Abstract

We discuss a maritime surveillance and detection concept based on Raman scattering of water molecules. Using a range-gated scanning lidar that detects Raman scattered photons from water, the absence or change of signal indicates the presence of a non-water object. With sufficient spatial resolution, a two-dimensional outline of the object can be generated by the scanning lidar. Because Raman scattering is an inelastic process with a relatively large wavelength shift for water, this concept avoids the often problematic elastic scattering for objects at or very close to the water surface or from the bottom surface for shallow waters. The maximum detection depth for this concept is limited by the attenuation of the excitation and return Raman light in water. If excitation in the UV is used, fluorescence can be used for discrimination between organic and non-organic objects. In this paper, we present a lidar model for this concept and discuss results of proof-of-concept measurements. Using published cross section values, the model and measurements are in reasonable agreement and show that a sufficient number of Raman photons can be generated for modest lidar parameters to make this concept useful for near-surface detection.

© 2018 Optical Society of America

1. INTRODUCTION

In discussions on physical security at maritime facilities, we became aware that automated detection of objects near the water surface presents a challenge for current technologies, especially for shallow littoral zones where the scattering environment is complex. Optical systems that utilize elastic scattering, such as the underwater laser-imaging system (UWLIS) [1], the airborne laser mine detection system (ALMDS) [2,3], and others, have been developed for underwater detection. Such systems rely on a contrast of the scattering signal from water and the objects of interest, which can be difficult to detect near the surface, especially when automated detection is required and the objects are dark without distinct reflectance features.

In this paper, we discuss a maritime detection concept based on Raman scattering by water molecules. It is proposed that an imaging lidar detects Raman scattering from water between the surface and a depth of a few attenuation lengths. The absence or change of Raman signal indicates the presence of a non-water object. With sufficient spatial resolution, a two-dimensional outline of the object can be generated. For objects below the surface, the detection signal can be enhanced by proper range gating. The detection depth is limited by overall attenuation of the incident beam and Raman scattered light.

For visible or ultraviolet (UV) light, the OH stretch band of liquid water has Raman shifts around 3400cm1. This provides ample spectral separation between excitation and Raman light and allows for elastic scattering to be practically eliminated by proper spectral filtering. Only passive backgrounds, such as solar or artificial lighting, would contribute to signal and noise for the proposed concept. A lidar system that measures the passive background can subtract it, and only the noise level is affected when the passive signal is comparable to the Raman signal. Thus, this concept is expected to work well close to the water surface and can be complementary to other technologies, such as ALMDS, which is capable of detection at significant depths.

Here we consider this concept and present a lidar model of the Raman scattering process for a body of water. Using published values of the cross section, it is shown that sufficiently large numbers of Raman photons are produced to make this concept attractive and, potentially, useful for many applications. Among potential applications are automated security in littoral regions, near-surface mine detection, discovery and mapping of floating or near-surface objects in day/night wide area searches, and other applications. Of particular interest is mapping of objects close to the surface where wave motion would make it difficult to interpret signals for elastic scattering-based technologies. If excitation in the UV range is used, the presence or absence of fluorescence from objects can add to discrimination capability. We also present results of proof-of-concept measurements using the Sandia Ares lidar at 355 nm excitation [4]. Three water samples were measured: bottled drinking water, Pacific Ocean water, and San Francisco Bay water. For the bottled-water sample, the measurements and the lidar model results are in good agreement, assuming attenuation of incident and Raman light based on published values for pure water. These measurements indicate that the proposed detection concept is feasible and provides sufficient signal photons for moderate lidar parameters.

2. RAMAN CROSS SECTION

Raman scattering is an inelastic process in which a photon loses or gains energy by changing an energy level of the scattering molecule. For incident polarized light and scattered natural light, the band-integrated differential Raman cross section is denoted by dσ(θ,ϕ)/dΩ, where θ is the scattering angle, and ϕ is the angle between the incident light polarization direction and the scattering plane (the plane formed by the incident and outgoing directions). Several measurements of this cross section are reported in the literature for the 3400cm1 OH stretch vibrational mode of water molecules and for excitation at λ=488nm [511]. The published value in Ref. [10] for θ=90°, for incident perpendicular polarized light, or ϕ=90°, is 8.2×1030cm2molecule1sr1. The angular dependence of this cross section is discussed in [10,11] and is given by

dσ(θ,ϕ)dΩ=dσ(θ=90°,ϕ=90°)dΩ{2ρ+(1ρ)(cos2θcos2ϕ+sin2ϕ)1+ρ},
where ρ is the depolarization ratio, which for water is 0.17 based on measurements [11]. For θ=180°, applicable to the lidar detection considered here (for co-located source and detector), Eq. (1) shows that the cross section is equal to dσ(θ=90°,ϕ=90°)/dΩ that is reported in the literature.

The dependence of the liquid water Raman cross section on wavelength is expressed in the literature [1214] by

dσ(θ=90°,ϕ=90°)dΩ=Aνs4(νi2νp2)2,
where νs is the scattered frequency, νp is the excitation frequency, the coefficient A=5.33×1027cm2molecule1sr1, and the resonance frequency νi88,000cm1 for water [13]. Note that here we use frequency and wavenumber interchangeably, where the wavenumber is given in terms of wavelength by ν(cm1)=1×107/λ(nm). At 488 nm incident light, νp=20492cm1, νs=204923400=17092cm1, and the result of Eq. (2) is 8.5×1030cm2molecule1sr1, which is close to the above value. At 355 nm incident light, the wavelength at which lidar measurements discussed later in this paper are made, νp=28169cm1, νs=24769cm1, and the differential Raman scattering cross section is 4.2×1029cm2molecule1sr1. In this paper, only liquid water is considered. Other applications, such as cloud and ice thickness measurements, use Raman cross sections and spectra for water vapor and ice [1517].

3. LIDAR MODEL

The lidar model considered here is for a pencil beam and one detector pixel. At the water surface, given the incidence angle and beam polarization, the refracted beam angle and intensity are known from basic optics. As the refracted beam propagates in water, it will be attenuated and undergo Raman scattering. The lidar is assumed sufficiently far from the surface so that only photons scattered close to 180° are in the detector field of view. These photons will nearly follow the reverse path of the incident beam and will also be partly reflected at the water–air interface. An illustration of the lidar and beam propagation is shown in Fig. 1.

 

Fig. 1. Illustration of lidar beam incidence, refraction at the air–water interface, and return Raman light. The range is R and s is the path length along the propagation direction in the water.

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Along the beam path, at distance s from the surface, the differential number of Raman photons produced in thickness ds per unit area of beam, per unit time, and in solid angle ΔΩ is

dNR=Ib(t,s)ϵbdσ(θ=180°)dΩNWdsΔΩ,
where Ib(t,s) is the beam intensity at time t and path length s, NW is the number density of water molecules, and ϵb is the energy of an incident photon. As the beam propagates in water, it will be attenuated due to absorption and scattering by the factor exp(μs), where μ is the attenuation coefficient of the incident light in the water in units of meter1. The generated Raman light is also attenuated with an attenuation coefficient μR. Integrating Eq. (3) over the beam cross section, the intensity is replaced with the local beam power.

Consider the time dependence of the detected Raman signal, let t=0 be measured from the start of the beam pulse at the lidar location, and let the lidar beam pulse shape be given by Pb(t). For a differential segment of the beam pulse at time t and width dt, Raman photons produced at path length s in the water will arrive at the detector at time τ=t+2R/c+2s/c, where R is the range from the lidar to the water surface, and c and c are the speeds of light in air and water, respectively. The factor of 2 accounts for the round-trip time. The differential energy measured by the detector for this beam segment from Raman photons produced in path length ds is

dER(τ,s)=Pb(t)dtexp[(μ+μR)s]ds(dσdΩNWλbλR)L,
where λb and λR are the incident and Raman wavelengths, respectively, and L is the product of the lidar and propagation factors, namely, atmospheric transmissions, refracted fractions of incoming and outgoing light at the water–air interface, solid angle of the receiver (ΔΩ), overall lidar system optical efficiency, and the lidar overlap factor (fraction of light collected by the receiver that is focused on the detector aperture). The total detected Raman energy for a pulse is obtained by integrating Eq. (4) over the interaction thickness of water sminssmax and over the beam pulse width, resulting in
ERTotal=L(dσdΩNWλbλR)1β0ΔTdtPb(t)[exp(βsmin)exp(βsmax)],
where ΔT is the pulse width and β=(μ+μR) is the overall attenuation coefficient. For a detector time gate of delay D and width W, signal is only detected for τ in the range DτD+W. In terms of the water path length, this corresponds to
smin=[D(2R/c+t)]c/2,smax=[D+W(2R/c+t)]c/2,
subject to the constraints of the water extent, that is, smin,smax>0 and smin,smax<ST, where ST is the path length at the target location (that blocks the beam) or at the maximum water depth.

A. Numerical Estimate of Raman Photons

Consider a quick estimate of the expected number of Raman photons for a single pulse to get an idea of the expected signals and therefore the feasibility of the concept. Lidar parameters similar to those for the proof-of-concept measurements will be used. For this example, the transmissions and refracted fractions are set to unity (propagation normal to the water surface), thus L=ΔΩηLidar, where ηLidar is the overall lidar optical efficiency. Also consider the limiting case of zero gate delay (smin=0), a wide gate (smax=ST), and neglect attenuation in water, that is, β0 and limβ0[1exp(βST)]/β=ST. For these limits, Eq. (5) reduces to

ER=(dσdΩNWλbλR)ΔΩηLidarEBeamST,
where EBeam is the pulse energy, and ΔΩ=ALidar/R2 (ALidar is the area of the lidar aperture and R is the range). The number density of water is NW3.34×1022molecules/cm3. For EBeam=30mJ per pulse at 355 nm, a collection aperture of 20 cm diameter, range of 100 m, ηLidar=0.1, water thickness ST=10cm, and the liquid water cross section of 4.2×1029cm2molecule1sr1 at 355 nm, we obtain ER1.1×1010mJ/pulse. This corresponds to 2.2×105 Raman photons at λR=404nm. Even if this number is spread over 1000 pixels for an imaging lidar, the number of detected Raman photons is 220 per pixel per pulse, which can be detected at high SNR. From a photon budget perspective, this shows that the concept presented here is feasible for modest lidar parameters. More detailed analysis of the lidar model is provided elsewhere [18].

B. Solar Background

For daytime applications, the solar background is relevant to the concept discussed here. For nighttime, other backgrounds such as lunar and passive lighting would need to be considered, but they are expected to be much smaller than the solar.

The spectral solar irradiance reaching a water surface as a function of wavelength can be estimated using the Moderate Resolution Atmospheric Transmission code MODTRAN [19]. Spectral irradiance is the radiative power incident on a surface per unit area per unit wavenumber (spectral radiative flux) and is given in units of watts per cm2 per cm1 in MODTRAN. Figure 2 shows a MODTRAN estimate of the solar spectral irradiance. The integrated value of this spectrum (summing over all spectral bins and multiplying by the bin width of 50cm1) is 9.01×102W/cm2. This is slightly less than the solar constant of 2.0 calories per cm2 per minute [20], or 0.139W/cm2 due to the effect of atmospheric attenuation.

 

Fig. 2. MODTRAN calculation of solar spectral irradiance. MODTRAN options: “Direct solar Irradiance,” zero zenith angle, zero altitude above sea level, “Mid-latitude Winter” atmospheric model, and 23 km visibility aerosol model. The spectral resolution or width per spectral bin is 50cm1.

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An estimate of the solar energy detected by the lidar for each pulse in the Raman spectral range is obtained by assuming diffuse reflection of solar light at the water surface and is given by

ESolar=(ΔkdkS(k))ΔΩ2πρSurfaceAFOVT(kR)WηLidar,
where S(k) is the solar spectral irradiance, Δk is the lidar Raman channel spectral width, ρSurface is an effective reflectance of the water surface, AFOV is the area of water surface in the field of view of the lidar, and T(kR) is the atmospheric transmission. The other terms are as defined previously. Equation (8) excludes the case of direct solar glint, which is orders of magnitude higher and needs to be avoided in application of the detection concept discussed here. The area AFOV=πR2ΘFOV2, where ΘFOV is the field-of-view angle of the lidar system. Thus, ΔΩ AFOV=πALidarΘFOV2 is independent of the lidar range R. Similarly, the solar background given by Eq. (8) is independent of range, except for the effect of atmospheric transmission. This is in contrast to the Raman signal, which has 1/R2 dependence, and implies that for any lidar there is a maximum detection range where noise from the solar background will dominate the Raman signal.

For a numerical estimate of the solar background, consider similar parameters to the previous section: ALidar=314cm2, gate width W=100ns, ηLidar=0.1, and Θ=1.0 milliradians. Near λR=404nm, S(k)1.3×106W/cm2/cm1. Consider a spectral interval of width 10 nm around λR, which corresponds to Δk610cm1. This interval is sufficient to contain the Raman signal for liquid water. For an upper limit estimate, we use T(kR)=1.0 and ρSurface=1.0, resulting in ESolar1.25×1012mJ per pulse. This value is much smaller than the Raman energy estimated in the previous section, and thus the solar background is expected to be negligible for the proof-of-concept measurements discussed here. However, because of the scaling with the different parameters and the possibility of spreading the beam over multiple pixels, the solar background has to be considered in modeling for any specific application, and the instrument needs to be designed with the capability to measure this background.

4. ATTENUATION IN WATER

Many measurements of light attenuation in a wide spectral range are reported in the literature. For pure water, the attenuation coefficient is a strong function of wavelength with a minimum of 0.025m1 in the visible region near 480 nm [2123]. Figure 3 shows this dependence along with the attenuation for the corresponding Raman wavelength. For natural waters, the attenuation strongly depends on particulate and organic matter content and can vary by several orders of magnitude at the same wavelength [24,25]. For clear ocean water, [23] it shows similar dependence of the attenuation on wavelength as Fig. 3, with a minimum slightly less than 0.025m1. This indicates that the effect of the salt content on attenuation is negligible in the wavelength range of interest.

 

Fig. 3. Attenuation coefficient of pure water based on [21]. Also shown are the attenuation coefficient at the corresponding Raman wavelength and the summed coefficients.

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For the proof-of-concept measurements presented in the next section, at 355 nm excitation and Raman at 404 nm, the attenuation coefficients of pure water are 0.20m1 and 0.06m1, respectively, based on Fig. 3. Thus, β=(μ+μR) in Eq. (5) is 0.26m1, corresponding to attenuation length of 3.8m.

From Fig. 3, the optimum wavelength for pure water is in the range 425–450 nm for the proposed detection concept. For green light at 532 nm, the overall attenuation coefficient is estimated at 0.35m1, which is worse than for UV at 355. However, the effect of particulates and organic matter is expected to result in much worse attenuation for UV light. Since the Raman cross section is also a strong function of wavelength, the optimum excitation wavelength will depend on the particular water conditions for the application.

5. PROOF-OF-CONCEPT MEASUREMENTS

The Sandia Ares lidar [4] and a water column with a movable target were used to demonstrate the detection concept and validate the number of detected Raman photons estimated by the model. A schematic of the Ares lidar is shown in Fig. 4. The Ares laser (commercial Big Sky Laser CFR200) generates a nominal 30 mJ, 10ns wide pulse at 355 nm and is operated at 30 Hz. Elastic back-scattered, Raman, and laser-induced fluorescence (LIF) light is collected by an 18.8 cm telescope and directed to a long-pass dichroic beam splitter, which reflects light with wavelengths shorter than 360nm, effectively separating the elastically backscattered laser light from the LIF and the Raman scattered light at 404 nm for the 3400cm1 band for water. LIF and Raman light is detected by a time-gated intensified charge-coupled device (CCD, Andor iStar ICCD) with a spectrally resolved channel of 512 spectral bins from 295 to 730 nm. This channel has no sensitivity below 360 nm due to the dichroic beam splitter. The elastic backscattered light is detected by a time-resolved photo-multiplier tube (PMT), which is used for ranging and setting the ICCD time gate. For each laser pulse, in addition to the spectrum, the passive background spectrum is also measured.

 

Fig. 4. Schematic diagram of the Ares UV-LIF lidar system at 355 nm.

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The measurement setup is shown in Fig. 5. The water column is a horizontal stainless steel pipe that is 152 cm in length and 14.0 cm. in diameter with several ports that allow insertion of an expandable target to serve as a beam stop at specific depths along the water column. Fused silica windows on both ends of the pipe were used and resulted in small beam losses estimated at 14%. The lidar was located 70m away from the pipe front window. At this range, the lidar overlap factor is about 22% (see below), and the beam spot size is less than 5 cm in diameter. The pulse energy was manually measured before and following the measurements. For all measurements the detector gain was adjusted to avoid saturation. Calibration factors at various gain settings are available from past measurements. The lidar overlap factor is a measure of the fraction of collected light that is focused on the detector and is estimated as a function of lidar range using atmospheric nitrogen (N2) Raman measurements as shown in Fig. 6.

 

Fig. 5. Left: The Ares lidar mounted in a trailer with beam aligned for horizontal propagation. Right: horizontal water pipe used for the Raman measurements. The pipe is 152 cm long and 14.0 cm in diameter with fused silica windows on both ends. The ports in the pipe were used for placing a target to set the water depth. The pipe front window is located 70m from the lidar.

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Fig. 6. Spectrally integrated N2 Raman signal and range-corrected signal versus range for the Ares lidar. The measured signal is normalized to maximum of unity. Also shown is the ratio of measured counts to range-corrected counts, which is the overlap factor of the lidar LIF channel. These measurements are for horizontal beam propagation in air with a gate delay of 0.05μs relative to the lidar range and a width of 0.1 μs, corresponding to a width of 15 m of air.

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Three water samples were measured: (1) pure bottled water, (2) Pacific Ocean water, and (3) San Francisco Bay water. The first water sample was bottled water, and the Raman spectra are shown in Fig. 7 for several target locations. Figure 8 shows the summed spectra over the spectral range 390–410 nm, along with scaled (1exp[βST]) model dependence using β=0.26m1, where ST is the target location. This model results from Eq. (5) in the limit of a wide gate relative to the pulse width (smin=0 and smax=ST). For these measurements, the expandable target allowed a small fraction of the beam to escape (10% as estimated using a green paper fluorescent target behind the rear window). The correction used in Fig. 8 and other details of the measurements are discussed in Ref. [18].

 

Fig. 7. Pure water Raman spectra with target at various locations along the water column. The spectra are normalized to 500 pulses. For all measurements the gate delay is 50ns with respect to the front window, the width is 100 ns, and the detector gain setting is at 50. The manually measured pulse energy is 30mJ.

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Fig. 8. Summed and corrected counts of the spectra in Fig. 7 versus target location. The last location at 152 cm. has no target but is the end of the tube. The dashed curve is the model fit based on an overall attenuation coefficient of β0.26m1.

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When attenuation in water is neglected, we earlier estimated 2.2×105 Raman photons per pulse for EBeam=30mJ/pulse, ΔΩ=A/R2 with R=100m, A=πd2/4, d=20cm, ηTotal=0.1, and a water thickness ST=10cm. Scaling this to the Ares measurement for the first target location ST=16.5cm (using R=70m, d=18.8cm, overlap factor=0.22 at the lidar range based on Fig. 6), for the same pulse energy and optical efficiency, the scaled number of photons per pulse is 1.4×105 photons. From Fig. 8, the corrected Raman signal is 1.0×107 counts for 500 pulses or 2.0×104 counts per pulse for the first target location. This corresponds to 4.0×104 photons after application of the lidar absolute calibration factor at the detector gain setting (previous absolute calibrations, using a standard lamp, at a gain setting of 250, resulted in 110counts/photon at 500 nm with accuracy to within a factor of two. The relative calibration factor between gain settings of 50 and 250 is 224 based on past relative calibration measurements). This number of photons is roughly within a factor of three of the model-obtained value, which is reasonable given the uncertainties in the parameters that were used (the optical efficiency is likely smaller than the 10% that was used—10% is based on measurements that were done several years ago). Therefore, these measurements give us confidence that the proposed detection concept has sound basis and the lidar model can be used for reasonable estimates of photon budgets.

Similar measurements were carried out for the ocean and SF Bay samples. The spectra are shown in Figs. 9 and 10 and show significant fluorescence, likely from organic matter. The organic content can be significantly different depending on location and water type [24,25]. To obtain the H2O Raman counts requires partitioning of the Raman and fluorescence spectra. After partitioning, the maximum Raman counts were used to obtain an estimate of β4.5m1 for the ocean sample and β17.0m1 for the SF Bay sample, assuming the maximum signals reached asymptotic values. Even at β of 17m1, a sufficient number of Raman photons is expected from the first 10 cm of water to allow for detection of objects just below the surface. It should be noted that the ocean and bay samples were obtained very close to the shoreline and therefore might not be accurate representations of these bodies of water. For all measurements reported here, the daytime passive background (ambient solar) is significantly smaller than the H2O Raman signals for the same detector gate width [18].

 

Fig. 9. Spectra for the ocean water sample at several target locations. All spectra are normalized to 500 pulses. The gate delay is 16ns, the gate width is 100 ns, and the gain setting is 100. At this gain setting, the detector calibration factor is 4.9 relative to the gain setting of 50 used in Fig. 7 (counts are divided by this factor to get equivalent counts at gain setting of 50). The manually measured laser energy is 7.5mJ/pulse. After partitioning of the Raman and fluorescence spectra, the summed Raman signal at the maximum target location is 1.7×107 counts for 500 pulses.

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Fig. 10. Spectra for the San Francisco Bay water sample at several target locations and normalized to 500 pulses. All measurement parameters are the same as in Fig. 9. After partitioning of the Raman and fluorescence spectra, the summed Raman signal is 4.5×106 counts for 500 pulses.

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6. CONCLUSIONS

The proof-of-concept measurements presented in this paper show that the proposed concept of using changes in water Raman scattering signals for detection of objects close to water surfaces is sound and could potentially complement other optical detection technologies in the region where elastic scattering is problematic. Lidar measurements of the Raman signal for the pure water sample at varying target positions are consistent with an overall attenuation coefficient of 0.26m1 for an incident beam at 355 nm and Raman at 404 nm. Measurements of water samples from the Pacific Ocean and the San Francisco Bay show much larger attenuation coefficients estimated at 4.5 and 17m1 for these two samples, respectively. The large attenuation is likely from organic matter content in the water. Longer wavelengths are expected to result in better penetration depths, especially for waters with high organic content. Even with the high attenuation and modest lidar parameters, sufficient Raman photons are generated to make near-surface detection of objects feasible using this concept.

In this paper, we discussed the general detection concept without a specific detection algorithm. It is anticipated that detection algorithms will need to be developed for specific applications and instruments; these algorithms will result in sensitivity and detection limits based on the lidar model. Because of the large variation of Raman signal for different waters, it is assumed for this detection concept that the water is reasonably uniform on the scale length of detection objects of interest. Under this condition, a detection algorithm can consider changes in Raman signal in the vicinity of the object, rather than the absolute value of the signals.

The measurements reported in this paper utilized the available Ares lidar with its gated ICCD to detect the Raman spectrum for demonstration of the detection concept. For a practical application, it is likely advantageous to use multiple PMTs, filtered for specific spectral bands, to detect the time-resolved Raman and fluorescence signals. The time-dependent Raman signals are expected to provide a clear target pattern without needing to set a time gate, making for easier and more precise target detection. The passive background is the PMT signal at long times after complete attenuation of the beam and decay of any fluorescence.

Funding

Sandia National Laboratories; U.S. Department of Energy’s National Nuclear Security Administration (DE-NA0003525).

Acknowledgment

The authors acknowledge Tom Kulp, Don Sheaffer, and Will Bolton for useful discussions and feedback.

This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

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References

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  1. T. J. Kulp, D. Garvis, R. Kennedy, T. Salmon, and K. Cooper, “Development and testing of a synchronous-scanning underwater imaging system capable of rapid two-dimensional frame imaging,” Appl. Opt. 32, 3520–3530 (1993).
    [Crossref]
  2. M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
    [Crossref]
  3. “AN/AES-1 Airborne laser mine detection system (ALMDS),” http://www.globalsecurity.org/military/systems/aircraft/systems/an-aes-1.htm .
  4. R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.
  5. C. H. Chang and L. A. Young, “Seawater temperature measurements from Raman spectra,” (Advanced Research Projects Agency, 1972).
  6. N. P. Romanov and V. S. Shuklin, “Raman scattering cross section of liquid water,” Opt. Spectrosc. 38, 646–648 (1975).
  7. R. B. Slusher and V. E. Derr, “Temperature dependence and cross sections of some Stokes and anti-Stokes Raman lines in ice Ih,” Appl. Opt. 14, 2116–2120 (1975).
    [Crossref]
  8. I. I. Kondilenko, P. A. Korotkov, V. A. Klimenko, and O. P. Demyanenko, “Transverse cross section of the Raman scattering of the u1 vibration of the water molecule in the liquid and gaseous states,” Opt. Spectrosc. 43, 384–386 (1978).
  9. S. Sugihara, M. Kishino, and M. Okami, “Contribution of Raman scattering to upward irradiance in the sea,” J. Oceanogr. Soc. Japan 40, 397–404 (1984).
    [Crossref]
  10. B. R. Marshall and R. C. Smith, “Raman scattering and in-water ocean optical properties,” Appl. Opt. 29, 71–84 (1990).
    [Crossref]
  11. G. W. Kattawar and X. Xu, “Filling in of Fraunhofer lines in the ocean by Raman scattering,” Appl. Opt. 31, 6491–6500 (1992).
    [Crossref]
  12. W. K. Bischel and G. Black, “Wavelength dependence of Raman scattering cross sections from 200–600  nm,” AIP Conf. Proc. 100, 181–187 (1983).
    [Crossref]
  13. G. W. Faris and R. A. Copeland, “Wavelength dependence of the Raman cross section for liquid water,” Appl. Opt. 36, 2686–2688 (1997).
    [Crossref]
  14. J. S. Bartlett, K. J. Voss, S. Sathyendranath, and A. Vodacek, “Raman scattering by pure water and seawater,” Appl. Opt. 37, 3324–3332 (1998).
    [Crossref]
  15. V. Rizi, M. Iarlori, G. Rocci, and G. Visconti, “Raman lidar observations of cloud liquid water,” Appl. Opt. 43, 6440–6453 (2004).
    [Crossref]
  16. F. Liu and F. Yi, “Spectrally resolved Raman lidar measurements of gaseous and liquid water in the atmosphere,” Appl. Opt. 52, 6884–6895 (2013).
    [Crossref]
  17. S. M. Pershin, V. N. Lednev, V. K. Klinkov, R. N. Yulmetov, and A. F. Bunkin, “Ice thickness measurements by Raman scattering,” Opt. Lett. 39, 2573–2575 (2014).
    [Crossref]
  18. I. R. Shokair, M. S. Johnson, R. L. Schmitt, and S. Sickafoose, “Concept for maritime near-surface surveillance using water Raman scattering,” (Sandia National Laboratories, 2016).
  19. L. W. Abreu and G. P. Anderson, “The MODTRAN® 2/3 report and LOWTRAN 7 model,” Ontar Corporation for PL/GPOS (1996).
  20. R. C. Weast, ed., Handbook of Chemistry and Physics, 66th ed. (CRC Press, 1985), section F-156.
  21. G. M. Hale and M. R. Querry, “Optical constants of water in the 200-nm to 200  µm wavelength region,” Appl. Opt. 12, 555–563 (1973).
    [Crossref]
  22. J. D. Jackson, Classical Electrodynamics, 2nd ed. (Wiley, 1975).
  23. R. C. Smith and K. S. Baker, “Optical properties of the clearest natural waters (200–800  nm),” Appl. Opt. 20, 177–184 (1981).
    [Crossref]
  24. C. D. Mobley, Radiative Transfer in the Ocean (Academic, 2001).
  25. D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
    [Crossref]

2014 (1)

2013 (1)

2004 (1)

2003 (1)

M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
[Crossref]

1998 (1)

1997 (1)

1995 (1)

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

1993 (1)

1992 (1)

1990 (1)

1984 (1)

S. Sugihara, M. Kishino, and M. Okami, “Contribution of Raman scattering to upward irradiance in the sea,” J. Oceanogr. Soc. Japan 40, 397–404 (1984).
[Crossref]

1983 (1)

W. K. Bischel and G. Black, “Wavelength dependence of Raman scattering cross sections from 200–600  nm,” AIP Conf. Proc. 100, 181–187 (1983).
[Crossref]

1981 (1)

1978 (1)

I. I. Kondilenko, P. A. Korotkov, V. A. Klimenko, and O. P. Demyanenko, “Transverse cross section of the Raman scattering of the u1 vibration of the water molecule in the liquid and gaseous states,” Opt. Spectrosc. 43, 384–386 (1978).

1975 (2)

N. P. Romanov and V. S. Shuklin, “Raman scattering cross section of liquid water,” Opt. Spectrosc. 38, 646–648 (1975).

R. B. Slusher and V. E. Derr, “Temperature dependence and cross sections of some Stokes and anti-Stokes Raman lines in ice Ih,” Appl. Opt. 14, 2116–2120 (1975).
[Crossref]

1973 (1)

Abreu, L. W.

L. W. Abreu and G. P. Anderson, “The MODTRAN® 2/3 report and LOWTRAN 7 model,” Ontar Corporation for PL/GPOS (1996).

Anderson, G. P.

L. W. Abreu and G. P. Anderson, “The MODTRAN® 2/3 report and LOWTRAN 7 model,” Ontar Corporation for PL/GPOS (1996).

Ashlock, T. A.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Baker, K. S.

Balseiro, E. G.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

Bartlett, J. S.

Bethel, M.

M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
[Crossref]

Bischel, W. K.

W. K. Bischel and G. Black, “Wavelength dependence of Raman scattering cross sections from 200–600  nm,” AIP Conf. Proc. 100, 181–187 (1983).
[Crossref]

Black, G.

W. K. Bischel and G. Black, “Wavelength dependence of Raman scattering cross sections from 200–600  nm,” AIP Conf. Proc. 100, 181–187 (1983).
[Crossref]

Boney, C. M.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Bunkin, A. F.

Calmes, L. K.

M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
[Crossref]

Chang, C. H.

C. H. Chang and L. A. Young, “Seawater temperature measurements from Raman spectra,” (Advanced Research Projects Agency, 1972).

Claassen, P. J.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Cooper, K.

Copeland, R. A.

Daniels, J. W.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Demyanenko, O. P.

I. I. Kondilenko, P. A. Korotkov, V. A. Klimenko, and O. P. Demyanenko, “Transverse cross section of the Raman scattering of the u1 vibration of the water molecule in the liquid and gaseous states,” Opt. Spectrosc. 43, 384–386 (1978).

Derr, V. E.

Faris, G. W.

Garvis, D.

Hale, G. M.

Hall, D.

M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
[Crossref]

Hargis, P. J.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Hargreaves, B. R.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

Heberle, G.

M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
[Crossref]

Hope, M.

M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
[Crossref]

Iarlori, M.

Jackson, J. D.

J. D. Jackson, Classical Electrodynamics, 2nd ed. (Wiley, 1975).

Johnson, M. S.

I. R. Shokair, M. S. Johnson, R. L. Schmitt, and S. Sickafoose, “Concept for maritime near-surface surveillance using water Raman scattering,” (Sandia National Laboratories, 2016).

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Kattawar, G. W.

Kennedy, R.

Kishino, M.

S. Sugihara, M. Kishino, and M. Okami, “Contribution of Raman scattering to upward irradiance in the sea,” J. Oceanogr. Soc. Japan 40, 397–404 (1984).
[Crossref]

Klarkowski, J. R.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Klimenko, V. A.

I. I. Kondilenko, P. A. Korotkov, V. A. Klimenko, and O. P. Demyanenko, “Transverse cross section of the Raman scattering of the u1 vibration of the water molecule in the liquid and gaseous states,” Opt. Spectrosc. 43, 384–386 (1978).

Klinkov, V. K.

Kondilenko, I. I.

I. I. Kondilenko, P. A. Korotkov, V. A. Klimenko, and O. P. Demyanenko, “Transverse cross section of the Raman scattering of the u1 vibration of the water molecule in the liquid and gaseous states,” Opt. Spectrosc. 43, 384–386 (1978).

Korotkov, P. A.

I. I. Kondilenko, P. A. Korotkov, V. A. Klimenko, and O. P. Demyanenko, “Transverse cross section of the Raman scattering of the u1 vibration of the water molecule in the liquid and gaseous states,” Opt. Spectrosc. 43, 384–386 (1978).

Krumel, L. J.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Kulp, T. J.

Kushina, M. E.

M. E. Kushina, G. Heberle, M. Hope, D. Hall, M. Bethel, and L. K. Calmes, “ALMDS laser system,” Proc. SPIE 4968, 163–168 (2003).
[Crossref]

Lang, A. R.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Lednev, V. N.

Liu, F.

Magee, G. I.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Marshall, B. R.

Mobley, C. D.

C. D. Mobley, Radiative Transfer in the Ocean (Academic, 2001).

Modenutti, B.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

Moeller, R.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

Morris, D. P.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

Okami, M.

S. Sugihara, M. Kishino, and M. Okami, “Contribution of Raman scattering to upward irradiance in the sea,” J. Oceanogr. Soc. Japan 40, 397–404 (1984).
[Crossref]

Pedroncelli, M. L.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Pershin, S. M.

Queimalinos, C.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

Querry, M. R.

Rizi, V.

Rocci, G.

Romanov, N. P.

N. P. Romanov and V. S. Shuklin, “Raman scattering cross section of liquid water,” Opt. Spectrosc. 38, 646–648 (1975).

Salmon, T.

Sathyendranath, S.

Schmitt, R. L.

I. R. Shokair, M. S. Johnson, R. L. Schmitt, and S. Sickafoose, “Concept for maritime near-surface surveillance using water Raman scattering,” (Sandia National Laboratories, 2016).

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Schroder, K. L.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Shokair, I. R.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

I. R. Shokair, M. S. Johnson, R. L. Schmitt, and S. Sickafoose, “Concept for maritime near-surface surveillance using water Raman scattering,” (Sandia National Laboratories, 2016).

Shuklin, V. S.

N. P. Romanov and V. S. Shuklin, “Raman scattering cross section of liquid water,” Opt. Spectrosc. 38, 646–648 (1975).

Sickafoose, S.

I. R. Shokair, M. S. Johnson, R. L. Schmitt, and S. Sickafoose, “Concept for maritime near-surface surveillance using water Raman scattering,” (Sandia National Laboratories, 2016).

Slusher, R. B.

Smith, M. W.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Smith, R. C.

Spooner, J. T.

R. L. Schmitt, K. L. Schroder, M. W. Smith, L. J. Krumel, P. J. Hargis, I. R. Shokair, T. A. Ashlock, J. W. Daniels, J. R. Klarkowski, M. S. Johnson, C. M. Boney, P. J. Claassen, G. I. Magee, M. L. Pedroncelli, J. T. Spooner, and A. R. Lang, “Ares UV LIF standoff system development and testing,” in Proceedings of the 6th Joint Conference on Standoff Detection for Chemical and Biological Defense, Williamsburg, Virginia, October 2004.

Sugihara, S.

S. Sugihara, M. Kishino, and M. Okami, “Contribution of Raman scattering to upward irradiance in the sea,” J. Oceanogr. Soc. Japan 40, 397–404 (1984).
[Crossref]

Visconti, G.

Vodacek, A.

Voss, K. J.

Williamson, C. E.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

Xu, X.

Yi, F.

Young, L. A.

C. H. Chang and L. A. Young, “Seawater temperature measurements from Raman spectra,” (Advanced Research Projects Agency, 1972).

Yulmetov, R. N.

Zagarese, H.

D. P. Morris, H. Zagarese, C. E. Williamson, E. G. Balseiro, B. R. Hargreaves, B. Modenutti, R. Moeller, and C. Queimalinos, “The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon,” Limnol. Oceanogr. 40, 1381–1391 (1995).
[Crossref]

AIP Conf. Proc. (1)

W. K. Bischel and G. Black, “Wavelength dependence of Raman scattering cross sections from 200–600  nm,” AIP Conf. Proc. 100, 181–187 (1983).
[Crossref]

Appl. Opt. (10)

G. W. Faris and R. A. Copeland, “Wavelength dependence of the Raman cross section for liquid water,” Appl. Opt. 36, 2686–2688 (1997).
[Crossref]

J. S. Bartlett, K. J. Voss, S. Sathyendranath, and A. Vodacek, “Raman scattering by pure water and seawater,” Appl. Opt. 37, 3324–3332 (1998).
[Crossref]

V. Rizi, M. Iarlori, G. Rocci, and G. Visconti, “Raman lidar observations of cloud liquid water,” Appl. Opt. 43, 6440–6453 (2004).
[Crossref]

F. Liu and F. Yi, “Spectrally resolved Raman lidar measurements of gaseous and liquid water in the atmosphere,” Appl. Opt. 52, 6884–6895 (2013).
[Crossref]

T. J. Kulp, D. Garvis, R. Kennedy, T. Salmon, and K. Cooper, “Development and testing of a synchronous-scanning underwater imaging system capable of rapid two-dimensional frame imaging,” Appl. Opt. 32, 3520–3530 (1993).
[Crossref]

R. B. Slusher and V. E. Derr, “Temperature dependence and cross sections of some Stokes and anti-Stokes Raman lines in ice Ih,” Appl. Opt. 14, 2116–2120 (1975).
[Crossref]

B. R. Marshall and R. C. Smith, “Raman scattering and in-water ocean optical properties,” Appl. Opt. 29, 71–84 (1990).
[Crossref]

G. W. Kattawar and X. Xu, “Filling in of Fraunhofer lines in the ocean by Raman scattering,” Appl. Opt. 31, 6491–6500 (1992).
[Crossref]

G. M. Hale and M. R. Querry, “Optical constants of water in the 200-nm to 200  µm wavelength region,” Appl. Opt. 12, 555–563 (1973).
[Crossref]

R. C. Smith and K. S. Baker, “Optical properties of the clearest natural waters (200–800  nm),” Appl. Opt. 20, 177–184 (1981).
[Crossref]

J. Oceanogr. Soc. Japan (1)

S. Sugihara, M. Kishino, and M. Okami, “Contribution of Raman scattering to upward irradiance in the sea,” J. Oceanogr. Soc. Japan 40, 397–404 (1984).
[Crossref]

Limnol. Oceanogr. (1)

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Figures (10)

Fig. 1.
Fig. 1. Illustration of lidar beam incidence, refraction at the air–water interface, and return Raman light. The range is R and s is the path length along the propagation direction in the water.
Fig. 2.
Fig. 2. MODTRAN calculation of solar spectral irradiance. MODTRAN options: “Direct solar Irradiance,” zero zenith angle, zero altitude above sea level, “Mid-latitude Winter” atmospheric model, and 23 km visibility aerosol model. The spectral resolution or width per spectral bin is 50 cm 1 .
Fig. 3.
Fig. 3. Attenuation coefficient of pure water based on [21]. Also shown are the attenuation coefficient at the corresponding Raman wavelength and the summed coefficients.
Fig. 4.
Fig. 4. Schematic diagram of the Ares UV-LIF lidar system at 355 nm.
Fig. 5.
Fig. 5. Left: The Ares lidar mounted in a trailer with beam aligned for horizontal propagation. Right: horizontal water pipe used for the Raman measurements. The pipe is 152 cm long and 14.0 cm in diameter with fused silica windows on both ends. The ports in the pipe were used for placing a target to set the water depth. The pipe front window is located 70 m from the lidar.
Fig. 6.
Fig. 6. Spectrally integrated N 2 Raman signal and range-corrected signal versus range for the Ares lidar. The measured signal is normalized to maximum of unity. Also shown is the ratio of measured counts to range-corrected counts, which is the overlap factor of the lidar LIF channel. These measurements are for horizontal beam propagation in air with a gate delay of 0.05 μs relative to the lidar range and a width of 0.1 μs, corresponding to a width of 15 m of air.
Fig. 7.
Fig. 7. Pure water Raman spectra with target at various locations along the water column. The spectra are normalized to 500 pulses. For all measurements the gate delay is 50 ns with respect to the front window, the width is 100 ns, and the detector gain setting is at 50. The manually measured pulse energy is 30 mJ .
Fig. 8.
Fig. 8. Summed and corrected counts of the spectra in Fig. 7 versus target location. The last location at 152 cm. has no target but is the end of the tube. The dashed curve is the model fit based on an overall attenuation coefficient of β 0.26 m 1 .
Fig. 9.
Fig. 9. Spectra for the ocean water sample at several target locations. All spectra are normalized to 500 pulses. The gate delay is 16 ns , the gate width is 100 ns, and the gain setting is 100. At this gain setting, the detector calibration factor is 4.9 relative to the gain setting of 50 used in Fig. 7 (counts are divided by this factor to get equivalent counts at gain setting of 50). The manually measured laser energy is 7.5 mJ / pulse . After partitioning of the Raman and fluorescence spectra, the summed Raman signal at the maximum target location is 1.7 × 10 7 counts for 500 pulses.
Fig. 10.
Fig. 10. Spectra for the San Francisco Bay water sample at several target locations and normalized to 500 pulses. All measurement parameters are the same as in Fig. 9. After partitioning of the Raman and fluorescence spectra, the summed Raman signal is 4.5 × 10 6 counts for 500 pulses.

Equations (8)

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d σ ( θ , ϕ ) d Ω = d σ ( θ = 90 ° , ϕ = 90 ° ) d Ω { 2 ρ + ( 1 ρ ) ( cos 2 θ cos 2 ϕ + sin 2 ϕ ) 1 + ρ } ,
d σ ( θ = 90 ° , ϕ = 90 ° ) d Ω = A ν s 4 ( ν i 2 ν p 2 ) 2 ,
d N R = I b ( t , s ) ϵ b d σ ( θ = 180 ° ) d Ω N W d s Δ Ω ,
d E R ( τ , s ) = P b ( t ) d t exp [ ( μ + μ R ) s ] d s ( d σ d Ω N W λ b λ R ) L ,
E R Total = L ( d σ d Ω N W λ b λ R ) 1 β 0 Δ T d t P b ( t ) [ exp ( β s min ) exp ( β s max ) ] ,
s min = [ D ( 2 R / c + t ) ] c / 2 , s max = [ D + W ( 2 R / c + t ) ] c / 2 ,
E R = ( d σ d Ω N W λ b λ R ) Δ Ω η Lidar E Beam S T ,
E Solar = ( Δ k d k S ( k ) ) Δ Ω 2 π ρ Surface A FOV T ( k R ) W η Lidar ,

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