Calibration Correction Research Articles

Dosimetric commissioning of a high-resolution CMOS 2D detector array for patient-specific QA of single-isocenter multi-target VMAT stereotactic radiosurgery.

Stereotactic radiosurgery (SRS) using the single-isocenter-multiple-target (SIMT) technique by volumetric modulated arc therapy is increasingly popular for treating multiple brain metastases. However, the complex nature of SIMT SRS necessitates rigorous patient-specific quality assurance (PSQA). This study presents a multi-institutional dosimetric commissioning of a high-resolution complementary metal oxide semiconductor (CMOS) 2D detector array, the myQA SRS device for SIMT SRS PSQA. Basic dosimetric properties such as dose-rate, field-size, energy and angular dependencies were characterized for the CMOS detectors. Additionally, gamma index analyses were performed between the measured dose and the films for nine simulated and clinical plans. The results showed that the CMOS detector was dose-rate, field-size, energy and beam-angle dependent. Specific to SIMT SRS, angular dependence on gantry rotations was invariant to couch rotations but was sensitive to off-isocenter distances. With appropriate dose calibration and angular corrections, myQA SRS showed a high dosimetric correlation with films. The average gamma index pass rates were 99.9 ± 0.03% and 99.2 ± 1.1% at 3%/2mm/10%thr(global) and 1mm/1%/10%thr(local) criteria, respectively. The average dose difference between myQA SRS and films was 0.4 ± 1.3%. In conclusion, the CMOS 2D detector array has demonstrated its potential as a reliable tool for PSQA for SIMT SRS. The excellent dosimetric agreement with the films was consistent in multiple institutions, further validating the dosimetric accuracy and reproducibility. It provides a timely alternative to film dosimetry for commissioning and quality assurance.

Infrared non-uniformity correction method based on binocular detection system without blindsight

The output image of an infrared detector often suffers from non-uniformity due to the inhomogeneity of the device material and limitations in the manufacturing process, which can reduce the detector's capability to detect and identify targets. It is therefore necessary to adequately correct the non-uniformity to fully utilize the high temperature sensitivity of the detector. Calibration-based non-uniformity correction technology is one of the earliest and most effective methods of correcting non-uniformity. Typically, a relatively uniform shutter is used to mask the field of view for calibration correction. However, this process interrupts the observation due to the need for masking, severely limiting its use in real-world projects. In order to maintain the performance superiority of the calibration-based method and eliminate the defect of target loss caused by masking, this paper takes the occlusion calibration as the theoretical basis, which consists of dual detectors to form a binocular detection system, and uses one of the occluded calibration auxiliary detector to assist the other occlusion-free primary detector, and takes advantage of the fact that the radiation is the same when observing the same target at the same time to make the correct response based on the steepest gradient descent learning algorithm, which removes the non-uniformity while achieving detail fidelity, no ghosting and continuous output.

Eigen-6c4 Gravity and Alos Palsar Radar Data Integration for Delineating Geological Lineaments in North Ghadames Basin, NW Libya

Introduction The ambiguity regarding the geological interpretation has the potential to be significantly decreased with the use of remote sensing, geophysical data, and the history of geology. Aims The objective of this work is to delineate geological lineaments and faults using EIGEN-6C4 satellite gravity and ALOS PALSAR radar data in the north Ghadames basin, of northwest Libya. Methods The satellite gravity dataset of the study region was used to perform a complete Bouguer anomaly map of the study area to start the gravity interpretation. Then different filters were performed on the gravity dataset, such as the total horizontal gradient (THG), CET grid analysis, 3-dimensional Euler solution (ED), and a tilt derivative (TDR) using the commercial Oasis Montaj programme. The techniques of edge identification (THG, TDR, and also CET grid analysis) are utilised for locating and identifying the boundaries or edges of geological structures that contribute to gravity anomalies. The 3-dimensional Euler solution, in conjunction with the TDR method, is employed to precisely figure out the positions and estimated depths associated with subsurface sources. Radiometric calibration, speckle filtering, and geometric correction were applied to preprocess the ALOS PALSAR L 1.1 image via the Sentinel Application Platform (SNAP) software. For automatic extraction, the PCI Geomatica software's LINE module was applied. Results The gravity data results indicate that the main trends of the identified geological lineaments are oriented in the North-South, East-West, Northwest-Southeast, and North-Northwest to South-Southeast directions. Furthermore, the depths of the sources observed underneath the study region differ from 250 m to 2750 m. The orientation of extracted lineaments from the ALOS PALSAR L1.1 images, specifically the horizontal-horizontal as well as horizontal-vertical polarisation images, predominantly have orientations in the north-south, north-northeast to south-southwest, east-west, north-northwest to south-southeast, and northeast-southwest directions within the study area. Conclusion All these findings of lineaments are associated with the tectonic features of the area. Consequently, identifying these lineaments/faults is important to reduce the ambiguity of geological interpretation and provide more information on the dominant trends for future exploration activities in the study region.

Giant Postflare Loops in Active Regions with an Extremely Strong Coronal Magnetic Field

We report for the first time the detection of thermal free–free emission from post-flare loops at 34 GHz in images from the Nobeyama Radioheliograph. We studied eight loops, seven of which were from regions with an extremely strong coronal magnetic field reported by Fedenev et al. Loop emission was observed in a wide range of wavelength bands, up to soft X-rays, confirming their multitemperature structure and was associated with noise storm emission in metric λ. The comparison of the 17 GHz emission with that at 34 GHz, after a calibration correction of the latter, showed that the emission was optically thin at both frequencies. We describe the structure and evolution of the loops and we computed their density, obtaining values for the top of the loops between 1 and 6 × 1010 cm−3, noticeably varying from one loop to another and in the course of the evolution of the same loop system; these values have only a weak dependence on the assumed temperature, 2 × 106 K in our case, as we are in the optically thin regime. Our density values are above those reported from EUV observations, which go up to about 1010 cm−3. This difference could be due to the fact that different emitting regions are sampled in the two domains and/or due to the more accurate diagnostics in the radio range, which do not suffer from inherent uncertainties arising from abundances and non-LTE excitation/ionization equilibria. We also estimated the magnetic field in the loop tops to be in the range of 10–30 G.

Smart calibration and monitoring: leveraging artificial intelligence to improve MEMS-based inertial sensor calibration

Micro-electro-mechanical systems (MEMS)-based sensors endure complex production processes that inherently include high variance. To meet rigorous client demands (such as sensitivity, offset noise, robustness against vibration, etc.). products must go through comprehensive calibration and testing procedures. All sensors undergo a standardized and sequential calibration process with a predetermined number of steps, even though some may reach the correct calibration value sooner. Moreover, the traditional sequential calibration method faces challenges due to specific operating conditions resulting from manufacturing discrepancies. This not only extends the calibration duration but also introduces rigidity and inefficiency. To tackle the issue of production variances and elongated calibration time and enhance efficiency, we provide a novel quasi-parallelized calibration framework aided by an artificial intelligence (AI) based solution. Our suggested method utilizes a supervised tree-based regression technique and statistical measures to dynamically identify and optimize the appropriate working point for each sensor. The objective is to decrease the total calibration duration while ensuring accuracy. The findings of our investigation show a time reduction of 23.8% for calibration, leading to substantial cost savings in the manufacturing process. In addition, we propose an end-to-end monitoring system to accelerate the incorporation of our framework into production. This not only guarantees the prompt execution of our solution but also enables the identification of process modifications or data irregularities, promoting a more agile and adaptable production process.

Auto recalibration based on dual-mode sensing for robust optical continuous glucose monitoring

Boronic acid based optical continuous glucose monitoring systems (CGMs) hold promise for long-term glucose monitoring. However, these sensors suffer drifts induced inaccuracy and external calibration. One of the reasons is the denature of boronic acid structures and optical reporters. To solve this problem, a dual-mode glucose sensing method with auto-recalibration capabilities is developed using glucose-selective diboronic acid molecule (DBA) and optical reporter alizarin red S (ARS). DBA binds ARS at a 1:2 ratio and produces distinct changes in both the absorbance (Abs) and the fluorescence (FL) spectra of ARS. Through competitive binding with DBA, glucose induces a compensatory shift in both Abs and FL signals. The two signals were demonstrated to be strongly correlated and were combined to build Abs-FL-glucose 3D calibration curves for glucose determination. The mapping relationship of two signals drift closely with both changes of DBA and ARS concentration. By ascertain the right mapping relationship, the two strongly correlated signals can alert undesirable degradation of sensing components, identify the correct calibration curve, and accurately predict glucose concentration without external calibration. The introduction and adoption of the auto-recalibrating dual-mode sensing strategy could constitute a useful development in the pursuit of next generation long-term calibration-free CGM and wearable sensors technologies with superior precision.

Development, validation and long-term evaluation of a liquid chromatography-tandem mass spectrometry method for simultaneous quantification of amiodarone, desethylamiodarone and mexiletine in human plasma and serum

Amiodarone and mexiletine are used for ventricular arrhythmias, for which a combination therapy of both anti-arrhythmic drugs (AADs) is not uncommon. Therapeutic drug monitoring (TDM) can be beneficial for clinical guidance of therapy, especially to correctly identify adverse events. Desethylamiodarone, the active metabolite of amiodarone, accumulates over time and is associated with serious adverse events. Therefore, simultaneous TDM for amiodarone, desethylamiodarone and mexiletine is advantageous in clinical practice. The presented LC-MS/MS method was validated for selectivity, matrix effect, linearity, accuracy, precision, carry-over and stability. The method was continuously evaluated during eight months of clinical use. The method was shown to be linear within the measured range of 0.1 to 10 mg/L for each component. The matrix effect was considered negligible. No interfering responses were found for amiodarone, desethylamiodarone and the isotopic-labeled internal standards. A constant and reproducible within-run contribution of 45.3 %, originating from the system, was identified for mexiletine. The systemic contribution to the peak area of the lowest quantifiable concentration of mexiletine affected the selectivity and carry-over effect measurements. Multiple measurements showed that regression adjusted concentrations were accurate and reproducible, indicating calibration correction was applicable. Sample stability was found to be within limits for all storage conditions and freeze–thaw cycles. Furthermore, long-term method evaluation with external controls resulted in stable measurements with a percentage coefficient of variance between 1.3 % and 6.3 %. The presented practical and reliable method is applicable for clinical TDM and will allow clinical practitioners to guide drug therapy of amiodarone and mexiletine.

Design and verification of a highly accurate in-situ hyperspectral radiometric measurement system (HyperNav)

Hyperspectral optical observations of the Earth’s surface oceans from space offer a means to improve our understanding of ocean biology and biogeochemistry. NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission, which includes a hyperspectral ocean color instrument (OCI), will provide radiometric observations of surface ocean with near continuous spectral resolution across the near UV to NIR range. Maintaining sufficient accuracy over the lifetime of satellite ocean color missions requires a robust program for system vicarious calibration (SVC) and product validation. The system vicarious calibration process combines satellite sensor data with in-situ radiometric/optical measurements to remove potential biases due to the combined errors from both satellite radiometric sensor calibration and atmospheric correction. As such, high accuracy, high-spectral resolution in-situ radiometric measurements are required to provide a principal source of truth for the satellite-derived products. To meet the requirements, a novel in-situ radiometric system, called HyperNav, has been developed, rigorously characterized and field tested. Key attributes of HyperNav are dual upwelling radiance heads coupled to individual spectrometers, spectral resolution of ∼2.2 nm (full width, half-maximum) across 320–900 nm, integrated shutter systems for dark measurements, and integrated tilt and pressure sensors. The HyperNav operational modes include traditional profiling and surface modes, as well as integration with an autonomous profiling float for unattended deployment, offering a new capability for a network of autonomous platforms to support the long-term needs for hyperspectral ocean color remote sensing observations. This paper describes the HyperNav design, in-situ operational modes, and field verification results.

Fine-mapping causal tissues and genes at disease-associated loci.

Heritable diseases often manifest in a highly tissue-specific manner, with different disease loci mediated by genes in distinct tissues or cell types. We propose Tissue-Gene Fine-Mapping (TGFM), a fine-mapping method that infers the posterior probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing GWAS summary statistics (and in-sample LD) and leveraging eQTL data from diverse tissues to build cis-predicted expression models; TGFM also assigns PIPs to causal variants that are not mediated by gene expression in assayed genes and tissues. TGFM accounts for both co-regulation across genes and tissues and LD between SNPs (generalizing existing fine-mapping methods), and incorporates genome-wide estimates of each tissue's contribution to disease as tissue-level priors. TGFM was well-calibrated and moderately well-powered in simulations; unlike previous methods, TGFM was able to attain correct calibration by modeling uncertainty in cis-predicted expression models. We applied TGFM to 45 UK Biobank diseases/traits (average N = 316K) using eQTL data from 38 GTEx tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease/trait, of which 11% were gene-tissue pairs. Implicated gene-tissue pairs were concentrated in known disease-critical tissues, and causal genes were strongly enriched in disease-relevant gene sets. Causal gene-tissue pairs identified by TGFM recapitulated known biology (e.g., TPO-thyroid for Hypothyroidism), but also included biologically plausible novel findings (e.g., SLC20A2-artery aorta for Diastolic blood pressure). Further application of TGFM to single-cell eQTL data from 9 cell types in peripheral blood mononuclear cells (PBMC), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs at PIP > 0.5-primarily for autoimmune disease and blood cell traits, including the biologically plausible example of CD52 in classical monocyte cells for Monocyte count. In conclusion, TGFM is a robust and powerful method for fine-mapping causal tissues and genes at disease-associated loci.

Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg

Abstract. This paper presents an open-access data set of reanalysed radar reflectivities and rainfall rates at sub-kilometre spatial and minute temporal scales. Variability at these scales is a blind spot for both operational rain gauge networks and operational radar networks. In the urban area of Hamburg, precipitation measurements of a single-polarized X-band weather radar operating at high temporal (30 s), range (60 m), and azimuthal sampling (1°) resolutions are made available for a period of more than 8 years. We describe in detail the reanalysis of the raw radar data, outline the radar performance for the years 2013 to 2021, and discuss open issues and limitations of the data set. Several sources of radar-based errors were adjusted gradually, affecting the radar reflectivity and rainfall measurements, e.g. noise, alignment, non-meteorological echoes, radar calibration, and attenuation. The deployment of additional vertically pointing micro rain radars yields drop size distributions at the radar beam height, which effectively reduces errors concerning the radar calibration and attenuation correction and monitors the radar data quality. A statistical evaluation revealed that X-band radar reflectivities and rainfall rates are in very good agreement with the micro rain radar measurements. Moreover, the analyses of rainfall patterns shown for an event and accumulated rainfall of several months prove the quality of the data set. The provided radar reflectivities facilitate studies on attenuation correction and the derivation of further weather radar products, like an improved rainfall rate. The rainfall rates themselves can be used for studies on the spatial and temporal scales of precipitation and hydrological research, e.g. input data for high-resolution modelling, in an urban area. The radar reflectivities and rainfall rates are available at https://doi.org/10.26050/WDCC/LAWR_UHH_HHG_v2 (Burgemeister et al., 2024).

PyDAP: Automated dental OPG beam area measurement using python and raspberry Pi camera

IntroductionThis study investigates if inexpensive computer hardware, open-source computer vision and a phosphor screen from disused CR (computed radiography) Cassette can be used to quantitatively assess beam shape and area. Materials and MethodsThe phosphor screen was affixed to a Carestream CS 8100 dental OPG system and the camera was mounted above the X-ray tube. Videos were acquired of the green light emissions during the tomographic irradiation. Images of a chessboard pattern, attached to the detector were used to correct for camera angulation and provide image pixel size calibration. K-Means colour clustering was used to define beam area. The effect of light conditions on beam dimension measurement was also investigated. The beam width measurement from optimised methodology was compared with that determined from dose calibrated GAFChromicTM XR-SP2film. ResultsVideos in dark conditions provided the most reproducible results. FW20M gained from initial sampling matched that obtained using the GAFChromicTM film within the errors of the measurements,6.41 ± 0.09 mm FW20M from this methodology,compared with FW20M (full width at 20 % of maximum) 6.4 ± 0.1 mm from film. The height and area were 126 ± 0.22 mm and 807 ± 11 mm2 respectively. The chess pattern imaging provided a robust means of perspective correction and pixel calibration. There is potential for this methodology to be employed using any digital camera, provided the camera acquisition settings remain constant, the sensor pixels are square, and the camera position is fixed. ConclusionThe potential of this low-cost open-source method of beam area measurement using computer vision is thus proven.

A method for obtaining the full field of view Mueller matrix of optical systems by fitting the Orientation Zernike Polynomial parameters

Polarization imaging technology expands the dimensions of the object and enriches its basic information compared to traditional imaging methods. During the imaging process, the polarization information of the object is changed by the aberration of the optical system, which affects the detection accuracy. In this article, we analyzed the Cassegrain system and the double Gaussian system. By using the Orientation Zernike Polynomial (OZP), we decomposed the system's diattenuation pupil and retardance pupil. We discovered a functional relationship between the OZP coefficients and the field of view. By fitting this relationship, we obtained the Mueller matrix for the full field of view. Compared to previous method of tracing a large number of polarized optical rays and integrating to obtain the Mueller matrix in optical software, this approach is more convenient and efficient. Furthermore, the obtained full-field Mueller matrix can provide theoretical guidance for the experimental calibration and system correction of optical system Mueller matrices.

Application of a metallic-magnetic calorimeter for high-resolution x-ray spectroscopy of Fe at an EBIT

In this work, we present an experiment conducted at the S-EBIT-I ion trap of GSI. It involved the study of ion-electron collisions of Fe and Ba ions in various charge states with the electron beam. Characteristic x-ray radiation emitted during the continuous interaction was recorded utilizing an energy-dispersive maXs-30 detector based on metallic-magnetic calorimeter (MMC) technology. Optimizations to the applied sensitivity-drift correction and energy calibration procedures significantly improved the achieved energy resolution compared to previous applications of a similar detector. This made it possible to individually resolve and identify overlapping x-ray lines of iron and barium in a wide spectral range. As a demonstration of the outstanding detector performance, we used the recorded spectral data to extract an estimate of the charge state distribution of Fe ions in the trap. This experiment campaign marks an important milestone in the ongoing effort to enable the deployment of MMC detectors for future high-precision measurements in fundamental physics experiments.

Optimization Scheme of Measuring Accuracy of Bearing Seat Size Based on Machine Vision

At present, the size measurement of industrial workpieces is mainly manual measurement and CMM measurement, which cannot meet the requirements of high precision, high efficiency and low error rate in industrial production at the same time. In order to solve the above problems, this paper uses monocular vision technology to propose an optimization scheme of workpiece size measurement accuracy based on machine vision, which takes the height and declination Angle between the camera lens and the workpiece as variables. Firstly, the image was captured by camera calibration correction, and morphological methods such as gray-scale, denoising, expansion and corrosion were used for image pre-processing. Secondly, features were extracted using double-threshold canny edge detection algorithm and connected domain algorithm. Finally, the bearing seat size was measured using the minimum external rectangle algorithm. The experiment shows that the higher the distance between the camera lens and the stage, the larger the error is when the image information can be collected completely. The greater the Angle between the center of the camera lens and the center of the workpiece, the greater the error; The device not only meets the precision requirements, but also has the advantages of fast response speed, which can meet the needs of industrial applications.

CROP HEIGHT ESTIMATION OF WHEAT USING SENTINEL-1 SATELLITE IMAGERY: PRELIMINARY RESULTS

Abstract. Wheat is one of the primary crop productions for half of the global production. It is the most exported cereal, which reached up to 40% according to the records of the Food and Agriculture Organization of the United Nations (FAO) in 2020. The relationship between the crop parameters and remote sensing tools has become essential for the temporal monitoring and estimations of crop growth. In this study, we investigate the relationship between crop height and Synthetic Aperture Radar (SAR) backscatter. Plant height was collected twice, in the early (13 April 2023) and late stages (21 June 2023) of wheat, for a total of 70 samples. Sentinel-1 SAR data was also attempted to be synchronized with ground measurements. For this purpose, 8 images were obtained, 4 in both ascending (8 and 15 April, 16 and 26 June) and descending (9 and 14 April, 20 and 25 June) directions. The basic steps of image pre-processing, calibration, filtering, and topography correction, were applied to each image. By evaluating the correlation coefficients between plant height and images, data with low correlations were excluded and the first three data, dated 8 April and 19 June, were used for plant height estimation. For prediction purposes, Linear Regression (LR) and Random Forest (RF) methods were evaluated with three different training data sets. The highest correlation and minimum error value were achieved by VH polarization with random forest (r = 0.868, RMSE = 5.377 cm) in the early stage and LR (r = 0.616, RMSE = 14.451 cm) in the late stage. In general, higher training (80%) and lower test data (20%) produced better results.

Polarization upgrade of specMACS: calibration and characterization of the 2D RGB polarization-resolving cameras

Abstract. The spectrometer of the Munich Aerosol Cloud Scanner (specMACS) is a high-spatial-resolution hyperspectral and polarized imaging system. It is operated from a nadir-looking perspective aboard the German High Altitude and LOng range (HALO) research aircraft and is mainly used for the remote sensing of clouds. In 2019, its two hyperspectral line cameras, which are sensitive to the wavelength range between 400 and 2500 nm, were complemented by two 2D RGB polarization-resolving cameras. The polarization-resolving cameras have a large field of view and allow for multi-angle polarimetric imaging with high angular and spatial resolution. This paper introduces the polarization-resolving cameras and provides a full characterization and calibration of them. We performed a geometric calibration and georeferencing of the two cameras. In addition, a radiometric calibration using laboratory calibration measurements was carried out. The radiometric calibration includes the characterization of the dark signal, linearity, and noise as well as the measurement of the spectral response functions, a polarization calibration, vignetting correction, and absolute radiometric calibration. With the calibration, georeferenced, absolute calibrated Stokes vectors rotated into the scattering plane can be computed from raw data. We validated the calibration results by comparing observations of the sunglint, which is a known target, with radiative transfer simulations of the sunglint.

Temperature-Automated Calibration Methods for a Large-Area Blackbody Radiation Source.

High-precision temperature control of large-area blackbodies has a pivotal role in temperature calibration and thermal imaging correction. Meanwhile, it is necessary to correct the temperature difference between the radiating (surface of use) and back surfaces (where the temperature sensor is installed) of the blackbody during the testing phase. Moreover, large-area blackbodies are usually composed of multiple temperature control channels, and manual correction in this scenario is error-prone and inefficient. At present, there is no method that can achieve temperature-automated calibration for a large-area blackbody radiation source. Therefore, this article is dedicated to achieving temperature-automated calibration for a large-area blackbody radiation source. First, utilizing two calibrated infrared thermometers, the optimal temperature measurement location was determined using a focusing algorithm. Then, a three-axis movement system was used to obtain the true temperature at the same measurement location on a large-area blackbody surface from different channels. This temperature was subtracted from the blackbody's back surface. The temperature difference was calculated employing a weighted algorithm to derive the parameters for calibration. Finally, regarding experimental verification, the consistency error of the temperature measurement point was reduced by 85.4%, the temperature uniformity of the surface source was improved by 40.4%, and the average temperature measurement deviation decreased by 43.8%. In addition, this system demonstrated the characteristics of strong environmental adaptability that was able to perform temperature calibration under the working conditions of a blackbody surface temperature from 100 K to 573 K, which decreased the calibration time by 9.82 times.

Improvements in digital meteor spectra reduction

This study addresses the complexity and importance of developing a method of calibrating digital observations of meteor spectra with all-sky cameras. It aims to present novel approaches to spectral sensitivity, atmospheric extinction and flat-field corrections. Images of a known line emission spectrum were captured at various positions within the field of view using a camera with a fish-eye lens and plastic holographic grating. The flat-field correction was separated into a wavelength-independent and wavelength-dependent component, both dependent on the position of the spectral line in the field of view (FoV). Total profile intensities of spectra obtained from the images were compared throughout the spectral range at different positions in the FoV. The flat-field was constructed by fitting those dependencies with high-degree polynomial functions. Using a simplified atmospheric model, a novel approach was constructed to determine the atmospheric extinction curve throughout the spectral range, allowing it to be separately considered from the spectral sensitivity which was previously not the case. A comparison of the newly developed and previously used methodology was tested on several meteor spectra of the same meteor captured from different stations of the European Fireball Network. It revealed a significantly improved correspondence of the analysed spectra in the part of the spectral range unaffected by the limitations imposed by the newly developed methodology. Failing to follow the correct calibration methodology precisely may introduce varying degrees of uncertainty in computations of elemental abundances and other physical properties, depending on the equipment’s specific effect magnitude.

Research on the UOSM four-port Calibration algorithm and determination method of the Transmission error term

As one of the key techniques for vector network analyzers to achieve high precision measurement, calibration, and error correction technology has always been the focus of continuous exploration and innovation. UOSM calibration algorithm uses unknown straight-through transmission standards that do not need to be defined and known open-circuit standards, short-circuit standards, and matching standards to calibrate microwave and millimeter wave bands. Based on the study of the mature UOSM calibration algorithm, this paper proposes a method of self-calibration and comparison of the measurement data based on the unknown cut-through standard, which no longer needs the group delay parameters of the unknown straight-through standard and reduces the dependence on the calibrator. The accuracy of the algorithm and error item determination method is verified by ADS simulation and instrument actual test, and a good calibration effect is achieved. It is proved that the algorithm has the ability of accurate calibration. Due to the reduction of parameters, the stability and applicability of the algorithm are improved.

Accuracy Improvement For Minor Elements Determination Using Modified Self-Absorption Correction And One-Point Calibration Laser-Induced Breakdown Spectroscopy

Accuracy Improvement For Minor Elements Determination Using Modified Self-Absorption Correction And One-Point Calibration Laser-Induced Breakdown Spectroscopy