The present invention generally relates to the field of optical distance and length metrology and specifically to the field of coherent length metrology and laser radar.
Various techniques for precisely measuring distance to objects or thicknesses of objects by optical means are known. These techniques include laser triangulation, conoscopic holography, low-coherence interferometry, chromatic confocal point sensing, frequency modulated continuous-wave (FMCW) laser radar, swept-frequency optical coherence tomography, and phase modulation range finding. (See, e.g., M.-D. Amann, et al., “Laser ranging: a critical review of usual techniques for distance measurement,” Opt. Eng. 40(1) 10-19 (January 2001), F. Blateyron, Chromatic Confocal Microscopy, in Optical Measurement of Surface Topography, (Springer Berlin Heidelberg) pp 71-106 (2011), C. Olsovsky, et al., “Chromatic confocal microscopy for multi-depth imaging of epithelial tissue,” Biomed Opt Express. May 1, 2013; 4(5): 732-740, G. Y. Sirat et al., “Conoscopic holography,” Opt. Lett. 10, (1985), W. C. Stone, et al., “Performance Analysis of Next-Generation LADAR for Manufacturing, Construction, and Mobility,” NISTIR 7117, May 2004, and M. A. Choma, “Sensitivity advantage of swept source and Fourier domain optical coherence tomography,” Opt. Exp. 11 (18), 2183 (2003).) These techniques offer varying levels and combinations of measurement ranges, precisions, and resolutions.
Optical phase-sensitive detection techniques (also sometimes referred to as “coherent detection techniques”), such as low-coherence interferometry, optical coherence tomography and laser radar, can offer extremely high resolution, but face unique challenges in measuring diffusely scattering surfaces due to speckle, the far-field interference pattern arising from the multiple scattering centers of a diffuse reflector. For relative lateral motion (i.e. motion perpendicular to the laser beam propagation direction, and thus not a Doppler shift) between the laser beam and a rough surface (with roughness less than the system resolution), researchers at the National Institute of Standards and Technology (NIST) recently showed that speckle-induced phase variations place a “strong limit” on the achievable range uncertainty and precision using the FMCW laser radar technique. (See, E. Baumann, et. al, “Speckle phase noise in coherent laser ranging: fundamental precision limitations,” Opt. Lett., Vol. 39, Issue 16, pp. 4776-4779 (2014).) This reference (“Baumann”) is incorporated herein by reference in its entirety. The researchers showed that speckle noise resulting from surface roughness of a laterally moving surface (or laser beam) leads to a non-Gaussian range distribution with measurement errors that can dramatically exceed both the Cramer Rao lower bound and the surface roughness amplitude. Motion of the beam location on the sample surface degrades measurements significantly compared to the case where each successive point is measured statically, even to the point where outliers during lateral motion approach the system range resolution (given, by c/2B, where c is the speed of light and B is the information bandwidth). As a result, the use of FMCW laser radar for high-precision surface imaging at a distance, for instance, is limited to either static point-by-point measurements, spatial averaging, or they must endure degraded precision when the beam location on the sample surface is in motion. Unfortunately, such lateral motion is needed for a variety of applications including non-contact, in-situ industrial metrology and impression-based forensics evidence. Baumann identifies the speckle noise problem with no solution. Solutions to the surface roughness speckle noise problem are therefore needed.
A method is provided for measuring distance with improved measurement accuracy or precision, comprising: producing a first laser output; producing a second laser output; modulating an optical frequency of at least one of the first laser output or the second laser output; producing a combined beam, which is the combination of the first and second laser outputs; directing the combined beam through a plurality of optical paths, at least one of the optical paths including a sample, and the plurality of optical paths being configured to direct at least part of the combined beam onto at least one optical detector to produce an interference signal; distinguishing the interference signal contributions that are due to the first laser output from the interference signal contributions that are due to the second laser output; and processing first interference signal contributions that are due to the first laser output with second interference contributions that are due to the second laser output to lessen distance or displacement measurement errors that result from surface roughness or from dispersion properties of the sample or from dispersion properties of the optical path that includes the sample.
The first interference signal contributions may be distinguished from the second interference signal contributions by substantially optically separating the first and second laser outputs onto a corresponding first and second detector.
The first interference signal contributions may be distinguished from the second interference signal contributions by electrical bandpass filtering or digital bandpass filtering.
At least one of the first or second optical frequency modulations may be a carrier optical frequency chirp. Alternatively, at least one of the first or second optical frequency modulations may be an optical sideband chirp;
A carrier optical frequency chirp may be additionally modulated to produce at least one optical sideband on the optical carrier.
The processing step may include calculating a first signal phase and a second signal phase as functions of time corresponding to a received first interference signal and a received second interference signal, manipulating the first interference signal phase and the second interference signal phase as a function of time to suppress common-mode distance measurement errors that result from surface roughness or dispersion properties of the sample or of the optical path that includes the sample, thereby producing a corrected signal phase; and determining the distance to the sample with reduced distance errors based on the corrected signal phase.
The manipulating of the first and second interference signal phases may involve determining the sum or difference of the first interference signal phase and the second interference signal phase.
The determination of the first signal phase and second signal phases may be performed using Hilbert transforms.
The method may further comprise performing corrections to at least one of the first and second signal phases based on the wavelength and chirp rate of the first and second laser outputs to produce a corrected first and second signal phase.
A system is provided for separating up-chirp and down-chirp components of a sideband-modulated FMCW system, comprising: a physical device providing a laser output;
a modulator imparting chirped sidebands on a carrier optical frequency of the laser output, the chirped sidebands being separated in frequency; a beam splitter configured to split the modulated laser output into a first local oscillator (LO) portion and a second transmitted portion (TX); a frequency shifter configured to shift either or both of the LO and the TX in optical frequency in order to allow separation of the contributions of the chirped sidebands; a combiner configured to combine the LO and a receiver portion (RX); a detector configured to detect the interference signal resulting from the LO and the RX; and a processor configured to distinguish the interference signal contributions that are due to different chirped sidebands and to use the separated interference signal contributions to determine a target range.
A method is provided of processing distance measurements to improve measurement accuracy or precision, comprising: producing a laser output; modulating the optical frequency of the laser output or modulating a sideband of the optical frequency of the laser output to produce a modulated laser output; directing the modulated laser output through a plurality of optical paths at least one of the optical paths including a sample, the plurality of optical paths being configured to direct at least part of the modulated laser output onto at least one optical detector to produce an interference signal; computing deviations of the interference signal amplitude, frequency, or phase from established amplitude, frequency, or phase functions or values in either the frequency domain or the time domain; identifying, weighting, or disregarding distance measurements based one or more metrics that quantify the computed deviations from the established amplitude, frequency, or phase functions or values; and utilizing the identification, weighting, or disregarding of measurements to improve the accuracy of one or more distance measurements to the sample.
The range peak shape in the frequency domain may be compared to an exemplary range peak shape. The root-mean-square deviations of the signal phase as a function of time may be compared to an established value. The signal-to-noise ratio may be compared to an established signal-to-noise ratio value.
A method is provided of processing distance measurements to improve measurement accuracy or precision, comprising: producing a first laser output; producing a second laser output; modulating at least one of a first optical frequency of the first laser output, and a second optical frequency of the second laser output; producing a combined beam which is the combination of the first and second laser outputs; directing the combined beam through a plurality of optical paths, at least one of the optical paths including a sample, the plurality of optical paths being configured to direct at least part of the combined beam onto at least one optical detector to produce an interference signal; distinguishing the interference signal contributions that are due to the first laser output from the contributions that are due to the second laser output wherein the interference signals result from laser outputs for which dispersion in the sample or the optical path to the sample are substantially the same; and processing the first and second interference signals to determine the distance to the sample with reduced dispersion-induced distance errors.
At least one of the laser outputs may be modulated with a linear chirp;
The processing may include calculating a first and a second signal phase as a function of time corresponding to the received first and second interference signal; and calculating the sum or difference of the first and the second signal phases as a function of time to substantially suppress common-mode measurement errors and to produce a corrected signal phase.
The first interference signal and the second interference signal may result from the same laser output, but at different times.
The first interference signal may result from a first laser output and the second interference signal may result from a second laser output.
The invention described herein teaches how multiple optical phase-sensitive measurements can be made of a surface and used to significantly suppress phase noise-induced distance measurement errors during lateral motion, such as those due to speckle. In each embodiment described, a difference in phase-sensitivity to the sample surface distance between the multiple measurements is used to suppress the phase noise-induced errors.
A measurement may be defined as the time-varying phase of the interference between light received from a reference surface and a sample surface for a single laser. It is understood that additional surfaces and lasers may also be considered. A depiction of a system that may perform two simultaneous measurements using two separate lasers is shown in
ELO(t,z=0)=E0e−i(ω
where ω0 is the angular optical frequency at the beginning of the chirp, and α is the angular chirp rate. Propagation of the LO field to the sample surface can be treated by performing a Fourier transform to the frequency domain.
The LO field is then propagated to the sample surface and back to the reference surface, where it interferes with the LO field, by applying a Taylor expanded form of the propagator eiβz.
ERx(ω,z=2R)=E(ω,z=0)ei2β
Here R is the distance to the sample surface, and
Also, c is the speed of light, n is the refractive index of the medium between the reference and sample surfaces, and νg is the group velocity in the medium. The time-domain description of the field reflected from sample surface, back to the LO surface, is given by
where
The interference between the fields ELO and ERx comprises a single distance measurement, and takes the form
For many cases, terms involving β2 and β12 can be neglected, and the signal can be adequately approximated by
However, we have included terms to second order in equation (5) to aid the discussion in later sections of this document.
FMCW Carrier Measurements for Compensating Phase Noise-Induced Errors
As shown in
The first frequency-chirped laser 110 and the second frequency-chirped laser 115 each output light of an optical frequency that changes substantially linearly (chirps) in time over a given chirp duration.
The beam combiner 120 is configured to receive and combine at least part of the first and second laser outputs into a combined laser output. In some embodiments, a single laser may produce an output with both frequency-chirped components, in which case the beam combination occurs internal to the laser.
The combined laser output from the beam combiner 120 is then directed through the circulator 130 and a plurality of optical paths configured to direct at least part of the combined beam onto an optical detector to produce an interference signal.
In
A sum of LO and Rx is directed to the detection and processing circuit to determine the distance measurement, as noted below.
In some embodiments of the invention, the optical phase-sensitive measurements may be performed using the FMCW ladar technique, and where the optical carrier may be linearly swept, or “chirped”, in time. “Performance Analysis of Next-Generation LADAR for Manufacturing, Construction, and Mobility,” (cited above) describes the FMCW chirped ladar technique and is incorporated herein by reference in its entirety. A simplified block diagram showing a setup that may be used to compensate speckle noise is shown in
However, when the sample surface is rough, using the measurement of the distance from just one of the frequency-swept lasers may result in distance errors due to speckle. These errors may increase dramatically when the sample surface is translated perpendicularly to the beam propagation direction (e.g. scanning the beam across the surface or vice versa).
Measurement Method
To solve the problem noted above, the disclosed embodiments teach how the use of two simultaneous distance measurements with different phase sensitivities on the surface distance can mitigate the speckle and other phase noise effects. In some embodiments of the invention, the different phase sensitivities are achieved by chirping the two lasers at different chirp rates. Even though both lasers are used to measure a single distance, for one chirp rate, the phase of the received signal evolves at one rate in time, while for the second chirp, the phase of the received signal evolves at a different rate in time. Conversely, it is important to note that the phase noise caused by speckle is common-mode for the two measurements, and can therefore be removed while maintaining the distance information. The measurement setup shown in
The following is a mathematical description for speckle phase error compensation of FMCW laser radar measurements from a diffuse target with surface roughness σz, where σz «ΔR, and ΔR=c/2B is the distance measurement resolution. The mathematical model relies on discretizing the sample plane into a uniform grid of j cells, and assigning a random height zj to each grid cell as shown in
The measured FMCW distance signal is a sum of the returns from each grid cell in the sample plane,
where κ is the laser chirp rate, νo is the laser start frequency, and zj is the distance to the jth grid cell. One can express equation (7) in polar form as,
where
and Θ(t) and A(t) are defined by equation (7). (See, P. Pavlicek, et. al. “Theoretical measurement uncertainty of white-light interferometry on rough surfaces,” Appl. Opt. 42, 1809-1813 (2003).) Due to the small surface roughness, and in the limit that the measurement bandwidth is small compared to the laser frequency ν0, the phase and amplitude functions can be approximated by first order Taylor expansions: Θ(t)≈Θ0+Θ1t, and A(t)≈A0+A1t. In this regime, the range errors due to speckle take the form, δz=c/2πκΘ1−z0. Equations (7) and (8) were developed to describe the complicated behavior of the amplitude and phase of coherent distance measurements from diffuse surfaces. References Baumann and Pavlicek both describe the degradation of their respective measurements due to speckle from diffuse surfaces, but offer no solutions for compensating the measured phase errors. In the following paragraphs we will describe how to use two FMCW laser radar measurements with different sensitivities of the phase to the sample distance to compensate speckle-induced phase errors.
Without compensation, these phase excursions can result in range errors that are on the order of the distance measurement resolution ΔR=c/2B.
This case can be described by equation (8), with first order Taylor expansions of the phase and amplitude functions, for time intervals where the phase fluctuations Θ are approximately linear. The entire measurement duration is then modeled by combining many sequential regions defined by first-order Taylor expansions in Θ and A. If the two lasers are sufficiently close in wavelength, and the surface roughness is sufficiently small, the speckle phases for the two measurements are approximately equal at every point in time [Θ1(t)≈Θ2(τ)]. The condition for measuring correlated speckle phase with lasers 1 and 2 is provided in equation (9).
Finally, the phases from the two separate measurements may be combined to form a “compensated phase” whose range may depend only on the average distance to the sample z0, and the two laser chirp rates. A linear fit of the compensated phase may then be performed to extract the phase slope (e.g. the angular frequency) of the compensated range peak from which the distance measurement may be calculated. These steps are shown mathematically in equations (10) and (11).
Chirped Sideband FMCW
As shown in
In some embodiments of the invention, the optical phase-sensitive measurements may be performed using the FMCW ladar technique, and where the waveforms used may include frequency-chirped sideband modulation (i.e. homodyne rather than heterodyne) following U.S. Pat. No. 7,742,152 “Coherent Detection Scheme for FM Chirped Laser Radar”. U.S. Pat. No. 7,742,152 is incorporated herein by reference in its entirety. In U.S. Pat. No. 7,742,152, the authors describe a “signal fading” problem that hinders the measurements during motion. We have determined that this signal fading is a result of the fact that, while two phase-sensitive measurements are present, the two measurements cannot be easily distinguished. This is because the two phase-sensitive measurements utilize sideband chirps with opposite signs (i.e. one is increasing in frequency and one is decreasing in frequency), but the same chirp rate magnitude. In this case, the “up” and “down” frequency chirps are measured at common or similar RF frequencies because the measurements are performed symmetrically about DC. As shown in
To separate and utilize the two, phase-sensitive measurements, the disclosed embodiment shows that by shifting the measurement off of DC, the up and down chirps can be made to not share similar RF frequencies and the measurements can be made without signal fading because they don't interfere with one another.
In
Measurement Filtering
The non-specular reflectivity of diffuse surfaces introduces the possibility for multipath interference in FMCW measurements of rough surfaces. Multipath interference refers to secondary reflections or scattering of the measurement beam between two or more surface features that may ultimately scatter back into the receiver. Multipath interference may cause time-varying phase shifts that result in errors in FMCW range measurements. These errors may become more pronounced when the sample undergoes lateral motion due to the rapid phase evolution of the interfering reflections. Specifically, large range errors may be observed in cases where the separation between the contributing surface features is sufficiently large that the inequality expressed in equation (9) is no longer valid. In such cases, the speckle-induced phase may not be well compensated by the measurement approach described in the previous section, and the resulting FMCW range measurement can exhibit errors on the order of the FMCW range resolution. FMCW measurements made on several types of rough surfaces indicate that the locations where multipath interferences occur, the spatial frequency of these effects, and the magnitude of the measurement errors may have the following properties: Their locations and magnitudes may be repeatable; the spatial frequency and magnitude of the errors are dependent on the material type; and the statistics of resulting range errors may not be Gaussian. Measurements of Lambertian scattering materials may exhibit more frequent and larger magnitude range errors while measurements of pseudo-diffuse materials, those that appear diffuse at low observance angles but reflective at high observance angles, yield less frequent and smaller magnitude range errors. Examples of range errors due to multipath interference are shown in
Fortunately, measurements that exhibit large range errors due to multipath interference contain signatures that may allow for detection of the errors. Once detected the errors may either be weighted or removed from the data set.
The disclosed embodiments teach two filtering methods to detect measurements containing large range errors. Both methods rely on the idea that peaks containing interference from multiple unresolved surface features may often be deformed as a result of the multi-surface interference, compared to an ideal single specular reflection. One embodiment uses peak shape analysis to detect misshapen peaks. In this embodiment, the FMCW range peak may first be fit with a Gaussian or other appropriate function. Next, the root-mean-squared error (RMSE) between the measured peak and the fit function may be computed. Finally, the RMSE is compared against a threshold value to identify peaks containing large range errors. In situations where multiple range measurements are averaged, the threshold value may be computed based on the statistics of the RMSE values for the set of points being averaged. In single-point measurement scenarios the threshold may be computed in the same way as for averaged measurements using the assumption that the average peak SNR changes slowly compared to the measurement rate.
The second embodiment for filtering compares the range peak SNR and the RMSE of the signal phase to detect misshapen range peaks. This embodiment was used to filter both data sets shown in
The data sets in
Dispersion Compensation of FMCW Measurements
In measurement scenarios where the target, the beam delivery optics, or the optical medium between the reference surface and sample surface has dispersion the ½(α−α′)t2 term in equation (5) may become significant, and the dispersion may require compensation to produce accurate distance measurements. Fortunately, compensation of such measurements can be achieved by averaging an up-chirp and down-chirp measurement that cover roughly the same spectral region, and have approximately the same, but opposite sign, chirp rate. In practice this can be accomplished by averaging temporally sequential up and down chirps from the same chirped laser source. This technique will be illustrated by considering a measurement where the reference surface and the sample surface are separated by 0.5 m of SMF-28 fiber. The dispersion coefficient for SMF-28 is β2=−0.022 ps2/m, and the group velocity is νg=c/1.4682 at 1550 nm. For this example the measurement duration will be 200 μs, and the chirp rate will be 600 MHz/μs. At the end of the measurement (tc=200 μs) the up-chirp (e.g. αup>0) will have accumulated an FMCW phase of ϕu=αuβ1ztc+½(αu−α′u)tc2. The accumulated phase for each term in ϕu is given by αuβ1ztc=3669.4 rad, and ½(αu−α′u)tc2=0.0063 rad. That ½(αu−α′u)tc2>0 reflects the fact that αu>α′u for the up-chirp. For the down-chirp the accumulated FMCW phase at the end of the measurement follows the same relation, ϕd=αdβ1ztc+½(αd−α′d)tc2. However, for the down-chirp αdβ1ztc=−3669.4 rad, whereas ½(αd−α′d)tc2=0.0063 rad. We can now use equation (11) to calculate the distance between the reference and sample surfaces. Due to the dispersion phase term the up-chirp measurement appears too long by ˜2 ppm, and the down-chirp measurement appears too short by ˜2 ppm. However, the averaged distance measurement,
provides the correct answer.
Using Phase Reconstruction to Compensate Phase Noise-Induced Distance Measurement Errors
As described in previous sections, compensation of phase-noise-induced distance measurement errors due to speckle for coherent ladar measurements may be important for obtaining accurate and precise measurements of dynamic and diffuse targets. In this section, we demonstrate an effective method for accomplishing the processing involved with this compensation using phase reconstruction, as shown in
As shown in
The up-chirp time-domain beat determination element 810 is configured to determine an up-chirp time-domain beat fup(t).
The up-chirp phase reconstruction element 820 is configured to reconstruct an up-chirp phase ϕup(t) based on the up-chirp time-domain beat fup(t).
The element for correction of the up-chirp for λ and κ differences 830 is configured to correct the up-chirp phase reconstruction ϕup(t) based on λ and κ differences to generate a corrected up-chirp phase reconstruction ϕ′up(t).
The down-chirp time-domain beat determination element 840 is configured to determine a down-chirp time-domain beat fdown(t)
The down-chirp phase reconstruction element 850 is configured to reconstruct a down-chirp phase ϕdown(t) based on the down-chirp time-domain beat fdown(t).
The element for correction of the down-chirp for λ and κ differences 860 is configured to correct the down-chirp phase reconstruction ϕdown(t) based on λ0 and κ differences to generate a corrected down-chirp phase reconstruction ϕ′down(t).
The averaging element 870 is configured to average the corrected up-chirp phase reconstruction ϕ′up(t) and the corrected down-chirp phase reconstruction ϕ′down(t) to generate an average phase reconstruction ϕavg(t).
The construction element 880 is configured to construct a corrected signal fcorr(t) based on the average phase reconstruction ϕavg(t).
This application is a continuation of U.S. patent application Ser. No. 15/680,076, filed Aug. 17, 2017, which is a continuation of U.S. patent application Ser. No. 14/926,750, filed Oct. 29, 2015 and issued as U.S. Pat. No. 9,784,560 on Oct. 10, 2017, which claims the filing benefit of U.S. Provisional Application No. 62/069,917, filed Oct. 29, 2014, and U.S. Provisional Application No. 62/181,820, filed Jun. 19, 2015. These applications, and issued patent, are incorporated by reference herein in their entirety and for all purposes.
Number | Name | Date | Kind |
---|---|---|---|
3925666 | Allan et al. | Dec 1975 | A |
4593368 | Fridge et al. | Jun 1986 | A |
4795253 | Sandridge et al. | Jan 1989 | A |
4830486 | Goodwin | May 1989 | A |
5115468 | Asahi et al. | May 1992 | A |
5294075 | Vertatschitsch et al. | Mar 1994 | A |
5367399 | Kramer | Nov 1994 | A |
5371587 | De Groot et al. | Dec 1994 | A |
5534993 | Ball et al. | Jul 1996 | A |
5548402 | Nogiwa | Aug 1996 | A |
5768001 | Kelley et al. | Jun 1998 | A |
5859694 | Galtier et al. | Jan 1999 | A |
6034976 | Mossberg et al. | Mar 2000 | A |
6516014 | Sellin et al. | Feb 2003 | B1 |
6822742 | Kalayeh et al. | Nov 2004 | B1 |
6864983 | Galle et al. | Mar 2005 | B2 |
7215413 | Soreide et al. | May 2007 | B2 |
7292347 | Tobiason et al. | Nov 2007 | B2 |
7511824 | Sebastian et al. | Mar 2009 | B2 |
7742152 | Hui et al. | Jun 2010 | B2 |
7920272 | Sebastian et al. | Apr 2011 | B2 |
8010300 | Stearns et al. | Aug 2011 | B1 |
8121798 | Lippert et al. | Feb 2012 | B2 |
8175126 | Rakuljic et al. | May 2012 | B2 |
8294899 | Wong | Oct 2012 | B2 |
8582085 | Sebastian et al. | Nov 2013 | B2 |
8730461 | Andreussi | May 2014 | B2 |
8781755 | Wang | Jul 2014 | B2 |
8913636 | Roos et al. | Dec 2014 | B2 |
9030670 | Warden et al. | May 2015 | B2 |
9559486 | Roos et al. | Jan 2017 | B2 |
9696423 | Martin | Jul 2017 | B2 |
9759597 | Wong | Sep 2017 | B2 |
9784560 | Thorpe et al. | Oct 2017 | B2 |
9864060 | Sebastian et al. | Jan 2018 | B2 |
9970756 | Kreitinger et al. | May 2018 | B2 |
10247538 | Roos et al. | Apr 2019 | B2 |
20020071122 | Kulp et al. | Jun 2002 | A1 |
20030043437 | Stough et al. | Mar 2003 | A1 |
20040088113 | Spoonhower et al. | May 2004 | A1 |
20040105087 | Gogolla et al. | Jun 2004 | A1 |
20050078296 | Bonnet | Apr 2005 | A1 |
20050094149 | Cannon | May 2005 | A1 |
20060050270 | Elman | Mar 2006 | A1 |
20060162428 | Hu et al. | Jul 2006 | A1 |
20060203224 | Sebastian et al. | Sep 2006 | A1 |
20080018881 | Hui et al. | Jan 2008 | A1 |
20080018901 | Groot | Jan 2008 | A1 |
20090046295 | Kemp et al. | Feb 2009 | A1 |
20090110004 | Chou | Apr 2009 | A1 |
20090153872 | Sebastian et al. | Jun 2009 | A1 |
20090257622 | Wolowelsky et al. | Oct 2009 | A1 |
20100007547 | D'Addio | Jan 2010 | A1 |
20100091278 | Liu et al. | Apr 2010 | A1 |
20100131207 | Lippert et al. | May 2010 | A1 |
20110069309 | Newbury et al. | Mar 2011 | A1 |
20110164783 | Hays et al. | Jul 2011 | A1 |
20110205523 | Rezk et al. | Aug 2011 | A1 |
20110213554 | Archibald et al. | Sep 2011 | A1 |
20110273699 | Sebastian et al. | Nov 2011 | A1 |
20110292403 | Jensen et al. | Dec 2011 | A1 |
20120038930 | Sesko et al. | Feb 2012 | A1 |
20120106579 | Roos et al. | May 2012 | A1 |
20120293358 | Itoh | Nov 2012 | A1 |
20130104661 | Klotz et al. | May 2013 | A1 |
20140002639 | Cheben et al. | Jan 2014 | A1 |
20140036252 | Amzajerdian et al. | Feb 2014 | A1 |
20140139818 | Sebastian et al. | May 2014 | A1 |
20140204363 | Slotwinski et al. | Jul 2014 | A1 |
20150019160 | Thurner et al. | Jan 2015 | A1 |
20150185313 | Zhu | Jul 2015 | A1 |
20160123718 | Roos et al. | May 2016 | A1 |
20160123720 | Thorpe et al. | May 2016 | A1 |
20160202225 | Feng et al. | Jul 2016 | A1 |
20160259038 | Retterath et al. | Sep 2016 | A1 |
20160261091 | Santis et al. | Sep 2016 | A1 |
20170097274 | Thorpe et al. | Apr 2017 | A1 |
20170097302 | Kreitinger et al. | Apr 2017 | A1 |
20170115218 | Huang et al. | Apr 2017 | A1 |
20170131394 | Roger et al. | May 2017 | A1 |
20170191898 | Rella et al. | Jul 2017 | A1 |
20170343333 | Thorpe et al. | Nov 2017 | A1 |
20180188369 | Sebastian et al. | Jul 2018 | A1 |
20180216932 | Kreitinger et al. | Aug 2018 | A1 |
20190013862 | He | Jan 2019 | A1 |
20190170500 | Roos et al. | Jun 2019 | A1 |
20190285409 | Kreitinger et al. | Sep 2019 | A1 |
Number | Date | Country |
---|---|---|
2010127151 | Nov 2010 | WO |
2014088650 | Jun 2014 | WO |
2016064897 | Apr 2016 | WO |
2018170478 | Sep 2018 | WO |
2019060901 | Mar 2019 | WO |
2019070751 | Apr 2019 | WO |
2019079448 | Apr 2019 | WO |
2019099567 | May 2019 | WO |
Entry |
---|
“International Search Report and Written Opinion received for PCT/US2015/058051 dated Jan. 19, 2016”. |
Amann, et al., ““Laser ranging: a critical review of usual techniques for distance measurement,” Optical Engineering, vol. 40(1) pp. 10-19 (Jan. 2001)”. |
Barber, et al., ““Accuracy of Active Chirp Linearization for Broadband Frequency Modulated Continuous Wave Ladar,” Applied Optics, vol. 49, No. 2, pp. 213-219 (Jan. 2010)”. |
Barker, , ““Performance enhancement of intensity-modulated laser rangefinders on natural surfaces””, SPIE vol. 5606, pp. 161-168 (Dec. 2004). |
Baumann, et al., ““Speckle Phase Noise in Coherent Laser Ranging: Fundamental Precision Limitations,” Optical Letters, vol. 39, Issue 16, pp. 4776-4779 (Aug. 2014)”. |
Blateyron, , ““Chromatic Confocal Microscopy, in Optical Measurement of Surface Topography,” Springer Berlin Heidelber, pp. 71-106 (Mar. 2011)”. |
Boashash, , ““Estimating and Interpreting the Instantaneous Frequency of a Signal-Part 2: Algorithms and Applications””, Proceedings of the IEEE, vol. 80, No. 4, pp. 540-568 (Apr. 1992). |
Bomse, et al., ““Frequency modulation and wavelength modulation spectroscopies: comparison of experimental methods using a lead-salt diode laser””, Appl. Opt., 31, pp. 718-731 (Feb. 1992). |
Choma, et al., ““Sensitivity Advantage of Swept Source and Fourier Domain Optical Coherence Tomography,” Optical Express, vol. 11, No. 18, 2183 (Sep. 2003)”. |
Ciurylo, , ““Shapes of pressure- and Doppler-broadened spectral lines in the core and near wings””, Physical Review A, vol. 58 No. 2, pp. 1029-1039 (Aug. 1998). |
Dharamsi, , “A theory of modulation spectroscopy with applications of higher harmonic detection”, J. Phys. D: Appl. Phys 29, pp. 540-549 (Jun. 1995; 1996) (Retrieved Jan. 16, 2017). |
Emran, Bara J. et al., “Low-Altitude Aerial Methane Concentration Mapping”, School of Engineering, The University of British Columbia, Aug. 10, 2017, pp. 1-12. |
Fehr, et al., ““Compact Covariance Descriptors in 3D Point Clouds for Object Recognition””, 2012 IEEE International Conference on Robotics and Automation, pp. 1793-1798, (May 2012). |
Fransson, Karin et al., “Measurements of VOCs at Refineries Using the Solar Occultation Flux Technique”, Department of Radio and Space Science, Chalmers University of Technology, 2002, 1-19. |
Fujima, et al., ““High-resolution distance meter using optical intensity modulation at 28 GHz””, Meas. Sci. Technol. 9, pp. 1049-1052 (May 1998). |
Gilbert, et al., ““Hydrogen Cyanide H13C14N Absorption Reference for 1530 nm to 1565 nm Wavelength Calibration—SRM 2519a””, NIST Special Publication 260-137 2005 ED, 29 pages, (Aug. 2005). |
Guest, “Numerical Methods of Curve Fitting”, Cambridge University Press; Reprint edition, ISBN: 9781107646957 (Dec. 2012). |
Harald, “Mathematical Methods of Statistics”, Princeton University Press, ISBN 0-691-08004-6 (1946). |
Hariharan, “Basics of Interferometry”, Elsevier Inc. ISBN 0-12-373589-0 (2007). |
Iiyama, et al., “Linearizing Optical Frequency-Sweep of a Laser Diode for FMCW Reflectrometry”, Iiyama et al. Journal of Lightwave Technology, vol. 14, No. 2, Feb. 1996. |
Iseki, et al., “A Compact Remote Methane Sensor using a Tunable Diode Laser”, Meas. Sci. Technol., 11, 594, pp. 217-220 (Jun. 2000). |
Jia-Nian, et al., ““Etalon effects analysis in tunable diode laser absorption spectroscopy gas concentration detection system based on wavelength modulation spectroscopy””, IEEE SOPO, pp. 1-5 (Jul. 2010). |
Johnson, et al., ““Using Spin-Images for Efficient Object Recognition in Cluttered 3D Scenes””, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, No. 5, 37 pages (Published May 1999). |
Karlsson, et al., “Linearization of the frequencysweep of a frequency-modulated continuous-wave semiconductor laser radar and the resulting ranging performance”, Christer J. Karlsson et al, Applied Optics, vol. 38, No. 15, May 20, 1999, pp. 3376-3386. |
Karmacharya, et al., ““Knowledge guided object detection and indentification in 3D point clouds””, SPIE 9528, 952804-952804-13 (Jun. 2015). |
Lenz, Dawn et al., “Flight Testing of an Advanced Airborne Natural Gas Leak Detection System”, ITT Industries Space Systems Division, Oct. 2005, all. |
Lu, et al., “Differential wavelength-scanning heterodyne interferometer for measuring large step height”, Applied Optics, vol. 41, No. 28, Oct. 1, 2002. |
Masiyano, et al., ““Use of diffuse reflections in tunable diode laser absorption spectroscopy: implications of laser speckle for gas absorption measurements””, Appl. Phys. B 90, pp. 279-288 (Feb. 2008). |
Mather, T.A. et al., “A reassessment of current volcanic emissions from the Central American arc with specific examples from Nicaragua”, Journal of Volcanology and Geothermal Research, Nov. 2004, 297-311. |
Ngo, et al., ““An isolated line-shape model to go beyond the Voigt profile in spectroscopic databases and radiative transfer codes””, Journal of Quantitative Spectroscopy and Radiative Transfer, 129, pp. 89-100 (Nov. 2013). |
Olsovsky, et al., ““Chromatic Confocal Microscopy for Multi-depth Imaging of Epithelial Tissue,” Biomedical Optics Express, vol. 4, No. 5, pp. 732-740 (May 2013)”. |
Paffenholz, “Direct geo-referencing of 3D point clouds with 3D positioning sensors”, (Doctoral Thesis), Leibniz Universität Hannover, 138 pages (Sep. 2012). |
Polyanksy, et al., “High-Accuracy CO2 Line Intensities Determined from Theory and Experiment”, Physical Review Letters, 114, 5 pages (Jun. 2015). |
Rao, “Information and the accuracy attainable in the estimatin of statistical parameters”, Bull. Calcutta Math. Soc., 37,pp. 81-89 (1945, reprinted 1992) (Retrieved Jan. 10, 2017). |
Riris, et al., ““Airborne measurements of atmospheric methane column abundance using a pulsed integrated-path differential absorption lidar””, Applied Optics, vol. 51, No. 34, pp. 8296-8305 (Dec. 2012). |
Roos, et al., “Ultrabroadband optical chirp linearization for precision metrology application”, Optics Letters, vol. 34 No. 23, pp. 3692-3694 (Dec. 2009). |
Roos, et al., “Ultrabroadband optical chirp linearization for precision metrology applications”, Optics Letters, vol. 34, Issue 23, pp. 3692-3694 (2009). |
Rothman, et al., ““The HITRAN 2008 molecular spectroscopic database””, Journal of Quantitative Spectroscopy & Radiative Transfer, 110, pp. 533-572 (Jul. 2009). |
Rusu, et al., ““Fast Point Feature Histograms (FPFH) for 3D Registration””, IEEE Int. Conf. Robot., pp. 3212-3217 (May 2009). |
Sandsten, et al., ““Volume flow calculations on gas leaks imaged with infrared gas-correlation””, Optics Express, vol. 20, No. 18, pp. 20318-20329 (Aug. 2012). |
Sheen, et al., “Frequency Modulation Spectroscopy Modeling for Remote Chemical Detection.” PNNL 13324 (Sep. 2000). |
Sheen, , ““Frequency Modulation Spectroscopy Modeling for Remote Chemical Detection””, PNNL 13324, 51 pages (Sep. 2000). |
Silver, ““Frequency-modulation spectroscopy for trace species detection: theory and comparison among experimental methods””, Appl. Opt., vol. 31 No. 6, pp. 707-717 (Feb. 1992). |
Sirat, et al., ““Conoscopic Holography,” Optics Letters, vol. 10, No. 1 (Jan. 1985)”. |
Sivananthan, , Integrated Linewidth Reduction of Rapidly Tunable Semiconductor Lasers Sivananthan, Abirami, Ph.D., University of California, Santa Barbara, 2013, 206; 3602218. |
Stone, et al., ““Performance Analysis of Next-Generation LADAR for Manufacturing, Construction, and Mobility,” NISTIR 7117 (May 2004)”. |
Thoma, Eben D. et al., “Open-Path Tunable Diode Laser Absorption Spectroscopy for Acquisition of Fugitive Emission Flux Data”, Journal of the Air & Waste Management Association (vol. 55), Mar. 1, 2012, 658-668. |
Twynstra, et al., ““Laser-absorption tomography beam arrangement optimization using resolution matrices””, Applied Optics, vol. 51, No. 29, pp. 7059-7068 (Oct. 2012). |
Xi, et al., “Generic real-time uniorm K-space sampling method for high-speed swept-Source optical cohernece tomography”, Optics Express, vol. 18, No. 9, pp. 9511-9517 (Apr. 2010). |
Zakrevskyy, et al., ““Quantitative calibration- and reference-free wavelength modulation spectroscopy””, Infrared Physics & Technology, 55, pp. 183-190 (Mar. 2012). |
Zhao, et al., ““Calibration-free wavelength-modulation spectroscopy based on a swiftly determined wavelength-modulation frequency response function of a DFB laser””, Opt. Exp., vol. 24 No. 2, pp. 1723-1733 (Jan. 2016). |
Zhao, Yanzeng et al., “Lidar Measurement of Ammonia Concentrations and Fluxes in a Plume from a Point Source”, Cooperative Institute for Research in Environmental Studies, University of Colorado/NOAA (vol. 19), Jan. 2002, 1928-1938. |
U.S. Appl. No. 16/966,451 titled “Apparatuses and Methods for Gas Flux Measurements” filed Jul. 30, 2020. |
Number | Date | Country | |
---|---|---|---|
20190383596 A1 | Dec 2019 | US |
Number | Date | Country | |
---|---|---|---|
62181820 | Jun 2015 | US | |
62069917 | Oct 2014 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 15680076 | Aug 2017 | US |
Child | 16551075 | US | |
Parent | 14926750 | Oct 2015 | US |
Child | 15680076 | US |