Abstract

A miniature thermal infrared laser heterodyne spectro-radiometer based on hybrid optical integration is demonstrated. A quantum cascade laser emitting at 953 cm−1 (10.5 μm) is used as the local oscillator. Integration is achieved using hollow waveguides inscribed in a copper substrate, with slot-encapsulated optical components positioned to maintain fundamental hybrid mode coupling. The demonstrator performances are studied in the laboratory and show a noise level within 1.6 times of the ideal case. Atmospheric high-resolution transmittance spectroscopy of carbon dioxide and water vapor in solar occultation is demonstrated. The total column concentrations are derived as well as measurement uncertainties, 399.5 ± 2.2 ppm for CO2 and 1066 ± 62 ppm for H2O. The miniature laser heterodyne spectro-radiometer demonstration opens the prospect for nanosatellite-based high spectral resolution thermal infrared atmospheric sounding.

Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

1. Introduction

Mid-infrared laser heterodyne spectro-radiometry (LHR) has long been applied to remote molecular characterization, for either atmospheric studies of planets (including the Earth) or characterization of astronomical objects [1, 2]. This spectrometry technique offers high-spectral resolution without relying on interferometric optical path difference, high sensitivity, and a narrow field of view. Use of a single-mode semiconductor laser such as a quantum cascade laser (QCL) [3, 4] as the local oscillator (LO), whose continuously tunable spectral window can be precisely tailored, allows optimized probing of selected molecular ro-vibrational transitions. From high-resolution lineshape measurements thermo-physical information, including molecular abundance and its vertical distribution, can be remotely deduced.

Recently, the advent of miniaturized airborne and space platforms such as high-altitude long endurance vehicles and nanosatellites (cubesats), and their prospective use for atmospheric sounding missions, has emphasized the need for spectrometer miniaturization without, when possible, loss of sensing performance. Of particular interest to atmospheric constituent profiling is maintaining high spectral resolution to resolve absorption lineshapes, such as the Doppler-limited molecular lines found in the Earth’s middle atmosphere, or in thin planetary atmospheres [5, 6].

Hybrid hollow waveguide (HW) integration offers an efficient path to ruggedization and miniaturization of laser optical systems, whilst enhancing spatial mode overlap and heterodyne mixing performance [7, 8]. Rigid hollow waveguides inscribed either in dielectric or metallic substrates are suitable for mid-infrared wavelengths; they have low insertion loss, and no facet reflection [9]. Despite the multimode nature of typical sub-mm cross-section HWs in the thermal infrared, with proper coupling, propagation in the fundamental EH11 waveguide mode [10] can be maintained throughout the entire integrated optical circuit, for optimum mixing efficiency and minimal losses.

This article reports on the design, fabrication, and demonstration of a first integrated thermal infrared HW-LHR for atmospheric sounding. The demonstration prototype is implemented to operate in ground-based solar occultation remote sensing mode, and performance evaluation is carried out through measurement of the carbon dioxide and water vapor total atmospheric columns. Section 2 gives a description of the instrument design and how it was fabricated. Section 3 presents results of a laboratory characterization of the instrument performance. Section 4 describes the details of the demonstration of the instrument for ground-based solar occultation remote sensing.

2. Miniaturized HW-LHR implementation

In LHR, the incoming radiation to be spectrally analyzed is mixed with that of an ideal optical oscillator onto a fast photodiode. This heterodyning converts the optical spectral information down to intermediate frequencies (IF) typically in the radio-frequency (RF) range. The spectral analysis is performed by RF filters in the electronic domain. The architecture of the HW-LHR is directly inspired from a standard breadboard optical QCL LHR, which is described in detail elsewhere [11].

The miniaturization into a single substrate is depicted in Fig. 1. A single substrate block integrates all the key optical elements in slots, and the HW optical circuit is directly inscribed into the block. The material chosen for the substrate is oxygen-free copper. Extensive study of copper HWs in the middle infrared has demonstrated improved propagation losses compared to HWs in dielectric materials such as Macor. The surface roughness (Rt) of the waveguide was measured to be < 1.5 µm in copper, compared to ∼ 5 µm for Macor owing to its granular composition. This improvement reduces HW wall scattering, improving propagation losses, and also translates into improved component positioning accuracy. In addition, the high thermal conductivity of the copper substrate enables an efficient control of the block temperature, and efficient dissipation of heat generated by active components such as the QCL, to ensure improved thermal stability. The HW block is mounted on a thermoelectric cooler for active temperature control.

 

Fig. 1. Schematic of the integrated HW-LHR. Electronic subsystem is given in grey lines. All optical components are integrated into the same substrate. The output from the heterodyne photomixer is split into a DC component and the IF component. The IF is filtered (HPF) to tailor the instrument lineshape and a Schottky diode (SD) measures the RF power prior to phase sensitive detection (LIA).

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The intersection point between the HW optical axis and the LO HW input port plane defines the reference datum of the structure, against which all components are positioned with an accuracy guaranteeing >95% coupling in the EH11 mode [8]. To achieve this requirement, optical dimensional metrology is carried out on all integrated components using contact and non-contact coordinate measurements (e.g. SmartScope). The QCL dimensions are particularly critical as the laser ridge position and orientation with respect to the QCL mount must be well-known to allow optimum coupling to the EH11 HW mode.

On the LO side, the QCL used (QD10492NS1AS, Thorlabs) has been specified and tailored for optimum measurements of CO2 in the thermal infrared. It is a distributed feedback device which can tune across ∼1 cm-1 in a single current ramp around 953.1 cm¬1. The frequency range has been selected through prior atmospheric retrieval simulations [11]. The QCL is linearly polarized perpendicular to the plane of the HW substrate. The optical output from the QCL needs to be conditioned to match the EH11 coupling condition at the HW LO input port. To do so, a custom aspheric lens (LightPath, 1.50 mm diameter, 0.5 mm focal length) is used. The laser is accurately positioned using insulating dowels referenced to the substrate datum. A thermistor is also integrated close by and is used for active PID control of the block temperature by a temperature controller (LDT-5545B, ILX Lightwave). The lens is brought to its nominal position using a 3-axis sub-micron resolution translation stage (New Focus) and optimized by monitoring the power and spatial profile exiting the heterodyne output port. Using an infrared camera, the beam profile is used as the metric to optimize EH11 fundamental mode coupling. The coupling efficiency of the QCL into the waveguide was ∼96%. Finally, the lens mount is permanently secured in position using UV-cured epoxy.

The beamsplitter (BS) which superimposes the LO and the signal radiation (from a blackbody or the sun) was a custom designed optic (II-IV, ZnSe, 3 × 3 mm) with a splitting ratio of approx. 80:20 (transmission/reflection), which maximizes the amount of solar radiation directed to the photomixer while also allowing the optimum LO power from the QCL. The BS was measured to give a reflectance of 18.1% at the operating wavelength, in good agreement with the specified value. The rear surface of the BS was antireflection coated and wedged (0.5°) with respect to the front surface, to prevent parasitic etalon fringes. The BS is positioned in an accurately machined slot in the waveguide block. The slot positioning tolerances must again ensure >95% recoupling in EH11 mode after transmission and reflection, and encapsulate the BS.

The channel guiding the superimposed LO and signal fields terminates in front of the photomixer: a Peltier cooled mercury cadmium telluride photovoltaic detector (Vigo PVI-2TE-9.7) equipped with an immersed lens. The effective active area of the detector is a square, 0.14×0.14 mm2.

The coupling of the signal radiation into the HW signal input port is less critical as both the laboratory blackbody (BB) and the Sun are extended sources. An 8” (203.2 mm) effective focal length 90° off axis parabolic mirror (OAPM) forms a source image onto the signal input port plane. For example, when operating in solar occultation mode, an image of the solar disk of 1.9 mm diameter is formed. The relevant mid infrared part of the incoming signal is selected by a long pass optical filter (>7.3 μm). The blades of a mechanical chopper are inserted just in front of the input HW port to provide signal amplitude modulation for phase sensitive detection at ∼1.8 kHz.

The radiation from the diagnostic output port of the HW goes through a large slot machined into the substrate and onto an uncooled “slow” detector. An optical etalon or a gas cell can be positioned into the large slot for laser frequency calibration.

Once completed, the HW-LHR optical block measures 95 × 34 mm and is installed on a fiberglass pedestal and connected to its control systems. Figure 2 shows a photograph of the demonstrator of the integrated HW-LHR, with all optics contained within the waveguide block.

 

Fig. 2. Photograph of the integrated HW-LHR: (A) diagnostic output port (diagnostic components are removed); (B) beamsplitter; (C) photomixer; (D) LO input HW; (E) lens; (F) QCL; (G) solar/BB input HW; (H) HW substrate.

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Connected to the HW-LHR block are: 1) the QCL current controller, 2) the temperature PID controller and control thermistors, 3) the photomixer back-end, and 4) the diagnostic detector back-end (optional, and only used during QCL characterization).

The photomixer package contains an AC/DC splitter, photomixer bias circuitry and amplifiers. The detector signal is therefore formed of two components, the DC signal, VDC, and the IF signal. The IF signal is amplified by a transimpedance amplifier (104 V/A gain with a 1000 MHz bandwidth). Low frequency components from the IF are further removed using a 25 MHz high pass lumped element filter. The RF power contained in the resulting filtered signal is then measured by a Schottky diode (1200 V/W). The signal delivered by the Schottky diode is fed into a lock-in amplifier (LIA) for phase sensitive detection using the chopper frequency as the reference. The phase of the LIA was rotated to set the quadrature output to zero and the in-phase output was used as the measured heterodyne signal.

All signals are acquired using a multichannel National Instruments DAQ card (USB-6259). Data recorded are the in-phase and quadrature signals from the LIA, the DC signal from the photomixer, the temperature of the HW, and the DC signal from the calibration arm, if present. The QCL was wavelength tuned by current or temperature modulation to cover several absorption lines of CO2 and H2O in the region of 10.48 µm. For current modulation, a waveform generator provided a sawtooth wave to the laser driver (LDX-3232, ILX Lightwave) to modulate the current from 410 mA to 510 mA with a period of 100 s. For temperature modulation, commands were sent to the temperature controller to ramp the temperature linearly from −8 °C to 30 °C at a rate of 0.1 °C/s.

3. Laboratory characterization

Prior to solar measurements, the HW-LHR was characterized in the laboratory using a reference BB source (IR-301, Infrared Systems Development Corporation) at 1323 K as the test radiative input. Background signals, baseline effects, and signal to noise ratio were scrutinized in turn.

Ideally, the measured IF signal is proportional to the product of the received optical signal power from the BB and the LO power. In reality, several ‘dark’ signals may contribute to a non-zero offset, which must be accounted for in order to avoid any bias in the magnitude of the signal measured. These include the dark signal of the photomixer, excess RF power from the LO, and residual leakage of the direct signal into the IF chain. Under the test conditions (integration time of 100 ms), the total heterodyne signal Vhet was 16.39 μV, of which the compounded ‘dark’ signal contribution was 5% (0.80 μV). When performing atmospheric remote sensing, regular measurements of these dark contributions were made by blocking the optical inputs of the instrument.

As the QCL is tuned in frequency by either temperature or current modulation, the LO power emitted also varies. Since Vhet is directly proportional to the LO power, tuning the LO produces a baseline variation in the measured heterodyne spectra. To capture this physical information, and to later constrain the atmospheric retrieval, the DC output from the photomixer was used as a proxy measurement of the LO power. Two sets of calibration data were used: i) the physical relationship Vhet as a function of VDC obtained with the calibration BB (both signals corrected for dark contributions) was modelled by a quadratic polynomial, which indicates saturation effects and deviation from the ideal case; ii) the dependence of Vhet as a function of BB temperature was also established based on the expected signal power received by the instrument [4] for a range of BB temperatures (400 to 1300 K). Extrapolating these data, the scaling factor to estimate Vhet expected from an exo-atmospheric solar signal can be calculated.

With this approach a first estimation of the measurement baseline can be determined by measuring VDC during a wavelength sweep. Figure 3 shows an example of a heterodyne atmospheric spectrum recorded using temperature tuning of the QCL. Overlaid in a red solid line, is the estimated baseline, after further inclusion of a ∼75% flat absorption to account for broadband atmospheric and optics absorption.

 

Fig. 3. Example solar data from integrated LHR. The heterodyne signal (black line) is the background-corrected Vhet. The baseline (red line) was calculated from the background-corrected VDC. Measurements were made at 11.52 am (UTC) on November 17th 2017, at the Rutherford Appleton Laboratory (51.5714°N, 1.3154°W). The laser operating temperature was scanned between –8 °C and + 30 °C for constant current at 490 mA; the scan took 8 minutes.

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To characterize the noise of the HW-LHR, the measurement covariance matrix was calculated. A statistical sample was created from 100 measurements using the BB as the source. Operating conditions were identical to those later used for atmospheric sounding: the QCL temperature was set to 15 °C, and the laser current was ramped from 410 to 510 mA to produce the frequency tuning. The integration time per point was 100 ms, each scan comprised 500 sample points and the total acquisition time for a scan was 100 s. The measurement covariance matrix derived from the sample set is shown in Fig. 4(a). The matrix is mostly diagonal (limited cross-correlation between sampling points in the scan): this is further exhibited in Fig. 4(b), which isolates the diagonal and anti-diagonal elements. The diagonal elements represent the signal variance across the frequency scan. Using the measurement of Vhet, an estimate of the SNR across the scan can be made, and is shown in Fig. 4(c). This outcome has important implications in the atmospheric retrievals, as the measurement covariance matrix to be used will be diagonal, with the diagonal elements being experimentally measured.

 

Fig. 4. a) Heat map representation of the heterodyne signal covariance matrix calculated from a sample of 100 measurements using the BB source. b) Comparison of the diagonal and anti-diagonal values of the covariance matrix. c) Comparison of the measured and theoretical SNRs during a QCL scan. The measured SNR is degraded by a factor 1.6 compared to the ideal one.

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The expression of the noise of the heterodyne receiver when it is not dominated by the shot noise is given in Eq. (1), as the ratio of the post detection power received to the noise equivalent power (NEP). Both are expressed per unit of bandwidth before being divided. Eq. (1) explicitly includes the effect of the LHR sensitivity to polarization.

$$SNR = P \cdot \frac{1}{{NEP}} = \frac{{h \cdot \nu \cdot \kappa \sqrt {\frac{{2B \cdot \tau }}{{{\pi ^2}}}} }}{{\exp \left( {\frac{{h \cdot \nu }}{{k \cdot {T_{BB}}}}} \right) - 1}} \cdot \frac{1}{{\frac{{h \cdot \nu }}{{{\eta _{HET}}}} + \frac{A}{{2{P_{LO}} \cdot {D^{{\ast} 2}}}}}}$$
h and k are Planck’s and Boltzmann’s constants, respectively. The transmission of the BB radiation through the instrument to the photomixer, κ = 0.374, comprises: 2 × OAPM reflection (T = 0.98); HW coupling (0.896); HW propagation (0.988); BS transmission (ZnSe, 0.82); detector window transmission (BaF2, 0.94); and detector immersed lens (GaAs, 0.57). The LHR double side-band resolution, B = 2.03 GHz, was simulated piecewise based on the RF filter specification, and optimized by minimizing the residuals from lineshape fitting. The integration time, τ = 0.1 s, was defined by the integration constant of the LIA. The BB operates at TBB = 1323 K. PLO was the LO power incident on the detector, which varies during the frequency scan; the power of the full beam at the detector output was measured using a power meter, and was then corrected using the aperture function to infer the power on the detector area A (∼11%). D* is the normalized detectivity, and was 2.1 × 109 cm·√Hz/W at this frequency. The heterodyne efficiency is not specified by the detector manufacturer and must be estimated; ηHET = 0.442 is the quantum efficiency calculated from the responsivity provided by the manufacturer at this frequency, and is the upper limit of heterodyne efficiency. Under these conditions, and at LO frequency ν defined above, the ideal calculated SNR can be derived. As shown in Fig. 4(c), the SNR dependence as the LO power varies during the QCL frequency tuning is well described by the model, providing an additional factor 1.6 reduction is applied. This factor provides a figure of merit of instrument noise performance. Some of the discrepancy might originate from the use of the most optimistic heterodyne efficiency, which in reality tends to be lower than the quantum efficiency. Nevertheless, the metric is well in line with, and even better than, previous estimates obtained from the free-space bench top LHR [4, 1113].

4. Demonstration in solar occultation zenith sounding

With promising performances obtained during laboratory tests, the miniature HW-LHR is then used to demonstrate its first solar occultation atmospheric sounding. To do so, the instrument input port is coupled to the solar tracker, described in [11]. No other instrumental change is otherwise made.

Before starting the atmospheric measurements, the QCL frequency is calibrated using the diagnostic arm of the HW-LHR. Relative frequency calibration is determined from the etalon trace, with absolute frequency calibration anchored to the CO2 frequency transition at 954.545086 cm-1 as per the HITRAN 2016 database.

The raw data from the HW-LHR are then pre-processed: i) they are calibrated in absolute optical frequency using the QCL frequency calibration data, ii) dark signals are subtracted, iii) a first estimated transmittance spectrum is produced using the QCL power modulation correction as described above and shown in Fig. 3. The pre-processed spectra are then used as the measurement input to the atmospheric retrieval algorithm that will determine the optimum solution for the total column quantities.

The retrieval methodology and algorithm has been thoroughly described in [11]. Here we focus on describing the input data specific to the HW-LHR. The a priori profiles for CO2 were chosen to be constant in altitude, set to a volume mixing ratio of 400 ppm. The a priori covariance matrix for the CO2 profile was taken from O’Dell et al. [14]. For the H2O profile, data from the closest available radiosonde station (Larkhill, no 3743, released on 11/17/2017 12:00 UTC) were used. The a priori covariance matrix chosen was diagonal, and concentration values were set to a relative uncertainty of 10% and 50% for CO2 and H2O, respectively. Finally, the a priori quadratic baseline was modelled to a constant of 1 (in transmittance units) with relative uncertainty of 10% on the polynomial coefficients, since the baseline is mostly corrected using the procedure already described.

The covariance matrix describing the measurement error was constructed based on the measured one shown in Fig. 4, but with the off diagonal elements set to zero to ease numerical calculation.

The HW-LHR instrument lineshape is determined by the double side band RF response of the back end IF system. For the HW-LHR, the full electrical bandwidth of the photomixer was used, with the low frequencies (<25 MHz) rejected by a steep high pass filter. The RF response of the detector was modelled by an ideal first order low pass filter with a 3 dB cutoff frequency of 1 GHz as per specification. This cutoff frequency was then locally optimized to minimize lineshape residuals. The optimum cutoff frequency was found to be 1040 MHz.

Atmospheric profiles of pressure and temperature were taken from the previously mentioned radiosonde data.

For the demonstration experiments of the HW-LHR, two QCL tuning methods were tested: application of temperature and current ramps. Example spectra recorded in both cases, along with the fitted model produced by the retrievals, are shown in Fig. 5. Temperature scans are slower, but offer a wider tuning range (c.f. Fig. 3). The associated LO power modulation also tends to be less pronounced than that from current scans (0.13 mW/cm-1 and 0.20 mW/cm-1 for temperature and current tuning, respectively). For current scans, the laser current was tuned between 410-510 mA, with a constant laser temperature of 24 °C; this scan took 100 s, compared to 381 s for the temperature scan.

 

Fig. 5. Measured heterodyne spectra (black cross) and fitted model (red line). a) frequency tuning by laser temperature ramp on November 17th 2017 at 11:52 (UTC). b) frequency tuning by laser current ramp on October 3rd 2017 at 11:00 (UTC). Retrieved baselines are shown as a grey line. The fit residuals are shown in the bottom section of each plot (note different scale).

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The fit residuals, shown in the lower panels of Fig. 5(a) and 5(b), indicate good agreement with the atmospheric transmission model. The χ2/m parameter (with m the number of data points in the spectrum) is close to one, showing the measurement error was well estimated. Additional quality metrics on the retrieval include the degrees of freedom for signal (DFS) and the total Shannon information content (H). The former describes the number of independent parameters the inversion can retrieve, and the latter quantifies the amount of distinguishable atmospheric states by the observing system (2H) [15]. For Fig. 5(a), DFS = 6.6, H = 35 bits; and for Fig. 5(b), DFS = 5.5, H = 24 bits. From the retrieved profiles, the total columns can be calculated as well as their errors; these are given in the figures.

By all metrics, spectra obtained by temperature tuning of the laser frequency are of better quality. The noise equivalent transmission is 0.0085 and 0.0280 for the temperature and current scans, respectively. Given the ∼4 times longer acquisition time for the temperature scan, if the noise were white, only a factor 2 improvement would be expected for the temperature scan, but an improvement of 3.3 is observed. Contributing factors to the reduced performance using current tuning include excess noise introduced through external modulation of the current driver, and large laser power dynamic range introduced by the current scan (see increased residual at the high ν end of the spectrum, Fig. 5(b)).

These retrievals are not yet intended to provide reliable geophysical data, as the bias error budget has not been completed during this demonstration study. Currently the error budget includes the measurement error (propagation of the instrument SNR down to geophysical quantities), and the smoothing error originating from the finite vertical resolution at which the observing system estimates concentration distribution. These errors are propagated down to the total column measurements for CO2 and H2O, and are given in the graphs of Fig. 5. The CO2 total column deduced from the spectrum of Fig. 5(a) seems realistic (399.5 ± 2.2 ppm), whilst the one from Fig. 5(b) is not and appears to be affected by bias (443.9 ± 5.5 ppm). The residuals show some significant variations in the latter case.

5. Summary and outlook

The results reported demonstrate the first measurements of atmospheric constituents using a fully integrated miniaturized HW-LHR instrument. Despite its extremely compact size, the spectrometer is shown to resolve individual molecular lines in the thermal infrared through solar occultation atmospheric transmission measurements, from which concentrations can be deduced. In the best case, during this first demonstration, a measurement error of ∼2.2 ppm on the CO2 column was achieved for a ∼380 s measurement duration.

Analysis of the HW-LHR noise performance also provided highly promising results: the SNR was found to follow the theoretical expectations in terms of dependence on the LO power, and the performance was found to be 1.6 times worse than the ideal case. This result is better than any previously measured figure of merit for free space optical breadboard LHR.

The sensitivity of the first HW-LHR demonstrator can nevertheless be further improved, as particularly evidenced by the fact that the optimum LO power level was not reached. For this demonstration work, the photomixer was not optimally matched to the beam diameter, as only 11% of the spatial mode contributed to the mixing. According to the SNR model, full matching of the HW output port to the photomixer would increase the SNR by a factor ∼3.3. This is certainly an area for future improvement.

The hybrid optical integration approach demonstrated the scalability of the thermal infrared laser heterodyne spectro-radiometers. The HW-LHR enables the level of miniaturization and ruggedization required for nanosatellite or airborne small platforms, and this spectrometer technology is considered for the development of cubesat constellation missions for the study of the middle atmosphere [6, 16].

Funding

Science and Technology Facilities Council (Centre for Instrumentation); Natural Environment Research Council (NE/P003230/1).

Acknowledgements

We thank the STFC RAL Space Precision Development Facility (PDF) for mechanical design input and manufacturing of the HW and ancillary components. We thank the STFC Technology Department Metrology Facility for assistance with contact and optical metrology of optical components. Radiosonde data were downloaded through the University of Wyoming web portal.

Disclosures

DW: Mirico Ltd (I, E, P). Remaining authors declare no conflicts of interest.

References

1. R. T. Menzies and R. K. Seals, “Ozone monitoring with an infrared heterodyne radiometer,” Science 197(4310), 1275–1277 (1977). [CrossRef]  

2. D. Glenar, T. Kostiuk, D. E. Jennings, D. Buhl, and M. J. Mumma, “Tunable diode-laser heterodyne spectrometer for remote observations near 8 μm,” Appl. Opt. 21(2), 253–259 (1982). [CrossRef]  

3. G. Sonnabend, D. Wirtz, and R. Schieder, “Evaluation of quantum-cascade lasers as local oscillators for infrared heterodyne spectroscopy,” Appl. Opt. 44(33), 7170–7172 (2005). [CrossRef]  

4. D. Weidmann, W. J. Reburn, and K. M. Smith, “Ground-based prototype quantum cascade laser heterodyne radiometer for atmospheric studies,” Rev. Sci. Instrum. 78(073107), 1–10 (2007). [CrossRef]  

5. D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017). [CrossRef]  

6. D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020). [CrossRef]  

7. M. Jenkins, R. W. J. Devereux, and A. F. Blockley, “Hollow waveguide integrated optics: A novel approach to 10 μm laser radar,” J. Mod. Opt. 45, 1613–1627 (1998). [CrossRef]  

8. D. Weidmann, B. J. Perrett, N. A. Macleod, and R. M. Jenkins, “Hollow waveguide photomixing for quantum cascade laser heterodyne spectro-radiometry,” Opt. Express 19(10), 9074–9085 (2011). [CrossRef]  

9. I. Robinson, H. L. Butcher, N. A. Macleod, and D. Weidmann, “Hollow waveguide integrated laser spectrometer for 13CO2/12CO2 analysis,” Opt. Express 27(24), 35670–35688 (2019). [CrossRef]  

10. K. D. Laakmann and W. H. Steier, “Waveguides: characteristic modes of hollow rectangular dielectric waveguides,” Appl. Opt. 15(5), 1334–1340 (1976). [CrossRef]  

11. A. Hoffmann, N. A. Macleod, M. Huebner, and D. Weidmann, “Thermal infrared laser heterodyne spectroradiometry for solar occultation atmospheric CO2 measurements,” Atmos. Meas. Tech. 9(12), 5975–5996 (2016). [CrossRef]  

12. T. R. Tsai, R. A. Rose, D. Weidmann, and G. Wysocki, “Atmospheric vertical profiles of O3, N2O, CH4, CCl2F2, and H2O retrieved from external-cavity quantum-cascade laser heterodyne radiometer measurements,” Appl. Opt. 51(36), 8779–8792 (2012). [CrossRef]  

13. A. Hoffmann, M. Huebner, N. Macleod, and D. Weidmann, “Spectrally resolved thermal emission of atmospheric gases measured by laser heterodyne spectrometry,” Opt. Lett. 43(16), 3810–3813 (2018). [CrossRef]  

14. C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012). [CrossRef]  

15. C. D. Rodgers, “Information Aspects,” in Inverse Methods for Atmospheric Sounding, F. W. Taylor, ed., 1st ed. (World Scientific Publishing Co. Pte. Ltd, 2000), pp. 13–41.

16. F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018). [CrossRef]  

References

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  1. R. T. Menzies and R. K. Seals, “Ozone monitoring with an infrared heterodyne radiometer,” Science 197(4310), 1275–1277 (1977).
    [Crossref]
  2. D. Glenar, T. Kostiuk, D. E. Jennings, D. Buhl, and M. J. Mumma, “Tunable diode-laser heterodyne spectrometer for remote observations near 8 μm,” Appl. Opt. 21(2), 253–259 (1982).
    [Crossref]
  3. G. Sonnabend, D. Wirtz, and R. Schieder, “Evaluation of quantum-cascade lasers as local oscillators for infrared heterodyne spectroscopy,” Appl. Opt. 44(33), 7170–7172 (2005).
    [Crossref]
  4. D. Weidmann, W. J. Reburn, and K. M. Smith, “Ground-based prototype quantum cascade laser heterodyne radiometer for atmospheric studies,” Rev. Sci. Instrum. 78(073107), 1–10 (2007).
    [Crossref]
  5. D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
    [Crossref]
  6. D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
    [Crossref]
  7. M. Jenkins, R. W. J. Devereux, and A. F. Blockley, “Hollow waveguide integrated optics: A novel approach to 10 μm laser radar,” J. Mod. Opt. 45, 1613–1627 (1998).
    [Crossref]
  8. D. Weidmann, B. J. Perrett, N. A. Macleod, and R. M. Jenkins, “Hollow waveguide photomixing for quantum cascade laser heterodyne spectro-radiometry,” Opt. Express 19(10), 9074–9085 (2011).
    [Crossref]
  9. I. Robinson, H. L. Butcher, N. A. Macleod, and D. Weidmann, “Hollow waveguide integrated laser spectrometer for 13CO2/12CO2 analysis,” Opt. Express 27(24), 35670–35688 (2019).
    [Crossref]
  10. K. D. Laakmann and W. H. Steier, “Waveguides: characteristic modes of hollow rectangular dielectric waveguides,” Appl. Opt. 15(5), 1334–1340 (1976).
    [Crossref]
  11. A. Hoffmann, N. A. Macleod, M. Huebner, and D. Weidmann, “Thermal infrared laser heterodyne spectroradiometry for solar occultation atmospheric CO2 measurements,” Atmos. Meas. Tech. 9(12), 5975–5996 (2016).
    [Crossref]
  12. T. R. Tsai, R. A. Rose, D. Weidmann, and G. Wysocki, “Atmospheric vertical profiles of O3, N2O, CH4, CCl2F2, and H2O retrieved from external-cavity quantum-cascade laser heterodyne radiometer measurements,” Appl. Opt. 51(36), 8779–8792 (2012).
    [Crossref]
  13. A. Hoffmann, M. Huebner, N. Macleod, and D. Weidmann, “Spectrally resolved thermal emission of atmospheric gases measured by laser heterodyne spectrometry,” Opt. Lett. 43(16), 3810–3813 (2018).
    [Crossref]
  14. C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
    [Crossref]
  15. C. D. Rodgers, “Information Aspects,” in Inverse Methods for Atmospheric Sounding, F. W. Taylor, ed., 1st ed. (World Scientific Publishing Co. Pte. Ltd, 2000), pp. 13–41.
  16. F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
    [Crossref]

2020 (1)

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

2019 (1)

2018 (2)

A. Hoffmann, M. Huebner, N. Macleod, and D. Weidmann, “Spectrally resolved thermal emission of atmospheric gases measured by laser heterodyne spectrometry,” Opt. Lett. 43(16), 3810–3813 (2018).
[Crossref]

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

2017 (1)

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

2016 (1)

A. Hoffmann, N. A. Macleod, M. Huebner, and D. Weidmann, “Thermal infrared laser heterodyne spectroradiometry for solar occultation atmospheric CO2 measurements,” Atmos. Meas. Tech. 9(12), 5975–5996 (2016).
[Crossref]

2012 (2)

T. R. Tsai, R. A. Rose, D. Weidmann, and G. Wysocki, “Atmospheric vertical profiles of O3, N2O, CH4, CCl2F2, and H2O retrieved from external-cavity quantum-cascade laser heterodyne radiometer measurements,” Appl. Opt. 51(36), 8779–8792 (2012).
[Crossref]

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

2011 (1)

2007 (1)

D. Weidmann, W. J. Reburn, and K. M. Smith, “Ground-based prototype quantum cascade laser heterodyne radiometer for atmospheric studies,” Rev. Sci. Instrum. 78(073107), 1–10 (2007).
[Crossref]

2005 (1)

1998 (1)

M. Jenkins, R. W. J. Devereux, and A. F. Blockley, “Hollow waveguide integrated optics: A novel approach to 10 μm laser radar,” J. Mod. Opt. 45, 1613–1627 (1998).
[Crossref]

1982 (1)

1977 (1)

R. T. Menzies and R. K. Seals, “Ozone monitoring with an infrared heterodyne radiometer,” Science 197(4310), 1275–1277 (1977).
[Crossref]

1976 (1)

Alminde, L. K.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Antonini, K.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Barraclough, S.

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

Bell, W.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

Blockley, A. F.

M. Jenkins, R. W. J. Devereux, and A. F. Blockley, “Hollow waveguide integrated optics: A novel approach to 10 μm laser radar,” J. Mod. Opt. 45, 1613–1627 (1998).
[Crossref]

Bösch, H.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Brodersen, B. K.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Buhl, D.

Butcher, H. L.

Castano, R.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Christi, M.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Connor, B.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Devereux, R. W. J.

M. Jenkins, R. W. J. Devereux, and A. F. Blockley, “Hollow waveguide integrated optics: A novel approach to 10 μm laser radar,” J. Mod. Opt. 45, 1613–1627 (1998).
[Crossref]

Eldering, D.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Fisher, B.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Frankenberg, C.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Gabriele, A.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Glenar, D.

Griffin, D.

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

Gunson, M.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Havemann, S.

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

Hegglin, M. I.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Hoffmann, A.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

A. Hoffmann, M. Huebner, N. Macleod, and D. Weidmann, “Spectrally resolved thermal emission of atmospheric gases measured by laser heterodyne spectrometry,” Opt. Lett. 43(16), 3810–3813 (2018).
[Crossref]

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

A. Hoffmann, N. A. Macleod, M. Huebner, and D. Weidmann, “Thermal infrared laser heterodyne spectroradiometry for solar occultation atmospheric CO2 measurements,” Atmos. Meas. Tech. 9(12), 5975–5996 (2016).
[Crossref]

Huebner, M.

A. Hoffmann, M. Huebner, N. Macleod, and D. Weidmann, “Spectrally resolved thermal emission of atmospheric gases measured by laser heterodyne spectrometry,” Opt. Lett. 43(16), 3810–3813 (2018).
[Crossref]

A. Hoffmann, N. A. Macleod, M. Huebner, and D. Weidmann, “Thermal infrared laser heterodyne spectroradiometry for solar occultation atmospheric CO2 measurements,” Atmos. Meas. Tech. 9(12), 5975–5996 (2016).
[Crossref]

Jenkins, M.

M. Jenkins, R. W. J. Devereux, and A. F. Blockley, “Hollow waveguide integrated optics: A novel approach to 10 μm laser radar,” J. Mod. Opt. 45, 1613–1627 (1998).
[Crossref]

Jenkins, R. M.

Jennings, D. E.

Kostiuk, T.

Kurtz, J.

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

Laakmann, K. D.

Macleod, N.

A. Hoffmann, M. Huebner, N. Macleod, and D. Weidmann, “Spectrally resolved thermal emission of atmospheric gases measured by laser heterodyne spectrometry,” Opt. Lett. 43(16), 3810–3813 (2018).
[Crossref]

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

Macleod, N. A.

Martinez Pino, D.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

McDuffie, J.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Menzies, R. T.

R. T. Menzies and R. K. Seals, “Ozone monitoring with an infrared heterodyne radiometer,” Science 197(4310), 1275–1277 (1977).
[Crossref]

Middleton, K.

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

Miller, C. E.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Miyazaki, K.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Mumma, M. J.

Natraj, V.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Newman, S.

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

O’Brien, D.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

O’Dell, C. W.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Oyafuso, F.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Pastena, M.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Patel, G.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Perrett, B. J.

Polonsky, I.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Reburn, W. J.

D. Weidmann, W. J. Reburn, and K. M. Smith, “Ground-based prototype quantum cascade laser heterodyne radiometer for atmospheric studies,” Rev. Sci. Instrum. 78(073107), 1–10 (2007).
[Crossref]

Robinson, I.

Rodgers, C. D.

C. D. Rodgers, “Information Aspects,” in Inverse Methods for Atmospheric Sounding, F. W. Taylor, ed., 1st ed. (World Scientific Publishing Co. Pte. Ltd, 2000), pp. 13–41.

Rose, R. A.

Schieder, R.

Seals, R. K.

R. T. Menzies and R. K. Seals, “Ozone monitoring with an infrared heterodyne radiometer,” Science 197(4310), 1275–1277 (1977).
[Crossref]

Sioris, C.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Smith, F.

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

Smith, K. M.

D. Weidmann, W. J. Reburn, and K. M. Smith, “Ground-based prototype quantum cascade laser heterodyne radiometer for atmospheric studies,” Rev. Sci. Instrum. 78(073107), 1–10 (2007).
[Crossref]

Smyth, M.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Sonnabend, G.

Steier, W. H.

Taylor, T.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Toon, G. C.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Tsai, T. R.

Weidmann, D.

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

I. Robinson, H. L. Butcher, N. A. Macleod, and D. Weidmann, “Hollow waveguide integrated laser spectrometer for 13CO2/12CO2 analysis,” Opt. Express 27(24), 35670–35688 (2019).
[Crossref]

A. Hoffmann, M. Huebner, N. Macleod, and D. Weidmann, “Spectrally resolved thermal emission of atmospheric gases measured by laser heterodyne spectrometry,” Opt. Lett. 43(16), 3810–3813 (2018).
[Crossref]

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

A. Hoffmann, N. A. Macleod, M. Huebner, and D. Weidmann, “Thermal infrared laser heterodyne spectroradiometry for solar occultation atmospheric CO2 measurements,” Atmos. Meas. Tech. 9(12), 5975–5996 (2016).
[Crossref]

T. R. Tsai, R. A. Rose, D. Weidmann, and G. Wysocki, “Atmospheric vertical profiles of O3, N2O, CH4, CCl2F2, and H2O retrieved from external-cavity quantum-cascade laser heterodyne radiometer measurements,” Appl. Opt. 51(36), 8779–8792 (2012).
[Crossref]

D. Weidmann, B. J. Perrett, N. A. Macleod, and R. M. Jenkins, “Hollow waveguide photomixing for quantum cascade laser heterodyne spectro-radiometry,” Opt. Express 19(10), 9074–9085 (2011).
[Crossref]

D. Weidmann, W. J. Reburn, and K. M. Smith, “Ground-based prototype quantum cascade laser heterodyne radiometer for atmospheric studies,” Rev. Sci. Instrum. 78(073107), 1–10 (2007).
[Crossref]

Wennberg, P. O.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Wirtz, D.

Wunch, D.

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

Wysocki, G.

Appl. Opt. (4)

Atmos. Meas. Tech. (2)

C. W. O’Dell, B. Connor, H. Bösch, D. O’Brien, C. Frankenberg, R. Castano, M. Christi, D. Eldering, B. Fisher, M. Gunson, J. McDuffie, C. E. Miller, V. Natraj, F. Oyafuso, I. Polonsky, M. Smyth, T. Taylor, G. C. Toon, P. O. Wennberg, and D. Wunch, “The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations,” Atmos. Meas. Tech. 5(1), 99–121 (2012).
[Crossref]

A. Hoffmann, N. A. Macleod, M. Huebner, and D. Weidmann, “Thermal infrared laser heterodyne spectroradiometry for solar occultation atmospheric CO2 measurements,” Atmos. Meas. Tech. 9(12), 5975–5996 (2016).
[Crossref]

J. Mod. Opt. (1)

M. Jenkins, R. W. J. Devereux, and A. F. Blockley, “Hollow waveguide integrated optics: A novel approach to 10 μm laser radar,” J. Mod. Opt. 45, 1613–1627 (1998).
[Crossref]

Opt. Express (2)

Opt. Lett. (1)

Proc. SPIE (1)

D. Weidmann, K. Antonini, D. Martinez Pino, B. K. Brodersen, G. Patel, M. I. Hegglin, C. Sioris, W. Bell, K. Miyazaki, L. K. Alminde, A. Gabriele, M. Pastena, and A. Hoffmann, “Cubesats for monitoring atmospheric processes (CubeMAP): a constellation mission to study the middle atmosphere,” Proc. SPIE XXIV(115300U), 1–19 (2020).
[Crossref]

Q. J. R. Meteorol. Soc. (1)

F. Smith, S. Havemann, A. Hoffmann, W. Bell, D. Weidmann, and S. Newman, “Evaluation of laser heterodyne radiometry for numerical weather prediction applications,” Q. J. R. Meteorol. Soc. 144(1831), 1–20 (2018).
[Crossref]

Remote Sens. (1)

D. Weidmann, A. Hoffmann, N. Macleod, K. Middleton, J. Kurtz, S. Barraclough, and D. Griffin, “The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis,” Remote Sens. 9(1073), 1–20 (2017).
[Crossref]

Rev. Sci. Instrum. (1)

D. Weidmann, W. J. Reburn, and K. M. Smith, “Ground-based prototype quantum cascade laser heterodyne radiometer for atmospheric studies,” Rev. Sci. Instrum. 78(073107), 1–10 (2007).
[Crossref]

Science (1)

R. T. Menzies and R. K. Seals, “Ozone monitoring with an infrared heterodyne radiometer,” Science 197(4310), 1275–1277 (1977).
[Crossref]

Other (1)

C. D. Rodgers, “Information Aspects,” in Inverse Methods for Atmospheric Sounding, F. W. Taylor, ed., 1st ed. (World Scientific Publishing Co. Pte. Ltd, 2000), pp. 13–41.

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Figures (5)

Fig. 1.
Fig. 1. Schematic of the integrated HW-LHR. Electronic subsystem is given in grey lines. All optical components are integrated into the same substrate. The output from the heterodyne photomixer is split into a DC component and the IF component. The IF is filtered (HPF) to tailor the instrument lineshape and a Schottky diode (SD) measures the RF power prior to phase sensitive detection (LIA).
Fig. 2.
Fig. 2. Photograph of the integrated HW-LHR: (A) diagnostic output port (diagnostic components are removed); (B) beamsplitter; (C) photomixer; (D) LO input HW; (E) lens; (F) QCL; (G) solar/BB input HW; (H) HW substrate.
Fig. 3.
Fig. 3. Example solar data from integrated LHR. The heterodyne signal (black line) is the background-corrected Vhet. The baseline (red line) was calculated from the background-corrected VDC. Measurements were made at 11.52 am (UTC) on November 17th 2017, at the Rutherford Appleton Laboratory (51.5714°N, 1.3154°W). The laser operating temperature was scanned between –8 °C and + 30 °C for constant current at 490 mA; the scan took 8 minutes.
Fig. 4.
Fig. 4. a) Heat map representation of the heterodyne signal covariance matrix calculated from a sample of 100 measurements using the BB source. b) Comparison of the diagonal and anti-diagonal values of the covariance matrix. c) Comparison of the measured and theoretical SNRs during a QCL scan. The measured SNR is degraded by a factor 1.6 compared to the ideal one.
Fig. 5.
Fig. 5. Measured heterodyne spectra (black cross) and fitted model (red line). a) frequency tuning by laser temperature ramp on November 17th 2017 at 11:52 (UTC). b) frequency tuning by laser current ramp on October 3rd 2017 at 11:00 (UTC). Retrieved baselines are shown as a grey line. The fit residuals are shown in the bottom section of each plot (note different scale).

Equations (1)

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S N R = P 1 N E P = h ν κ 2 B τ π 2 exp ( h ν k T B B ) 1 1 h ν η H E T + A 2 P L O D 2

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