Improve Calibration Accuracy Research Articles

Polarimetric SAR Calibration and Residual Error Estimation When Corner Reflectors Are Unavailable

In this article, we propose a polarimetric calibration (PolCal) algorithm to estimate the system crosstalk, cross-polarization (x-pol), and co-polarization (co-pol) channel imbalance (CI) when ground corner reflectors (CRs) are unavailable. The current PolCal process requires at least one trihedral CR to determine the co-pol CI. However, the deployment of ground CRs is costly and may even be impossible in some areas. To calibrate a polarimetric image without CRs, our proposed method automatically extracts the volume-dominated and Bragg-like pixels as a reference to estimate the crosstalk, x-pol, and co-pol CI values. Then, a first-order polynomial model is exploited to fit the co-pol CI to further improve calibration accuracy. In the experimental section, we demonstrate the effectiveness of our proposed method with data from two of China’s newly developed very high-resolution systems. The experiments confirmed that the proposed workflow can be considered as a feasible calibration scheme when the ground deployment of CRs is impossible, and it is also an effective analysis tool for the assessment of calibrated products.

Stereo calibration of binocular ultra-wide angle long-wave infrared camera based on an equivalent small field of view camera

ABSTRACTIn this paper, a stereo calibration method for binocular ultra-wide angle long-wave infrared camera is proposed on the basis of an equivalent small field of view camera. Extrinsic parameters are calibrated through the corrected images from the left and right cameras. They can be viewed as images taken by a small field of view camera. The calibration procedure consists of three steps: monocular calibration, distortion correction and extrinsic parameters calibration. In order to evaluate the accuracy of the method, stereo vision of the camera is modelled and a 3D reconstruction approach is presented. A series of experiments, including intrinsic parameters, extrinsic parameters and 3D reconstruction, are conducted to validate the proposed method. The results show that the baseline length error decreases to 0.67%, and the relative error for the 3D reconstruction of corners is smaller than 8.11%. In contrast to the common stereo calibration method, it improves calibration accuracy.

Calibration method of Risley-prism imaging System

In this paper, a Risley-prism imaging system is proposed, which incorporates a camera and two coaxial Risley prisms to capture various scenes, namely images captured by equivalent cameras. An equivalent camera calibration method is established to obtain the extrinsic parameters of the equivalent cameras from rectified images captured by the system. To improve calibration accuracy, a geometric method is applied to rectify the degraded images over the whole scanning area. Such opto-electronmechanical configuration makes possible an agile and compact imaging system suitable for boresight adjustment. Experiments that apply imaging system located in different positions are conducted to validate the proposed method, and results are compared to verify its efficiency and accuracy.

Complete relative pose error model for robot calibration

Purpose This paper aims to present a complete relative pose error model for robot calibration, considering both the relative distance error and the relative rotation error of the robot end-effector, which can improve calibration accuracy. Design/methodology/approach In this paper, the relative distance error model and the relative rotation error model of robot calibration are derived by ignoring high-order nonlinear errors, and the two models form into a complete relative pose error model. Besides, mathematical expectation of the nonlinear errors is calculated, indicating that they have little influence on calibration accuracy. Findings Comparative experiments have indicated that the proposed complete relative pose error model does better in robot calibration than only the distance error model. Originality/value The main contribution of this paper lies in the derivation of the relative rotation error model, which helps to form a complete relative pose error model for calibration. The proposed method improves calibration accuracy, with avoiding identifying the transformation matrix between the measurement system frame and the robot base frame.

Subtleties of extrinsic calibration of cameras with non-overlapping fields of view

Abstract The calibration of the relative pose between rigidly connected cameras with non-overlapping fields of view (FOV) is a prerequisite for many applications. In this paper, the subtleties of the experimental realization of such calibration optimization methods like in (Z. Liu, et al., Measurement Science and Technology, 2011, Z. Li, V. Willert, Intelligent Transportation Systems (ITSC), 2018) are presented. Two strategies that could be adapted to certain optimization processes to find better local minima are evaluated. The first strategy is a careful measurement acquisition of pose pairs for solving the calibration problem, which improves the accuracy of the initial value for the following non-linear refinement. The second strategy is the introduction of a quality measure for the image data used for the calibration, which is based on the projection size of the known planar calibration patterns on the image. We show that introducing an additional weighting to the optimization objective chosen as a function of that quality measure improves calibration accuracy and increases robustness against noise. The above strategies are integrated into different setups and their improvement is demonstrated both in simulation and real-world experiment.

Improving metacognition: A comparison of interventions

SummaryAccurate knowledge monitoring is critical to the learning process, as it allows one to regulate studying and test preparation. Thus, a number of investigations have attempted to improve metacognition in the classroom, with the ultimate goal of improving student exam performance. However, such interventions have had inconsistent success using varying paradigms. We compared the effectiveness of five interventions aimed at improving prediction accuracy in a laboratory environment: review, salient feedback, motivation warning lecture, incentives, and reflection. Only the salient feedback and the motivation warning lecture interventions significantly improved participants' prediction accuracy from test 1 to test 2. Review, incentives, and reflection did not improve predictive or postdictive calibration. Well‐timed salient feedback and a lecture warning students not to be biased by desired grades were effective methods of improving calibration accuracy. Results offer effective interventions to improve metacognition that could be used in a classroom setting.

Learning to calibrate: Providing standards to improve calibration accuracy for different performance levels

SummaryThis experimental study explores whether feedback in the form of standards helps students in giving more accurate performance estimates not only on current tasks but also on new, similar tasks and whether performance level influences the effect of standards. We provided 122 first‐year psychology students with seven texts that contained key terms. After reading each text, participants recalled the correct definitions of the key terms and estimated the quality of their recall. Half of the participants subsequently received standards and again estimated their own performance. Results showed that providing standards led to better calibration accuracy, both on current tasks and on new, similar tasks, when standards were not available yet. Furthermore, with or without standards, high performers calibrated better than low performers. However, results showed that especially low performers' calibration accuracy benefitted from receiving standards.

Improving eye-tracking calibration accuracy using symbolic regression.

Eye tracking systems have recently experienced a diversity of novel calibration procedures, including smooth pursuit and vestibulo-ocular reflex based calibrations. These approaches allowed collecting more data compared to the standard 9-point calibration. However, the computation of the mapping function which provides planar gaze positions from pupil features given as input is mostly based on polynomial regressions, and little work has investigated alternative approaches. This paper fills this gap by providing a new calibration computation method based on symbolic regression. Instead of making prior assumptions on the polynomial transfer function between input and output records, symbolic regression seeks an optimal model among different types of functions and their combinations. This approach offers an interesting perspective in terms of flexibility and accuracy. Therefore, we designed two experiments in which we collected ground truth data to compare vestibulo-ocular and smooth pursuit calibrations based on symbolic regression, both using a marker or a finger as a target, resulting in four different calibrations. As a result, we improved calibration accuracy by more than 30%, with reasonable extra computation time.

Performance of the Acute Physiology and Chronic Health Evaluation II (APACHE II) in the prediction of hospital mortality in a mixed ICU in Singapore

Background: The Acute Physiology and Chronic Health Evaluation II (APACHE II) is used to quantify disease severity and hospital mortality risk in critically ill patients. It is widely used in intensive care units (ICUs) in Singapore, but its prognostic validity remains questionable as it has not been thoroughly assessed by established statistical methods. Objectives: This study aimed to: (a) evaluate the discrimination and calibration accuracy of the APACHE II in the prediction of hospital mortality in a mixed ICU, and (b) customise the APACHE II in an effort to maximise its prognostic performance. Methods: A prospective cohort study was conducted and all adult patients with >24 h of ICU admission in a tertiary care institution in Singapore were included. The outcome measure was hospital mortality, and all patients were followed-up until hospital discharge or death for up to one year after ICU admission. Results: There were 503 patients, and their mean (SD) age and APACHE II score were 61.2 (15.8) years and 24.5 (8.2), respectively. Hospital mortality was 31%, and no patients were lost to follow-up. The APACHE II has good discrimination (receiver operating characteristic: 0.76) but poor calibration (Hosmer–Lemeshow C test: <0.001). Customisation did not significantly improve calibration accuracy. Conclusions: The APACHE II and its customised version should not be used in the local setting as they both have poor calibration. There is an urgent need for larger studies to perform second-level customisation or to develop a new prognostic model tailored to the Singapore critical care setting.

On-line calibration and uncertainties evaluation of spherical joint positions on large aircraft component for zero-clearance posture alignment

Abstract With the improvement of performance requirements for modern aircraft, such as speed and leak tightness, the posture alignment of large components without clearance is now extremely required in the aircraft industry. Nevertheless, the inherent errors of both the components themselves and the posture alignment system lead to high risk of collision during the inserting stage, among which the positional errors of spherical joints that connecting the large component to the numerical controlled locators are identified as the primary error source by existing studies. In this paper, a novel method for on-line correction and uncertainties evaluation of the positions of spherical joint centers (SJCs) is presented. Firstly, the rough positions of SJCs are identified based on the nominal model, and the finite element analysis (FEA) method is applied to preliminarily compensate the self-weight deformation of the component. Secondly, the on-line correction model of SJCs is further established, majorly on the basis of the displacements of locators and the relative postures between the initial posture and the new posture after each motion. Thirdly, to improve the correction accuracy, a new relative posture evaluation model considering the anisotropic measurement uncertainties of key points is suggested and solved by particle swarm optimization, and the correction uncertainties are then analyzed using Monte Carlo simulation. According to the numerical experiments, the proposed relative posture evaluation method has demonstrated more robustness evaluation results than the conventional approaches, and also leads to lower correction uncertainties of SJCs. Moreover, since the relative posture evaluation is a common problem in robot calibration, it also provides a promising alternative or supplement for the conventional optimal posture selection method to improve calibration accuracy. The practical application for a wing to fuselage assembly has verified the effectiveness of the correction method, in which the largest positional error of SJCs has decreased from about 14.2 mm to less than 0.4 mm after correction, and the displacement calculation error has been accordingly reduced from 0.1 mm to smaller than 0.01 mm. Therefore, the security of posture adjustment in confined clearance has been largely enhanced.

Improving calibration over texts by providing standards both with and without idea-units

ABSTRACTThis study aims at improving calibration accuracy, which is the match between estimated performance and actual performance. In our experiment, one hundred and twenty-seven university students read texts and learned definitions. The students recalled these definitions during a test and made performance judgements. After recalling their definitions half of the students received full-definition standards, stating what the correct definition should have been. The other half of the students received idea-unit standards: The correct definition was parsed into units that had to be present. Providing standards improved calibration accuracy not only on current texts, but also on new, subsequent texts. Especially the calibration of low performing students benefitted from receiving both idea-unit and full-definition standards. Furthermore, over multiple texts, students who received idea-unit standards benefitted more than students receiving full-definition standards. This study is among the first to show the effect of standards on calibration on new texts and underscores the importance of self-testing.

Calibration of focusing lens artifacts in a dual rotating-compensator Mueller matrix ellipsometer.

A focusing lens consisting of two or more elements is widely used in ellipsometers for spatial resolution. In a typical ellipsometer layout, a lens is placed before the sample to focus light emerging to the sample, and another after the sample to collect the scattered light from the sample. Accurately calibrating the artifacts of the focusing lens is of great importance. In this paper, a method to improve calibration accuracy is proposed. A general analytical model is deduced to describe the artifacts of the focusing lens. This model can be applied to a system model of a dual rotating-compensator Mueller matrix ellipsometer. By adding a uniaxial crystal to calibration samples, with its optical axis neither parallel nor perpendicular to the incident plane, we can better separate artifacts from the lens before and after the sample. The system model also includes depolarization effects due to a finite numerical aperture (NA) that is related to the focusing lens. Similar effects due to the finite spectral bandwidth are also considered. Our simulation's results have validated the proposed method.

Strategies for virtual in-situ sensor calibration in building energy systems

Virtual in-situ sensor calibration (VIC), using Bayesian MCMC with system models, can be applied to large-scale building sensor networks in order to calibrate multiple working sensors including virtual and physical sensors. Using the calibration strategies herein, VIC methods work to overcome various systematic errors (from simple to troublesome) that cannot otherwise be handled by a conventional calibration. Thus, it is important to understand and evaluate the VIC strategies in a whole system with various error conditions to ensure reliable performance of VIC in the operational stage. This study applied individual calibration strategies to a whole building system (a LiBr–H2O refrigeration system), and their effectiveness and limitations in solving the VIC problem were evaluated for the calibration of each type of working sensor under the various error conditions that cause negative effects. The combined strategies are also suggested to improve calibration accuracy by overcoming the individual limitations. This paper (1) explains how to formulate the individual and combined VIC strategies with Bayesian MCMC, (2) shows their capability to handle negative effects and limitations, and (3) demonstrates how combined strategies surmount the individual limitations for a high accuracy in various error conditions.

Data multiplexing in radio interferometric calibration

New and upcoming radio interferometers will produce unprecedented amounts of data that demand extremely powerful computers for processing. This is a limiting factor due to the large computational power and energy costs involved. Such limitations restrict several key data processing steps in radio interferometry. One such step is calibration where systematic errors in the data are determined and corrected. Accurate calibration is an essential component in reaching many scientific goals in radio astronomy and the use of consensus optimization that exploits the continuity of systematic errors across frequency significantly improves calibration accuracy. In order to reach full consensus, data at all frequencies need to be calibrated simultaneously. In the SKA regime, this can become intractable if the available compute agents do not have the resources to process data from all frequency channels simultaneously. In this paper, we propose a multiplexing scheme that is based on the alternating direction method of multipliers (ADMM) with cyclic updates. With this scheme, it is possible to simultaneously calibrate the full dataset using far fewer compute agents than the number of frequencies at which data are available. We give simulation results to show the feasibility of the proposed multiplexing scheme in simultaneously calibrating a full dataset when a limited number of compute agents are available.

Design of 0.35-ps RMS Jitter 4.4–5.6-GHz Frequency Synthesizer with Adaptive Frequency Calibration Using 55-nm CMOS Technology

This paper demonstrates the design and implementation of a 5-GHz frequency synthesizer using 55-nm complementary metal-oxide semiconductor technology. The proposed synthesizer achieves an ultra-low 0.35-ps jitter with a high-resolution adaptive frequency calibration scheme that automatically chooses frequency-tuning curves and improves calibration accuracy. The proposed synthesizer employs a high-Q LC voltage-controlled oscillator, constant bandwidth, low, and even $$K_{\mathrm{VCO}}$$ technique using thermometer-weighted capacitor calibration, a low-power divider, and a charge-pump (CP) circuit to achieve low jitter. The oscillator comprises a modified digitally controlled capacitor and varactor array, which extend the tuning range and minimize the phase noise. A matched differential CP is adopted to reduce reference spurs and phase-noise performance. The proposed frequency synthesizer achieves an output frequency of 4.4–5.6 GHz with a chip area of $$0.33\hbox { mm}^{2}$$ . The power consumption is 20 mW from a 1.2-V supply at 5 GHz, and the reference spur is −67.99 dBc. The measured root mean-square random jitter and phase noise are 0.35 ps and −110.04 dBc/Hz at 1 MHz, respectively.

Error analysis of the calibration of a dual-rotating-retarder Mueller matrix polarimeter.

We previously developed a Mueller matrix microscope by combining a dual-rotating-retarder device with a commercial microscope, which holds promise for pathologic diagnosis applications. In practical applications, the signals to be measured are sensitive to systematic errors, and the measurement accuracy and the instrument calibration affect the capacity to characterize the data. In conventional calibration, the initial positions of the rotating devices are constrained, causing calibration instability. To improve the calibration, we examine the mathematical model of the calibration process using previous studies, and derive a calibration algorithm with reduced error magnification. Our experimental results show the proposed algorithm improves calibration accuracy, and provides more robust results.

A High-Resolution Foreground Model for the MWA EoR1 Field: Model and Implications for EoR Power Spectrum Analysis

AbstractThe current generation of experiments aiming to detect the neutral hydrogen signal from the Epoch of Reionisation (EoR) is likely to be limited by systematic effects associated with removing foreground sources from target fields. In this paper, we develop a model for the compact foreground sources in one of the target fields of the MWA’s EoR key science experiment: the ‘EoR1’ field. The model is based on both the MWA’s GLEAM survey and GMRT 150 MHz data from the TGSS survey, the latter providing higher angular resolution and better astrometric accuracy for compact sources than is available from the MWA alone. The model contains 5 049 sources, some of which have complicated morphology in MWA data, Fornax A being the most complex. The higher resolution data show that 13% of sources that appear point-like to the MWA have complicated morphology such as double and quad structure, with a typical separation of 33 arcsec. We derive an analytic expression for the error introduced into the EoR two-dimensional power spectrum due to peeling close double sources as single point sources and show that for the measured source properties, the error in the power spectrum is confined to highk⊥modes that do not affect the overall result for the large-scale cosmological signal of interest. The brightest 10 mis-modelled sources in the field contribute 90% of the power bias in the data, suggesting that it is most critical to improve the models of the brightest sources. With this hybrid model, we reprocess data from the EoR1 field and show a maximum of 8% improved calibration accuracy and a factor of two reduction in residual power ink-space from peeling these sources. Implications for future EoR experiments including the SKA are discussed in relation to the improvements obtained.

A 40-Gb/s 3-tap forward feedback equalizer with DLL-based delay time calibration

This paper presents a 40-Gb/s 3-tap forward feedback equalizer (FFE) incorporating broadband active delay cell, multiplier & summer and a delay-locked loop (DLL). The active delay cell employs capacitive degeneration and negative impedance structures to broaden the bandwidth. The source-degenerated linear transconductor based multiplier & summer circuits are used through appropriate setting of the FFE tap coefficients. The delay time of the delay cells are calibrated by a DLL against process, voltage, and temperature (PVT) variations. For improving calibration accuracy, the phase detector adopting two symmetric XOR gates and the charge pump utilizing current splitting and self-detection compensation techniques are designed. The proposed circuit is fabricated in 130 nm BiCMOS process, which achieves a data rate of 40 Gb/s through 20-inch FR-4 PCB trace and the horizontal and vertical eye openings of 0.55 UI and 150 mV.

Calibration of piezoelectric RL shunts with explicit residual mode correction

Piezoelectric RL (resistive-inductive) shunts are passive resonant devices used for damping of dominant vibration modes of a flexible structure and their efficiency relies on the precise calibration of the shunt components. In the present paper improved calibration accuracy is attained by an extension of the local piezoelectric transducer displacement by two additional terms, representing the flexibility and inertia contributions from the residual vibration modes not directly addressed by the shunt damping. This results in an augmented dynamic model for the targeted resonant vibration mode, in which the residual contributions, represented by two correction factors, modify both the apparent transducer capacitance and the shunt circuit impedance. Explicit expressions for the correction of the shunt circuit inductance and resistance are presented in a form that is generally applicable to calibration formulae derived on the basis of an assumed single-mode structure, where modal interaction has been neglected. A design procedure is devised and subsequently verified by a numerical example, which demonstrates that effective mitigation can be obtained for an arbitrary vibration mode when the residual mode correction is included in the calibration of the RL shunt.

Improving calibration accuracy of a vibration sensor through a closed loop measurement system

A sensor is a transducer whose purpose is to sense (that is, to detect) some characteristic of its environments. It detects events or changes in quantities and provides a corresponding output, generally as an electrical or optical signal. It has been widely used in mechanical engineering, aeronautics and astronautics engineering, industrial control, etc. Sensors play important roles in industries such as manufacturing, where all require the sensor to act as a reliable unit [1], [2]. In practical engineering applications, a sensor is often used for measuring vibrations, including acceleration, velocity, and displacement. It is the primary link in achieving conversion, processing, recording, and storage of information. Therefore, its performance directly influences the reliability and accuracy of the entire system. The calibration for vibration sensors, which need to ascertain sensitivity, frequency response characteristics, amplitude linearity, etc., are required before the measurement is made [3], [4]. Traditionally, an open loop device (in which the excitation signal is adjusted manually and the parameters are recorded manually) is used for sensor calibration. This type of manual calibration generates a large amount of work and active jamming, which results in errors. If a closed loop calibration system can be designed (i.e., the excitation signals are adjusted automatically by devices, and the real time data are sampled and analyzed), it will offer abundant measurement information and analysis methods which can help improve calibration accuracy and efficiency. In this article, we introduce such a closed loop calibration system for vibration sensors.