A low-cost correction algorithm for transient data errors

Ubiquity ◽  
2006 ◽  
Vol 2006 (August) ◽  
pp. 1-1
Author(s):  
Aiguo Li ◽  
Bingrong Hong
Keyword(s):  
Low Cost ◽  
Correction Algorithm ◽  
Data Errors ◽  
Transient Data

A low-cost correction algorithm for transient data errors

Ubiquity ◽  
2006 ◽  
Vol 2006 (May) ◽  
pp. 2-15 ◽  
Author(s):  
Aiguo Li ◽  
Bingrong Hong
Keyword(s):  
Low Cost ◽  
Correction Algorithm ◽  
Data Errors ◽  
Transient Data

Design and Implementation of Gain-Offset Correction Algorithm Hardware Architecture for Grayscale and Color Images Contrast Enhancement

2016 ◽  
Vol 25 (10) ◽  
pp. 1650120 ◽  
Author(s):  
Uche A. Nnolim
Keyword(s):  
Contrast Enhancement ◽  
High Speed ◽  
Low Cost ◽  
Correction Algorithm ◽  
Design And Implementation ◽  
Image Contrast Enhancement ◽  
Offset Correction ◽  
Time Requirements ◽  
Enhancement Algorithm ◽  
Processing Solution

This paper describes the design and implementation of a novel, high-speed hardware (HW) architecture for the gain-offset correction (GOC) image contrast enhancement algorithm on an FPGA fabric. The design is extremely fast and has been shown to process megapixel image frames at frame rates greatly exceeding real-time requirements. The design is small and compact enough to fit on small FPGAs to form a low-cost image processing solution. The automated nature of the contrast enhancement operation is due to the computation of global image statistics for each image. The architecture does not store any image frames to perform this task, heavily reducing memory requirements.

scholarly journals Developing a Relative Humidity Correction for Low-Cost Sensors Measuring Ambient Particulate Matter

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2790 ◽  
Author(s):  
Andrea Di Antonio ◽  
Olalekan Popoola ◽  
Bin Ouyang ◽  
John Saffell ◽  
Roderic Jones
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Relative Humidity ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Low Cost ◽  
Monitoring Networks ◽  
Ambient Particulate Matter ◽  
Correction Algorithm ◽  
Ambient Conditions

There is increasing concern about the health impacts of ambient Particulate Matter (PM) exposure. Traditional monitoring networks, because of their sparseness, cannot provide sufficient spatial-temporal measurements characteristic of ambient PM. Recent studies have shown portable low-cost devices (e.g., optical particle counters, OPCs) can help address this issue; however, their application under ambient conditions can be affected by high relative humidity (RH) conditions. Here, we show how, by exploiting the measured particle size distribution information rather than PM as has been suggested elsewhere, a correction can be derived which not only significantly improves sensor performance but which also retains fundamental information on particle composition. A particle size distribution–based correction algorithm, founded on κ -Köhler theory, was developed to account for the influence of RH on sensor measurements. The application of the correction algorithm, which assumed physically reasonable κ values, resulted in a significant improvement, with the overestimation of PM measurements reduced from a factor of ~5 before correction to 1.05 after correction. We conclude that a correction based on particle size distribution, rather than PM mass, is required to properly account for RH effects and enable low cost optical PM sensors to provide reliable ambient PM measurements.

Pedestrian navigation system using MEMS sensors for heading drift and altitude error correction

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 270-281 ◽  
Author(s):  
Xiaochun Tian ◽  
Jiabin Chen ◽  
Yongqiang Han ◽  
Jianyu Shang ◽  
Nan Li
Keyword(s):  
Navigation System ◽  
Low Cost ◽  
Three Dimensional ◽  
Step Height ◽  
Reference Trajectory ◽  
Correction Algorithm ◽  
Content Type ◽  
Pedestrian Navigation ◽  
Smoothing Filter ◽  
Zero Velocity

Purpose This study aims to design an optimized algorithm for low-cost pedestrian navigation system (PNS) to correct the heading drift and altitude error, thus achieving high-precise pedestrian location in both two-dimensional (2-D) and three-dimensional (3-D) space. Design/methodology/approach A novel heading correction algorithm based on smoothing filter at the terminal of zero velocity interval (ZVI) is proposed in the paper. This algorithm adopts the magnetic sensor to calculate all the heading angles in the ZVI and then applies a smoothing filter to obtain the optimal heading angle. Furthermore, heading correction is executed at the terminal moment of ZVI. Meanwhile, an altitude correction algorithm based on step height constraint is proposed to suppress the altitude channel divergence of strapdown inertial navigation system by using the step height as the measurement of the Kalman filter. Findings The verification experiments were carried out in 2-D and 3-D space to evaluate the performance of the proposed pedestrian navigation algorithm. The results show that the heading drift and altitude error were well corrected. Meanwhile, the path calculated by the novel algorithm has a higher match degree with the reference trajectory, and the positioning errors of the 2-D and 3-D trajectories are both less than 0.5 per cent. Originality/value Besides zero velocity update, another two problems, namely, heading drift and altitude error in the PNS, are solved, which ensures the high positioning precision of pedestrian in indoor and outdoor environments.

Is Linear Camera Space Manipulation Impervious to Systematic Distortions?

2018 ◽  
Author(s):  
Felipe Martinez ◽  
Adam Mihalko ◽  
Lillian Blum ◽  
Antonio Cardenas ◽  
Davide Piovesan
Keyword(s):  
High Resolution ◽  
Biomedical Applications ◽  
Low Cost ◽  
Systematic Errors ◽  
Calibration Model ◽  
Positional Error ◽  
Positioning Error ◽  
Post Processing ◽  
Correction Algorithm ◽  
Non Gaussian

Raster imaging is a low cost application for the tracing of movements for biomedical applications. While of the shelf cameras can nowadays provide pictures with high resolution, the optics used can generate unwanted distortions. We evaluated the positional error obtained using a set of GoPro® cameras in conjunction with a Linear Camera Space Manipulation (LCSM) calibration model. The positioning error was compared with a post-processing algorithm to compensate for the radial distortion of a fisheye lens. We found that using the correction algorithm, the error is statistically lower, but the decrease is negligible for practical use. This demonstrates the imperviousness of LCSM to systematic errors of non-Gaussian nature.

Towards the Design of Efficient Error Detection Mechanisms for Transient Data Errors

2012 ◽  
Vol 56 (6) ◽  
pp. 674-692 ◽  
Author(s):  
M. Leeke ◽  
A. Jhumka ◽  
S. S. Anand
Keyword(s):  
Error Detection ◽  
Data Errors ◽  
Transient Data ◽  
Detection Mechanisms

scholarly journals Straight Gait Research of a Small Electric Hexapod Robot

2021 ◽  
Vol 11 (8) ◽  
pp. 3714
Author(s):  
Feng Zhang ◽  
Shidong Zhang ◽  
Qian Wang ◽  
Yujie Yang ◽  
Bo Jin
Keyword(s):  
Low Cost ◽  
Duty Factor ◽  
Hexapod Robot ◽  
Correction Algorithm ◽  
Motion Error ◽  
Gait Planning ◽  
Angle Correction ◽  
Hexapod Robots ◽  
Yaw Angle ◽  
And Control

Gait is an important research content of hexapod robots. To better improve the motion performance of hexapod robots, many researchers have adopted some high-cost sensors or complex gait control algorithms. This paper studies the straight gait of a small electric hexapod robot with a low cost, which can be used in daily life. The strategy of “increasing duty factor” is put forward in the gait planning, which aims to reduce foot sliding and attitude fluctuation in robot motion. The straight gaits of the robot include tripod gait, quadrangular gait, and pentagonal gait, which can be described conveniently by discretization and a time sequence diagram. In order to facilitate the user to control the robot to achieve all kinds of motion, an online gait transformation algorithm based on the adjustment of foot positions is proposed. In addition, according to the feedback of the actual attitude information, a yaw angle correction algorithm based on kinematics analysis and PD controller is designed to reduce the motion error of the robot. The experiments show that the designed gait planning scheme and control algorithm are effective, and the robot can achieve the expected motion. The RMSE of the row, pitch, and yaw angle was reduced by 35%, 25%, and 12%, respectively, using the “increasing duty factor” strategy, and the yaw angle was limited in the range −3°~3° using the yaw angle correction algorithm. Finally, the comparison with related works and the limitations are discussed.

scholarly journals High-accuracy current measurement with low-cost shunts by means of dynamic error correction

2016 ◽  
Vol 5 (2) ◽  
pp. 389-400 ◽  
Author(s):  
Patrick Weßkamp ◽  
Joachim Melbert
Keyword(s):  
Measurement Error ◽  
Error Correction ◽  
Low Cost ◽  
Dynamic Error ◽  
Real Life ◽  
Lithium Ion ◽  
Calibration Method ◽  
Correction Algorithm ◽  
Temperature Drift

Abstract. Measurement of electrical current is often performed by using shunt resistors. Thermal effects due to self-heating and ambient temperature variation limit the achievable accuracy, especially if low-cost shunt resistors with increased temperature coefficients are utilized. In this work, a compensation method is presented which takes static and dynamic temperature drift effects into account and provides a significant reduction of measurement error. A thermal model of the shunt resistor setup is derived for this purpose and a suitable calibration method is developed. The correction algorithm is based upon a digital filter bank and is optimized for microcontrollers with low computational complexity. It is implemented in laboratory test equipment for long-term studies on automotive lithium-ion cells. For a 600 A current pulse, it reduces the measurement error from 2 % to less than 0.1 %. Measurements with a real-life testing profile show a reduction of remaining measurement error by 60 %. Statistical results for 100 test systems and long-term drift measurements prove the reliability of the method. The proposed dynamic error correction algorithm therefore allows high measurement accuracy despite the use of low-cost shunt resistors.

scholarly journals A Data Correction Algorithm for Low-Frequency Floating Car Data

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3639 ◽  
Author(s):  
Bijun Li ◽  
Yuan Guo ◽  
Jian Zhou ◽  
Yi Cai
Keyword(s):  
Low Cost ◽  
Low Frequency ◽  
Map Matching ◽  
Correction Algorithm ◽  
Trajectory Data ◽  
Matching Algorithm ◽  
Data Correction ◽  
Floating Car Data ◽  
Attraction Model ◽  
Physical Attraction

The data collected by floating cars is an important source for lane-level map production. Compared with other data sources, this method is a low-cost but challenging way to generate high-accuracy maps. In this paper, we propose a data correction algorithm for low-frequency floating car data. First, we preprocess the trajectory data by an adaptive density optimizing method to remove the noise points with large mistakes. Then, we match the trajectory data with OpenStreetMap (OSM) using an efficient hierarchical map matching algorithm. Lastly, we correct the floating car data by an OSM-based physical attraction model. Experiments are conducted exploiting the data collected by thousands of taxies over one week in Wuhan City, China. The results show that the accuracy of the data is improved and the proposed algorithm is demonstrated to be practical and effective.

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