scholarly journals Sensor Modeling and Calibration Method Based on Extinction Ratio Error for Camera-Based Polarization Navigation Sensor

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3779
Author(s):  
Haonan Ren ◽  
Jian Yang ◽  
Xin Liu ◽  
Panpan Huang ◽  
Lei Guo
Keyword(s):  
Extinction Ratio ◽  
Calibration Method ◽  
Degree Of Polarization ◽  
Model Parameters ◽  
Calibration Model ◽  
Ratio Error ◽  
Polarization Sensor ◽  
Orthogonal Channels ◽  
Sensor Modeling ◽  
Indoor And Outdoor

The performance of camera-based polarization sensors largely depends on the estimated model parameters obtained through calibration. Limited by manufacturing processes, the low extinction ratio and inconsistency of the polarizer can reduce the measurement accuracy of the sensor. To account for the challenges, one extinction ratio coefficient was introduced into the calibration model to unify the light intensity of two orthogonal channels. Since the introduced extinction ratio coefficient is associated with degree of polarization (DOP), a new calibration method considering both azimuth of polarization (AOP) error and DOP error for the bionic camera-based polarization sensor was proposed to improve the accuracy of the calibration model parameter estimation. To evaluate the performance of the proposed camera-based polarization calibration model using the new calibration method, both indoor and outdoor calibration experiments were carried out. It was found that the new calibration method for the proposed calibration model could achieve desirable performance in terms of stability and robustness of the calculated AOP and DOP values.

The Calibration Method of Three-Axis Magnetometer Based on Genetic Algorithm

2014 ◽  
Vol 722 ◽  
pp. 373-378
Author(s):  
Xue Liang Pang ◽  
Pei Jiang ◽  
Chun Sheng Lin
Keyword(s):  
Genetic Algorithm ◽  
Optimal Parameter ◽  
Calibration Method ◽  
Model Parameters ◽  
Calibration Model ◽  
Optimal Parameter Estimation ◽  
Magnetic Field Magnitude ◽  
Simulation And Experiment ◽  
Poor Individual ◽  
Sensor Errors

Because of the bias, scaling factors and non-orthogonality, it is difficult for the three-axis magnetometer to be used directly to measure the magnetic field magnitude. It is imperative that the magnetometer is properly calibrated for sensor errors. In this paper, we present a method based on Genetic Algorithm that can be used to estimate calibration model parameters. The algorithm put the parameters of the calibration model as the evolutionary population; According to the fitness, the poor individual is eliminated step by step and the optimal individual is obtained after crossing and mutation; The optimal parameter estimation corresponding to optimal individuals is achieved. It is effective for Genetic Algorithm to estimate parameters of calibration model overcoming the correlation between the parameters. The simulation and experiment show that the method based on Genetic Algorithm can converge steadily and can achieve high estimation precision.

scholarly journals Thermal Modeling and Calibration Method in Complex Temperature Field for Single-Axis Rotational Inertial Navigation System

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 384 ◽  
Author(s):  
Zihui Wang ◽  
Xianghong Cheng ◽  
Jingjing Du
Keyword(s):  
Temperature Field ◽  
Inertial Navigation ◽  
Calibration Method ◽  
Measurement Unit ◽  
Calibration Model ◽  
Navigation Systems ◽  
Moving Vehicle ◽  
Temperature Change Rate ◽  
Environment Temperature ◽  
Complex Temperature

Single-axis rotational inertial navigation systems (single-axis RINSs) are widely used in high-accuracy navigation because of their ability to restrain the horizontal axis errors of the inertial measurement unit (IMU). The IMU errors, especially the biases, should be constant during each rotation cycle that is to be modulated and restrained. However, the temperature field, consisting of the environment temperature and the power heating of single-axis RINS, affects the IMU performance and changes the biases over time. To improve the precision of single-axis RINS, the change of IMU biases caused by the temperature should be calibrated accurately. The traditional thermal calibration model consists of the temperature and temperature change rate, which does not reflect the complex temperature field of single-axis RINS. This paper proposed a multiple regression method with a temperature gradient in the model, and in order to describe the complex temperature field thoroughly, a BP neural network method is proposed with consideration of the coupled items of the temperature variables. Experiments show that the proposed methods outperform the traditional calibration method. The navigation accuracy of single-axis RINS can be improved by up to 47.41% in lab conditions and 65.11% in the moving vehicle experiment, respectively.

scholarly journals On-Orbit Geometric Calibration from the Relative Motion of Stars for Geostationary Cameras

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6668
Author(s):  
Linyi Jiang ◽  
Xiaoyan Li ◽  
Liyuan Li ◽  
Lin Yang ◽  
Lan Yang ◽  
...  
Keyword(s):  
Relative Motion ◽  
Calibration Method ◽  
System Structure ◽  
Calibration Model ◽  
Control Points ◽  
Penetration Process ◽  
Geometric Calibration ◽  
Positioning Errors ◽  
Ground Control Points ◽  
Motion Transformation

Affected by the vibrations and thermal shocks during launch and the orbit penetration process, the geometric positioning model of the remote sensing cameras measured on the ground will generate a displacement, affecting the geometric accuracy of imagery and requiring recalibration. Conventional methods adopt the ground control points (GCPs) or stars as references for on-orbit geometric calibration. However, inescapable cloud coverage and discontented extraction algorithms make it extremely difficult to collect sufficient high-precision GCPs for modifying the misalignment of the camera, especially for geostationary satellites. Additionally, the number of the observed stars is very likely to be inadequate for calibrating the relative installations of the camera. In terms of the problems above, we propose a novel on-orbit geometric calibration method using the relative motion of stars for geostationary cameras. First, a geometric calibration model is constructed based on the optical system structure. Then, we analyze the relative motion transformation of the observed stars. The stellar trajectory and the auxiliary ephemeris are used to obtain the corresponding object vector for correcting the associated calibration parameters iteratively. Experimental results evaluated on the data of a geostationary experiment satellite demonstrate that the positioning errors corrected by this proposed method can be within ±2.35 pixels. This approach is able to effectively calibrate the camera and improve the positioning accuracy, which avoids the influence of cloud cover and overcomes the great dependence on the number of the observed stars.

scholarly journals Development of multivariate calibration method for simultaneous determination of nickel, lead and zinc in tap water

2015 ◽  
Vol 18 (2) ◽  
pp. 145-151
Author(s):  
Chau Minh Huynh ◽  
Thu Du Ly ◽  
Thach Thai Pham ◽  
Tran Thi Bao Pham ◽  
Minh Khanh Duong ◽  
...  
Keyword(s):  
Simultaneous Determination ◽  
Absorption Spectra ◽  
Multivariate Calibration ◽  
Tap Water ◽  
Calibration Method ◽  
Calibration Model ◽  
Determination Of Nickel ◽  
Lead And Zinc ◽  
Nickel Lead

Conventional spectrophotometric methods for simultaneous determination of nickel, lead and zinc in forms of complexes with a reagent is not feasible due to the overlap of their absorption spectra. A multivariate calibration method was used to overcome this problem. In this study, the calibration model was constructed based on absorption spectra of 30 mixture standards in the range from 490 to 600 nm. Factors influencing experimental results such as amount of reagents, pH, and color development time were optimized. The standard calibration ranges for determination of nickel, lead and zinc were found at 0.5-5 ppm. The method was applied for determination of these ions in tap water samples at ppm level, with recoveries (and RSD) of nickel, lead and zinc were 103.3 % (3.0 %), 74.9 % (11.5 %) and 104.6 % (4.6 %), respectively.

scholarly journals An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City

2021 ◽  
Author(s):  
Sheng Zhang ◽  
Joan Ponce ◽  
Zhen Zhang ◽  
Guang Lin ◽  
George Karniadakis
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Robustness Analysis ◽  
Data Driven ◽  
Model Parameters ◽  
Calibration Model ◽  
Epidemiological Models ◽  
Analysis Model ◽  
Identifiability Analysis

AbstractEpidemiological models can provide the dynamic evolution of a pandemic but they are based on many assumptions and parameters that have to be adjusted over the time when the pandemic lasts. However, often the available data are not sufficient to identify the model parameters and hence infer the unobserved dynamics. Here, we develop a general framework for building a trustworthy data-driven epidemiological model, consisting of a workflow that integrates data acquisition and event timeline, model development, identifiability analysis, sensitivity analysis, model calibration, model robustness analysis, and forecasting with uncertainties in different scenarios. In particular, we apply this framework to propose a modified susceptible–exposed–infectious–recovered (SEIR) model, including new compartments and model vaccination in order to forecast the transmission dynamics of COVID-19 in New York City (NYC). We find that we can uniquely estimate the model parameters and accurately predict the daily new infection cases, hospitalizations, and deaths, in agreement with the available data from NYC’s government’s website. In addition, we employ the calibrated data-driven model to study the effects of vaccination and timing of reopening indoor dining in NYC.

scholarly journals Prediction of Caffeine Content in Liberica Coffee Green Bean by NIR Spectroscopy Using Kubelka-Munk Model

2020 ◽  
Vol 7 (3) ◽  
pp. 119
Author(s):  
Ei Mon Kyaw ◽  
I Wayan Budiastra ◽  
Sutrisno Sutrisno ◽  
Samsudin Samsudin ◽  
Dheni Mita Mala
Keyword(s):  
Chemical Analysis ◽  
Nir Spectroscopy ◽  
Consumer Preference ◽  
Data Transformation ◽  
Calibration Method ◽  
Partial Least Square ◽  
Green Bean ◽  
Calibration Model ◽  
Second Derivative ◽  
Caffeine Content

<p>Liberica is one of coffee species that is becoming popular and increasingly in demand in present days due to its unique characteristics. Caffeine is one of the important coffee quality parameter which determines the coffee flavor, consumer preference and market price. Caffeine content is usually analyzed by chemical method which is destructive, time consuming, expensive and involving a lot of procedures. NIR Spectroscopy is one of the non-destructive techniques to overcome these disadvantages. This study was conducted at the Department of Mechanical and Biosystem Engineering, IPB University for NIR measurement and the Center of Agro-based Industry (BBIA), Bogor for chemical analysis from August to November 2019. The study aimed to determine the best calibration model for the prediction of caffeine content in Liberica coffee green bean powder. In this study, FT-NIRS in the wavelength of 1000-2500 nm was used for NIR measurement and HPLC tool was used for chemical analysis. Kubelka-Munk (K/S) and Absorbance (Log 1/R) were used as data transformation, whereas Standard Normal Variance (SNV) and Second derivative of Savitzky-Golay (dg2) as data pretreatment. In addition, Partial Least Square (PLS) and Multiple Linear Regression (MLR) were applied for multivariate calibration method. The best calibration model for the prediction of caffeine content of Liberica coffee green bean powder was obtained by the spectral data pretreated with second derivative of Savitzky-Golay (dg2) and Kubelka-Munk data transformation using PLS calibration method with the results of r = 0.90, RPD = 2.24, CV = 2.01%.</p>

A Rapid Field Calibrating Method for MIMU

2011 ◽  
Vol 80-81 ◽  
pp. 1140-1144
Author(s):  
Yu Bao Fan ◽  
Jie Li ◽  
Bo Wang ◽  
Xiao Chun Tian ◽  
Jun Liu
Keyword(s):  
Inertial Measurement Unit ◽  
Operation Time ◽  
Calibration Method ◽  
Least Square ◽  
Measurement Unit ◽  
Calibration Model ◽  
Time Saving ◽  
Inertial Measurement ◽  
Field Calibration ◽  
Calibration Program

When the Micro Inertial Measurement Unit is been placed randomly in the case of stationary, the sum vectors that measured by the inertial devices configured orthogonally along three axis, are constant vectors. In view of the above objective facts, a field calibration method of micro inertial measurement unit was proposed. On the base of the establishment and optimization of calibration model, all parameters to be calibrated can be obtained through the least square by the ellipsoid fitting, with the result of high-precision field calibration for micro inertial measurement unit. Finally, a filed calibration program for micro inertial measurement unit is scheduled reasonably. The experiment results show that the method has such characteristics such as easily-operation, time-saving, higher calibration accuracy, and not depending on the baseline direction and datum offered by precision instruments. Especially, it fits for inertial measurement systems which work short time and ask for high accuracy. In addition, it can also significantly increase the measurement accuracy of micro inertial measurement system in practical application.

Dynamic Calibration for Serial Robotic Manipulators Based on the Zero Position Analysis Method

1989 ◽  
Author(s):  
G. Z. Qian ◽  
K. Kazerounian
Keyword(s):  
Robotic Manipulators ◽  
Calibration Method ◽  
Dynamic Calibration ◽  
Calibration Model ◽  
Kinematic Calibration ◽  
Dynamic Parameters ◽  
Analysis Method ◽  
Kinematic Parameters ◽  
Position Analysis ◽  
Zero Position

Abstract In the continuation of a kinematic calibration method developed in a previous report, a new dynamic calibration model for serial robotic manipulators is presented in this paper. This model is based on the Zero Position Analysis Method. It entails the process of estimating the errors in the robot’s dynamic parameters by assuming that the kinematic parameters are free of errors. The convergence and effectiveness of the model are demonstrated through numerical simulations.

scholarly journals On-Orbit Polarization Calibration for Multichannel Polarimetric Camera

2019 ◽  
Vol 9 (7) ◽  
pp. 1424 ◽  
Author(s):  
Mingxin Liu ◽  
Xin Zhang ◽  
Tao Liu ◽  
Guangwei Shi ◽  
Lingjie Wang ◽  
...  
Keyword(s):  
Linear Polarization ◽  
Calibration Method ◽  
Experimental Results ◽  
Calibration Model ◽  
Radiometric Calibration ◽  
Relative Deviation ◽  
Transmission Process ◽  
Radiation Transmission ◽  
Polarimetric Imaging ◽  
Imaging Detection

In this paper, a new on-orbit polarization calibration method for the multichannel polarimetric camera is presented. A polarization calibration model for the polarimetric camera is proposed by taking analysis of the polarization radiation transmission process. In order to get the polarization parameters in the calibration model, an on-orbit measurement scheme is reported, which uses a solar diffuser and a built-in rotatable linear analyzer. The advantages of this scheme are sharing the same calibration assembly with the radiometric calibration and acquiring sufficient polarization accuracy. The influence of the diffuser for the measurement is analyzed. By using a verification experiment, the proposed method can achieve on-orbit polarization calibration. The experimental results show that the relative deviation for the measured degree of linear polarization is 0.8% at 670 nm, which provides a foundation for the accurate application of polarimetric imaging detection.

Design and Application of an In-Line Measurement System for Polarization Parameters

2013 ◽  
Vol 321-324 ◽  
pp. 447-452
Author(s):  
Zhang Bin Wen ◽  
Mi Zhou ◽  
Zhe Chen ◽  
Yun Han Luo
Keyword(s):  
Measurement System ◽  
High Speed ◽  
Low Cost ◽  
Extinction Ratio ◽  
Polarization State ◽  
Light Polarization ◽  
Polarization Measurement ◽  
Degree Of Polarization ◽  
Stokes Vector ◽  
Line System

An in-line all-fiber measurement system for polarization parameters is designed and fabricated in this paper. This system implements accurate control of polarization state, together with in-line, accurate, and high-speed measurement of Stokes vector. It can measure the light polarization parameters such as States of Polarization (SOP), Degree of Polarization (DOP), Light Polarization Extinction Ratio (LPER), and related losses of polarization. Besides, polarization monitoring and stabilizing can be achieved using this system. Because there is no discrete device concluded, the optical path of this system is completely constituted by optical fiber, which makes the entire system low-cost, with small size and low insertion loss. Keywords: All-fiber, polarization control, polarization measurement, in-line system, Stokes vector

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