels can be eliminated by the new weight scheme compared to the traditional method. It also surpasses the built-in satellite-based augmentation systems (SBAS) solutions of the u-blox M8T and is even better than the built-in real-time-kinematic (RTK) solutions of multi-frequency receivers like the u-blox F9P and Trimble BD982.

Low Cost, High Accuracy Positioning In Urban Environments

2006 ◽  
Vol 59 (3) ◽  
pp. 365-379 ◽  
Author(s):  
Chris Hide ◽  
Terry Moore ◽  
Chris Hill ◽  
David Park
Keyword(s):  
Urban Environment ◽  
Real Time ◽  
Low Cost ◽  
High Accuracy ◽  
Urban Environments ◽  
Reference Trajectory ◽  
Differential Gps ◽  
Positioning Accuracy ◽  
Gps Receivers ◽  
Better Than

It is well known that GPS measurements are regularly obstructed in urban environments. Positioning accuracy in such environments is significantly degraded and in many areas, it is not possible to obtain a GPS position fix at all. There are currently two methods that can be used to improve availability in the urban environment. Firstly, GPS receivers can be augmented with dead reckoning sensors such as an INS. Alternatively, High Sensitivity GPS (HSGPS) receivers can be used which are able to acquire and track very weak signals. This paper assesses the performance obtained from a GPS and low cost INS integrated system and a HSGPS receiver in an urban environment in Nottingham, UK. The navigation systems are compared to a high accuracy integrated GPS/INS system which is used to provide a reference trajectory. It is demonstrated that the differential GPS and low cost INS system can provide horizontal positioning accuracy of better than 2·5 m RMS in real-time, and better than 1 m RMS in post-processing, whereas the non-differential HSGPS receiver provides a real-time performance of 5 m RMS. These results were obtained in an environment where, with conventional GPS receivers, a position solution is only available 48·4% of the time. Operational considerations such as initial alignment of the GPS and low cost INS are also discussed when comparing the two systems for urban positioning applications.

scholarly journals Smartphone Positioning and Accuracy Analysis Based on Real-Time Regional Ionospheric Correction Model

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3879
Author(s):  
Qi Liu ◽  
Chengfa Gao ◽  
Zihan Peng ◽  
Ruicheng Zhang ◽  
Rui Shang
Keyword(s):  
Real Time ◽  
Convergence Time ◽  
Electron Content ◽  
Ionospheric Model ◽  
Positioning Accuracy ◽  
Correction Model ◽  
The Real ◽  
Gnss Positioning ◽  
Klobuchar Model ◽  
Regional Ionospheric Model

As one of the main errors that affects Global Navigation Satellite System (GNSS) positioning accuracy, ionospheric delay also affects the improvement of smartphone positioning accuracy. The current ionospheric error correction model used in smartphones has a certain time delay and low accuracy, which is difficult to meet the needs of real-time positioning of smartphones. This article proposes a method to use the real-time regional ionospheric model retrieved from the regional Continuously Operating Reference Stations (CORS) observation data to correct the GNSS positioning error of the smartphone. To verify the accuracy of the model, using the posterior grid as the standard, the electron content error of the regional ionospheric model is less than 5 Total Electron Content Unit (TECU), which is about 50% higher than the Klobuchar model, and to further evaluate the impact of the regional ionosphere model on the real-time positioning accuracy of smartphones, carrier-smoothing pseudorange and single-frequency Precise Point Positioning (PPP) tests were carried out. The results show that the real-time regional ionospheric model can significantly improve the positioning accuracy of smartphones, especially in the elevation direction. Compared with the Klobuchar model, the improvement effect is more than 34%, and the real-time regional ionospheric model also shortens the convergence time of the elevation direction to 1 min. (The convergence condition is that the range of continuous 20 s is less than 0.5 m).

Performance evaluation of real-time tightly-coupled GNSS PPP/MEMS-based inertial integration using an improved robust adaptive Kalman filter

2020 ◽  
Vol 14 (4) ◽  
pp. 413-430
Author(s):  
Abdelsatar Elmezayen ◽  
Ahmed El-Rabbany
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Integrated System ◽  
Adaptive Kalman Filter ◽  
Integration Algorithm ◽  
Positioning Accuracy ◽  
Precise Positioning ◽  
The Real ◽  
Tightly Coupled ◽  
Robust Adaptive

AbstractTypically, the extended Kalman filter (EKF) is used for tightly-coupled (TC) integration of multi-constellation GNSS PPP and micro-electro-mechanical system (MEMS) inertial navigation system (INS) to provide precise positioning, velocity, and attitude solutions for ground vehicles. However, the obtained solution will generally be affected by both of the GNSS measurement outliers and the inaccurate modeling of the system dynamic. In this paper, an improved robust adaptive Kalman filter (IRKF) is adopted and used to overcome the effect of the measurement outliers and dynamic model errors on the obtained integrated solution. A real-time IRKF-based TC GPS+Galileo PPP/MEMS-based INS integration algorithm is developed to provide precise positioning and attitude solutions. The pre-saved real-time orbit and clock products from the Centre National d’Etudes Spatials (CNES) are used to simulate the real-time scenario. The performance of the real-time IRKF-based TC GNSS PPP/INS integrated system is assessed under open sky environment, and both of simulated partial and complete GNSS outages through two ground vehicular field trials. It is shown that the real-time TC GNSS PPP/INS integration through the IRKF achieves centimeter-level positioning accuracy under open sky environments and decimeter-level positioning accuracy under GNSS outages that range from 10 to 60 seconds. In addition, the use of IRKF improves the positioning accuracy and enhances the convergence of the integrated solution in comparison with the EKF. Furthermore, the IRKF-based integrated system achieves attitude accuracy of 0.052°, 0.048°, and 0.165° for pitch, roll, and azimuth angles, respectively. This represents improvement of 44 %, 48 %, and 36 % for the pitch, roll, and azimuth angles, respectively, in comparison with the EKF-based counterpart.

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