External Calibration Targets Research Articles

Development and validation of an individual-based state-transition model for the prediction of frailty and frailty-related events.

Frailty is a biological syndrome that is associated with increased risks of morbidity and mortality. To assess the value of interventions to prevent or manage frailty, all important impacts on costs and outcomes should be estimated. The aim of this study is to describe the development and validation of an individual-based state transition model that predicts the incidence and progression of frailty and frailty-related events over the remaining lifetime of older Australians. An individual-based state transition simulation model comprising integrated sub models that represent the occurrence of seven events (mortality, hip fracture, falls, admission to hospital, delirium, physical disability, and transitioning to residential care) was developed. The initial parameterisation used data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The model was then calibrated for an Australian population using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The simulation model established internal validity with respect to predicting outcomes at 24 months for the SHARE population. Calibration was required to predict longer terms outcomes at 48 months in the SHARE and HILDA data. Using probabilistic calibration methods, over 1,000 sampled sets of input parameter met the convergence criteria across six external calibration targets. The developed model provides a tool for predicting frailty and frailty-related events in a representative community dwelling Australian population aged over 65 years and provides the basis for economic evaluation of frailty-focussed interventions. Calibration to outcomes observed over an extended time horizon would improve model validity.

Deep Learning Calibration of the High-Frequency Airborne Microwave and Millimeter-Wave Radiometer (HAMMR) Instrument

Calibration plays an important role in improving the accuracy of the microwave and millimeter-wave radiometric measurements. Several calibration techniques have been used in radiometers including external calibration targets, vicarious sources, and internal calibrators such as noise diodes or matched reference load. A new calibration technique based on deep learning has recently been developed to calibrate microwave and millimeter-wave radiometers. The deep-learning calibrator has been previously demonstrated on a computer noise-wave modeled Dicke-switching radiometer. This article applies the new deep-learning calibration technique for the calibration of the high-frequency airborne microwave and millimeter-wave radiometer (HAMMR) instrument. A deep-learning neural network model is built to calibrate the 2014 West Coast Flight Campaign antenna temperature measurements of the HAMMR. The deep-learning calibrator antenna temperature estimates are obtained from the radiometric measurements. The deep-learning calibration results are compared with the existing conventional calibration techniques used in HAMMR 2014 field campaign. The results have shown that the deep-learning calibrator is in agreement with the conventional calibration techniques. In this article, it is demonstrated that the deep-learning calibrator can be employed for calibrating the radiometers with high accuracy.

A Preliminary Study of Three-Point Onboard External Calibration for Tracking Radiometric Stability and Accuracy

Absolute calibration of radiometers is usually implemented onboard using one hot and one cold external calibration targets. However, two-point calibration methods are unable to differentiate calibration drifts and associated errors from fluctuations in receiver gain and offset. Furthermore, they are inadequate to characterize temporal calibration stability of radiometers. In this paper, a preliminary study with linear radiometer systems has been presented to show that onboard external three-point calibration offers the means to quantify calibration drifts in the radiometer systems, and characterize associated errors as well as temporal stability in Earth and space measurements. Radiometers with three external calibration reference targets operating two data processing paths: i.e., (1) measurement path and (2) calibration validation path have been introduced. In the calibration validation data processing path, measurements of one known calibration target is calibrated using the other two calibration references, and temporal calibration stability and possible calibration temperature drifts are analyzed. In the measurement data processing path, the impact of the calibration drifts on Earth and space measurements is quantified and bounded by an upper limit. This two-path analysis is performed through calibration error analysis (CEA) diagrams introduced in this paper.

Ice thickness effects on Aquarius brightness temperatures over Antarctica

AbstractThe Dome‐C region, in the East Antarctic Plateau, is regarded as an ideal natural laboratory for calibration/validation of space‐borne microwave radiometers. At L‐band, the thermal stability of this region has been confirmed by several experimental campaigns. However, its use as an independent external calibration target has recently been questioned due to some spatial inhomogeneities and seasonal effects revealed in the brightness temperatures (TB) acquired in this area. This paper shows the observed relationship, from exploratory research, between the Antarctic ice thickness spatial variations and the measured Aquarius TB changes. A 3‐months no‐daylight period during the Austral winter has been analyzed. Four transects have been defined over East Antarctica covering areas with different ice thickness variations and ranges. The theoretical L‐band penetration depth has been estimated to understand the possible contributions to the measured signal. A good agreement has been observed between Aquarius TB and ice thickness variations over the whole Antarctica, with correlations of ∼0.6–0.7. The two variables show a linear trend with slopes of ∼8.3–9.5 K/km. No correlation has been observed with the subglacial bedrock. The maximum L‐band penetration depth has been estimated to be ∼1–1.5 km. Results are therefore consistent: the spatial variations found on Aquarius TB are not related to the emissivity of the bedrock, which lies deeper. This study provides evidence that new L‐band satellite observations could contribute to further our understanding of Antarctic geophysical processes.

지표면 영향을 고려한 삼각 전파 반사기의 RCS 분석

위성 SAR(Synthetic Aperture Radar)를 정확하게 보정하기 위해서는 검보정에 사용되는 삼각 전파 반사기(Trihedral Corner Reflector: TCR)의 RCS(Radar Cross Section)를 정확하게 계산해야 한다. 본 연구에서는 TCR이 설치된 지표면이 TCR의 RCS 값에 얼마나 영향을 미치는지를 알아보기 위해서 지표면에서의 반사파와 TCR 모서리에서의 회절파를 이론적으로 계산하여 검보정 사이트의 지표면 상태에 따른 RCS 변화를 분석하였다. 지표면 반사파를 구하기 위해 지표면에 대한 PO 반사 계수를 이용하였으며, PO 반사 계수는 지표면 상태 변수인 거칠기와 유전율에 대한 함수이다. 중심 주파수 9.65 GHz에서 지표면 위에 설치된 <TEX>$10{\lambda}$</TEX> 크기 TCR의 RCS 값은 공기 중의 TCR에 비해 0.46 dB 변화가 발생하였고, 이 변화는 지표면의 상태 및 TCR 크기에 따라 크게는 1.55 dB정도의 차이가 날 수 있다. 지표면 영향에 따른 TCR의 RCS 값은 지표면의 거칠기가 작고 유전율이 클수록 크며, 중심 주파수가 낮고 TCR의 크기가 작을수록 크게 발생하였다. The radar cross section(RCS) of a trihedral corner reflector(TCR) should be accurately computed when it is used as an external calibration target for a satellite synthetic aperture radar(SAR) calibration campaign. This paper presents the RCS analysis on a trihedral corner reflector which is installed on a calibration site, using the wave reflection from the rough surface and the wave diffraction from the TCR edges. The results in this paper show quantitatively the effect of the front surface on the RCS of a TCR. The difference of the RCS between a TCR in air and a TCR on a ground surface is computed by including the interaction term which consists of the edge diffraction from the TCR edges and the surface reflection from the front rough surface. The reflection coefficient of a randomly rough surface is a function of the surface roughness and dielectric constant of the surface. The RCS of <TEX>$10{\lambda}$</TEX> size TCR on a ground is 0.46 dB higher than TCR in air at 9.65 GHz, and this can reach at maximum 1.55 dB depending on a surface condition and TCR size. The effect of the front surface on the RCS of a TCR increases, as the surface roughness decreases, the soil moisture increases, and the size of TCR in wavelength decreases.

Absolute Radiometric Calibration of ALS Intensity Data: Effects on Accuracy and Target Classification

Radiometric calibration of airborne laser scanning (ALS) intensity data aims at retrieving a value related to the target scattering properties, which is independent on the instrument or flight parameters. The aim of a calibration procedure is also to be able to compare results from different flights and instruments, but practical applications are sparsely available, and the performance of calibration methods for this purpose needs to be further assessed. We have studied the radiometric calibration with data from three separate flights and two different instruments using external calibration targets. We find that the intensity data from different flights and instruments can be compared to each other only after a radiometric calibration process using separate calibration targets carefully selected for each flight. The calibration is also necessary for target classification purposes, such as separating vegetation from sand using intensity data from different flights. The classification results are meaningful only for calibrated intensity data.

A Physical Method for the Calibration of the AVHRR/3 Thermal IR Channels 1: The Prelaunch Calibration Data

Abstract The absolute accuracy of the thermal infrared (IR) radiances and brightness temperatures derived from the Advanced Very High Resolution Radiometer (AVHRR) is still unknown, with major sources of error not yet fully understood. This is despite the fact that data from the AVHRR IR channels are widely used in deriving important atmospheric and surface parameters as well as in weather prediction, climate modeling, and other environmental studies. Central to the problem are possible errors introduced by the calibration test procedures and methodologies that can range up to approximately 0.5 K, much larger than the instrument electronic and detector noise characteristics. Further, there are known issues with the current calibration including a large mismatch of up to 0.7 K between the measured physical temperature of the internal calibration target (ICT) and its radiometric temperature estimated by using the AVHRR-observed counts. In an effort to improve this, a new approach to the calibration has been adopted that is dependent on physical instrument parameters. It is shown that this new calibration method can explain the ICT temperature mismatch as a combination of an incorrect assumption that the AVHRR was kept at a constant temperature during testing combined with the effect of scattered radiation from the test chamber and other sources. This new calibration also reduces the total biases and errors that exist when using the current operational calibration on the prelaunch data. Comparing the external calibration target temperatures to the temperatures derived using the AVHRR measurements, this new calibration can reduce an up to 0.7-K bias seen currently to an essentially zero bias with a scatter of less than 0.05 K in the SST regime. This marks an improvement of up to an order of magnitude in accuracy over the current operational calibration.

Prelaunch instrument calibration in the real world: The GOES example

The pre-launch ground infrared calibration of the Geostationary Operational Environmental Satellite (GOES) N-Q Imager and Sounder is presented. Ground calibration provides information necessary to the accurate on-orbit calibration of these radiometers. Infrared channels are calibrated in a thermal vacuum environment, under minimum and maximum mission operation temperatures, using a variable-temperature warm target to simulate the Earth scene and a cold target to simulate the space scene. Brightness temperatures derived from observation of the instrument internal calibration target, used for on-orbit calibration, are compared to brightness temperatures of the external calibration target as a check of relative accuracy using these two sources. Changes to the GOES N-Q specification from GOES I-M are highlighted, as well as results of noise, relative calibration accuracy, and spectral response performance to date. For completeness, results of spatial and pointing performance will be presented. Enhancements to test methodology and data processing techniques are highlighted throughout.

Calibration of polarimetric radar images using only image parameters and trihedral corner reflector responses

A technique that uses the radar return from natural targets and at least one trihedral corner reflector to calibrate compressed polarimetric radar data is described. Calibration for relative amplitude, relative phase, absolute amplitude, and system crosstalk is addressed. The crosstalk calibration method is based on the theoretical result that for natural targets with azimuthal symmetry the copolarized and crosspolarized components of the scattering matrix are uncorrelated, and the method does not require any external calibration targets to be deployed before imaging. Because compressed data are used, one is forced to model the transmitting and receiving systems as reciprocal. Even though the inferred transmit and receive matrices are not each simply related to the physical transmitter and receiver, the true Stokes matrix for each pixel in an image can be accurately determined by this approach. The method is illustrated by estimating the crosstalk parameters of the NASA/JPL aircraft for different types of terrain and for two frequencies. For the C-band system, the crosstalk is less than -20 dB for all ranges in the images. The crosstalk of the L-band system is a function of range, however, and may be as poor as -10 dB in the near range, leading to a noticeable distortion of the polarization signatures.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Calibration of advanced very high resolution radiometer infrared observations

A detailed analysis of the calibration procedures for the NOAA advanced very high resolution radiometer (AVHRR) based on thermal vacuum test data was performed as part of the Warm Core Rings Experiment. We find systematic differences in the derived calibration results and those reported in the various addenda to work by Lauritson et al. (1979). A weak, but important, dependence in calibration upon internal operating temperature is also observed. Calibration results for various AVHRR radiometers show instrument specific changes in the relative emittance between internal and external calibration targets. A consistent calibration methodology is developed based on this analysis of the thermal vacuum test data. Use of these new results provides an improvement of radiometer calibration at the ±0.2°C level. Such an improvement is quite important to the absolute accuracy of surface thermal fields which are derived from these data utilizing various multichannel atmospheric water vapor correction schemes. Demonstration of such accuracies with presently operational sensors is of importance to climate related studies being planned for the next decade since it shows that appropriate processing can lead to higher‐quality SST fields.