Noise Equivalent Spectral Radiance Research Articles

Low-latency equal optical path difference sampling for multi-field VLWIR interference signals

The spaceborne Fourier Transform Spectrometer has been utilized for vertical atmospheric soundings with a HgCdTe infrared focal plane arrays (FPAs) detector. However, the VLWIR FPA Fourier spectrometer system faces the difficulty of poor sensitivity due to the major contribution of the system sampling error. In this work, low-latency data acquisition of multi-field VLWIR interference signals based on VLWIR FPA Fourier spectrometer system is realized with an optimized field programmable gate array (FPGA) timing driver scheme and layout algorithm. This scheme can effectively reduce routing delay and constrain critical timing paths, and thus leads to a significant decrease in the deviation of equal optical path difference sampling time from 10.27μs to 0.10μs. Interferograms and spectrograms are efficiently obtained. Furthermore, the average value of noise equivalent spectral radiance (NESR) in VLWIR FPA Fourier spectrometer system, is reduced by 1.75% by timing optimization. In particular, the decay of the NESR can be as high as 15% for some of the pixels. These results illustrate that the proposed scheme will acquire hyperspectral data accurately with VLWIR FPA and meet the needs of rapid soundings development of the Geostationary Interferometric Infrared Sounder (GIIRS) availing a rapid prediction of the appearance of an extreme weather event.

Performance evaluation of noise equivalent spectral radiance calibration system

Performance evaluation of noise equivalent spectral radiance calibration system

Performance of an uncooled imaging interferometric spectrometer with intrinsic background radiation

A signal-to-noise performance of an imaging Michelson interferometer based on corner cubes is modeled and experimental results are presented. The influence from the background radiation of the uncooled sensor is explained. The noise equivalent spectral radiance is determined in the 700 to 1300 cm − 1 range at two spectral resolutions using blackbody sources. The performance of the sensor system is tested on a scene at an average temperature of 19°C. From these results, the performance is given in terms of number of samples and spectral resolution. The performance model is used to predict the sensor performance at different scene temperatures.

Antinoise Estimation of Temperature and Emissivity for FTIR Spectrometer Data Using Spectral Polishing Filters: Design and Comparison

The ill-posed separation problem of land surface temperature and emissivity (LST and LSE) from ground-based Fourier transform infrared (FTIR) spectrometer data is vulnerable to random errors generated in the preceding measurement and calibration processes. Under the assumption that the influence of random radiative errors is mainly manifested in the overall stretching (multiplicative noise) and high frequency fluctuation (additive noise) upon at-ground radiance spectrum, the traditional iterative retrieval method is improved to an antinoise estimation method. A prepolishing strategy in radiance domain is employed to suppress the additive noise. A spectrally invariant coefficient is introduced during iteration for the estimation and correction of multiplicative noise. The Savitzky-Golay filtering is introduced to the proposed method first. For the simulation data of typical ground-based FTIR spectrometers (spectral sampling interval of 1-4 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> , noise equivalent spectral radiance of 5 ×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-9</sup> W/(cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ·sr ·cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ), and multiplicative noise error of 1.015), the root-mean-square error (RMSE) of LST is ≤ 0.4 K, the RMSE of LSE is <; 0.01 in the long-wave infrared range. For field data of a spectrometer under similar noise conditions, the RMSE of LST is about 0.7 K and consistent with the LST measured by a thermocouple thermometer, considering the measurement uncertainty. The proposed method is also generalized to use moving average filtering, derivation filtering, the Fourier transform, and wavelet transform. For the field data with both multiplicative and additive noises, the antinoise estimation methods with these tested filters have similar accuracy; among them, the moving average filtering and the Savitzky-Golay filtering are recommended.

Radiometric sensitivity contrast metrics for spectral remote sensors

The calculation, interpretation, and implications of radiometric sensitivity metrics for Earth-observing multispectral and hyperspectral imaging sensors are discussed. The most commonly used sensor performance metric is signal-to-noise ratio, from which additional noise equivalent quantities can be computed, including noise equivalent spectral radiance (NESR), noise equivalent delta reflectance ( NE Δ ρ ), noise equivalent delta emittance ( NE Δ ϵ ), and noise equivalent delta temperature ( NE Δ T ). For hyperspectral sensors, these metrics are typically calculated from an at-aperture radiance (typically generated by MODTRAN) that includes both target radiance and nontarget (atmosphere and background) radiance. Unfortunately, these calculations treat the entire at-aperture radiance as the desired signal, even when the target radiance is only a fraction of the total (such as when sensing through a long or optically dense atmospheric path). To overcome this limitation, an augmented set of metrics based on a contrast signal-to-noise ratio, including their noise equivalent counterparts (CNESR, CNE Δ ρ , CNE Δ ϵ , and CNE Δ T ), is developed. These contrast metrics better quantify sensor performance in an operational environment that includes remote sensing through the atmosphere.

Investigation of detecting biological aerosol by passive Fourier transform infrared spectroscopy technology based on MODTRAN model

The problem of detecting the biological aerosol at low elevation angle is analyzed and discussed by using MODTRAN model. First of all, the atmospheric model and profile of MODTRAN model are introduced for the biological aerosol detection by Fourier transform infrared (FTIR) spectroscopy. According to the passive detection of biological aerosol by FTIR spectroscopy, the radiation brightness difference L between the background and the target biological aerosol is calculated by using the radiative transfer theory and the simplest three-layer model. The signal value 2Lt under the actual circumstance is derived from the derivative of L combined with the noise equivalent spectral radiance value of the spectrometer. Finally, the detection limit of biological aerosol for each atmospheric mode is predicted with the passive remote sensing method. The limit concentration of detection for each atmospheric mode is different due to the differences in boundary layer temperature, transmittance, and background radiation brightness of atmospheric model, and it is also related to the absorption coefficient of biological aerosol. It is shown that the passive remote sensing of FTIR technology can detect the presence of the biological aerosol. Therefore, the detection of the biological aerosol is feasible. It presents a method of detecting the biological aerosol cloud under the actual circumstance.

Scattering in infrared radiative transfer: A comparison between the spectrally averaging model JURASSIC and the line-by-line model KOPRA

The viability of a spectrally averaging model to perform radiative transfer calculations in the infrared including scattering by atmospheric particles is examined for the application of infrared limb remote sensing measurements. Here we focus on the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the European Space Agency's Envisat. Various spectra for clear air and cloudy conditions were simulated with a spectrally averaging radiative transfer model and a line-by-line radiative transfer model for three atmospheric window regions (825–830, 946–951, 1224–1228cm−1) and compared to each other. The results are rated in terms of the MIPAS noise equivalent spectral radiance (NESR). The clear air simulations generally agree within one NESR. The cloud simulations neglecting the scattering source term agree within two NESR. The differences between the cloud simulations including the scattering source term are generally below three and always below four NESR. We conclude that the spectrally averaging approach is well suited for fast and accurate infrared radiative transfer simulations including scattering by clouds. We found that the main source for the differences between the cloud simulations of both models is the cloud edge sampling. Furthermore we reasoned that this model comparison for clouds is also valid for atmospheric aerosol in general.

Absolute characterization of laser-induced breakdown spectroscopy detection systems

A quantitative comparison of the performance of four different laser-induced breakdown spectroscopy detection systems is presented. The systems studied are an intensified photodiode array coupled with a Czerny–Turner spectrometer, an intensified CCD coupled with a Czerny–Turner spectrometer, an intensified CCD coupled to an Echelle spectrometer, and a prototype multichannel compact CCD spectrometer system. A simple theory of LIBS detection systems is introduced, and used to define noise-equivalent spectral radiance and noise-equivalent integrated spectral radiance for spectral detectors. A detailed characterization of cathode noise sources in the intensified systems is presented.

MIPAS Level 1B algorithms overview: operational processing and characterization

Abstract. This paper gives an overview of the MIPAS Level 1B (L1B) processor whose main objective is to calibrate atmospheric measurements radiometrically, spectrally and geo-located. It presents also the results of instrument characterization done on ground and during the first years in-flight. An accurate calibration is mandatory for high quality atmospheric retrievals. MIPAS has shown very good performance and stability. The noise equivalent spectral radiance ranges from 3 to 50 nW/(cm2 sr cm−1) and is well within the requirements over nearly the whole spetral range. The systematic radiometric error is estimated to be within 1 or 2% in most situations.

TES level 1 algorithms: interferogram processing, geolocation, radiometric, and spectral calibration

The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite measures the infrared radiance emitted by the Earth's surface and atmosphere using Fourier transform spectrometry. The measured interferograms are converted into geolocated, calibrated radiance spectra by the L1 (Level 1) processing, and are the inputs to L2 (Level 2) retrievals of atmospheric parameters, such as vertical profiles of trace gas abundance. We describe the algorithmic components of TES Level 1 processing, giving examples of the intermediate results and diagnostics that are necessary for creating TES L1 products. An assessment of noise-equivalent spectral radiance levels and current systematic errors is provided. As an initial validation of our spectral radiances, TES data are compared to the Atmospheric Infrared Sounder (AIRS) (on EOS Aqua), after accounting for spectral resolution differences by applying the AIRS spectral response function to the TES spectra. For the TES L1 nadir data products currently available, the agreement with AIRS is 1 K or better.

Noise assessment of a Fourier transform infrared spectroradiometer subject to the stability of a conventional laboratory blackbody source.

A method is described for the measurement of the noise-equivalent spectral radiance (NESR) of Fourier transform infrared (FTIR) spectroradiometers at all wave numbers of a selected range. The method requires minimal detailed knowledge of the sensor and no support equipment beyond a blackbody source. The NESRs of the FTIR spectroradiometer are determined at every wave-number increment in the 700-1300 cm(-1) range, for six resolutions, with a conventional blackbody source and ensembles of differential spectra. The NESRs are well behaved and consistent with the expected dependence on resolution; however, they depend on source temperature at the highest (1 cm(-1)) and lowest (32 cm(-1)) resolutions, with little or no statistical dependence at intermediate resolutions. Residual source drift is shown to be the likely cause of the dependence at 1 cm(-1); the dependence on the source at 32 cm(-1) resolution is shown to be most probably due to photon noise. At intermediate resolutions the sensor noise is dominant.

Tunable Fabry–Perot etalon-based long-wavelength infrared imaging spectroradiometer

Imaging spectrometry enables passive, stand-off detection and analysis of the chemical composition of gas plumes and surfaces over wide geographic areas. We describe the use of a long-wavelength infrared imaging spectroradiometer, comprised of a low-order tunable Fabry-Perot etalon coupled to a HgCdTe detector array, to perform multispectral detection of chemical vapor plumes. The tunable Fabry-Perot etalon used in this research provides coverage of the 9.5-14-microm spectral region with a resolution of 7-9 cm(-1). The etalon-based imaging system provides the opportunity to image a scene at only those wavelengths needed for chemical species identification and quantification and thereby minimize the data volume necessary for selective species detection. We present initial results using a brassboard imaging system for stand-off detection and quantification of chemical vapor plumes against near-ambient-temperature backgrounds. These data show detection limits of 22 parts per million by volume times meter (ppmv x m) and 0.6 ppmv x m for dimethyl methyphosphonate and SF6, respectively, for a gas/background DeltaT of 6 K. The system noise-equivalent spectral radiance is approximately 2 microW cm(-2) sr(-1) microm(-1). Model calculations are presented comparing the measured sensitivity of the sensor to the anticipated signal levels for two chemical release scenarios.

Surface-roughness considerations for atmospheric correction of ocean color sensors 1: The Rayleigh-scattering component

The first step in the coastal zone color scanner (CZCS) atmospheric-correction algorithm is the computation of the Rayleigh-scattering contribution, Lr(r), to the radiance leaving the top of the atmosphere over the ocean. In the present algorithm Lr(r), is computed by assuming that the ocean surface is flat. Computations of the radiance leaving a Rayleigh-scattering atmosphere overlying a rough Fresnel-reflecting ocean are presented to assess the radiance error caused by the flat-ocean assumption. The surface-roughness model is described in detail for both scalar and vector (including polarization) radiative transfer theory. The computations utilizing the vector theory show that the magnitude of the error significantly depends on the assumptions made in regard to the shadowing of one wave by another. In the case of the coastal zone color scanner bands, we show that for moderate solar zenith angles the error is generally below the 1 digital count level, except near the edge of the scan for high wind speeds. For larger solar zenith angles, the error is generally larger and can exceed 1 digital count at some wavelengths over the entire scan, even for light winds. The error in Lr(r) caused by ignoring surface roughness is shown to be the same order of magnitude as that caused by uncertainties of +/- 15 mb in the surface atmospheric pressure or of +/- 50 Dobson units in the ozone concentration. For future sensors, which will have greater radiometric sensitivity, the error caused by the flat-ocean assumption in the computation of Lr(r) could be as much as an order of magnitude larger than the noise-equivalent spectral radiance in certain situations.

Radiometric Performance Of The Test-Bed Aircraft Multispectral Scanner (TBAMS) System

Laboratory and flight radiometric performance testing of an experimental multispectral scanner system is described. High sensitivity performance is confirmed by test results using noise equivalent spectral radiance as the primary figure of merit. A performance comparison between the test-bed air-craft multispectral scanner (MAMS) and the Bendix modular multispectral scanner (MIS) is presented. Methods for achieving high sensitivity operation are discussed as well as some of the practical implications of such operation for flight remote sensing experiments.

Infrared spectrometer: liquid-helium-cooled rocketborne circular-variable filter

An ir spectrometer used to obtain atmospheric emission spectra from a rocket at altitudes between 45 km and 200 km in the ICECAP Auroral Measurements Program is described. The instrument continuously scans the 6.75-23.2-microm spectral region at the rate of 2 scans/sec. The spectral resolution of the instrument, which employs a circular-variable interference filter (CVF), ranges from 3% to 4%. The entire optical subsection, silicon-arsenic detector, CVF, Irtran 6 lens, baffle, and removable cold cover are cooled below 10 K in a high-vacuum Dewar system. The noise equivalent spectral radiance (NESR) of the spectrometer at 22 ,microm is better than 1 x 10(-11) (W cm(-2)sr(-1)microm(-1)). The dominant high altitude atmospheric emission features observed on two rocket flights were 9.6-microm O(3) and 15-microm CO(2).