This PDF file contains the front matter associated with SPIE Proceedings Volume 9459, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

Space division multiplexing of optical beams has recently been demonstrated for improving the bandwidth of optical communication links. This paper will explore the use of space division multiplexing utilizing blue lasers for potential undersea applications. Experimental results will be shown for optical vortices utilizing a range of charge numbers corresponding to various Orbital Angular Momentum states.

This paper explores the use of a recently developed chaotic lidar sensor to perform impulse response measurements underwater. The sensor’s measured system impulse response, which approximates a thumbtack function with a 1 ns peak width, is used with an ocean impulse response simulator to predict the chaotic lidar’s expected performance underwater. A calibration routine is developed to compensate for the finite resolution and sidelobes in the sensor’s system impulse response, improving the accuracy of the simulated chaotic lidar results. In an example application of water turbidity measurement, the extinction coefficient of water, c, is extracted from simulated chaotic lidar impulse responses with an average error of 0.03/m over a range of turbidities from c=0.1/m to c=0.3/m. Simulations are also presented to demonstrate that the chaotic lidar sensor impulse response can simultaneously detect multiple reflective elements and the volumetric backscatter response with a 1 ns temporal resolution. Laboratory water tank measurements are performed to validate the simulation approach, and the experimental chaotic lidar measurements are in reasonable agreement with the simulated results.

Recent interest in high speed laser communications underwater has restimulated theoretical studies in laser propagation in turbid media. In particular, the characterization of temporal dispersion is of paramount importance in order to predict the bandwidth and capacity of underwater optical channels. While the temporal aspects of underwater laser propagation have received attention from the modeling community in the past, few if any of these models have been validated with experimental data. However recent advances in hardware technology now enable experimental characterization at high speeds (~GHz). Such measurements have been made by the authors.¹ In this work, we develop a Monte Carlo model, and present initial results validated against the aforementioned experimental data.

The performance of a frequency-modulated continuous-wave (FMCW) hybrid lidar-radar system will be presented in the context of an underwater optical ranging application. In adapting this technique from the radar community, a laser is intensity-modulated with a linear frequency ramp. A custom wideband laser source modulated by a new wideband digital synthesizer board is used to transmit an 800 MHz wide chirp into the underwater channel. The transmitted signal is mixed with a reference copy to obtain a “beat” signal representing the distance to the desired object. The expected form of the return signal is derived for turbid waters, a highly scattering environment, indicating that FMCW can detect both the desired object and the volumetric center of the backscatter “clutter” signal. This result is verified using both laboratory experiments and a realistic simulation model of the underwater optical channel. Ranging performance is explored as a function of both object position and water turbidity. Experimental and simulated results are in good agreement and performance out to ten attenuation lengths is reported, equivalent to 100 meters in open ocean or 5 meters in a turbid harbor condition.

A modulated pulse laser imaging system has been developed which utilizes coded/chirped RF modulation to mitigate the adverse effects of optical scattering in degraded visual underwater environments. Current laser imaging techniques employ either short pulses or single frequency modulated pulses to obtain both intensity and range images. Systems using short pulses have high range resolution but are susceptible to scattering due to the wide bandwidth nature of the pulse. Range gating can be used to limit the effects of backscatter, but this can lead to blind spots in the range image. Modulated pulse systems can help suppress the contribution from scattered light in generated imagery without gating the receiver. However, the use of narrowband, single tone modulation results in limited range resolution where small targets are camouflaged within the background. This drives the need for systems which have high range resolution while still suppressing the effects of scattering caused by the environment. Coded/chirped modulated pulses enable the use of radar pulse compression techniques to substantially increase range resolution while also providing a way to discriminate the object of interest from the light scattered from the environment. Linearly frequency chirped waveforms and phase shift keyed barker codes were experimentally investigated to determine the effects that pulse compression would have on intensity/range data. The effect of modulation frequency on the data produced with both wideband and narrowband modulation was also investigated. The results from laboratory experiments will be presented and compared to model predictions.

In recent years, a compressive sensing based underwater imaging system has been under investigation: the Compressive Line Sensing (CLS) imaging system. In the CLS system, each line segment is sensed independently; with regard to signal reconstruction, the correlation among the adjacent lines is exploited via the joint sparsity in the distributed compressive sensing model. Interestingly, the dynamic compressive sensing signal model is also capable of exploiting the correlated nature of the adjacent lines through a Bayesian framework. This paper proposes a new CLS reconstruction technique through the integration of these different models, and includes an evaluation of the proposed technique using the experiment dataset obtained from an underwater imaging test setup.

A fine structure underwater imaging LiDAR (FSUIL) has recently been developed and initial field trials have been conducted. The instrument, which rapidly scans an array of closely spaced, narrow, collimated laser pulses into the water column produces two-dimensional arrays of backscatter profiles, with fine spatial and temporal resolution. In this paper a novel method to derive attenuation profiles is introduced. This approach is particularly attractive in applications where primary on-board processing is required, and other applications where conventional model-based approaches are not feasible due to a limited computational capacity or lack of a priori knowledge of model input parameters. The paper also includes design details regarding the new FSUIL instrument are given, with field results taken in clear to moderately turbid water being presented to illustrate the various effects and considerations in the analysis of the system data. LiDAR waveforms and LiDAR derived attenuation coefficients are analyzed and compared to calibrated beam attenuation, particulate scattering and absorption coefficients. The system was field tested during the NATO Ligurian Sea LIDAR & Optical Measurements Experiment (LLOMEx) cruise in March 2013, during the spring bloom conditions. Throughout a wide range of environmental conditions, the FSUIL was deployed on an in situ profiler obtaining thousands of three-dimensional LiDAR scans from the near surface down to the lower thermocline. Deployed concurrent to the FSUIL was a range of commercially available off-the-shelf instruments providing side-by-side in-situ attenuation measurement.

Polarized image of underwater light field contains rich information of and the targets strongly affected by the water inherent optical properties. We present a comprehensive analysis of the polarimetric images of a manmade underwater target with known polarization properties acquired by a full Stokes vector imaging camera in underwater environment. The effects of the camera’s parameters such as numerical aperture and orientation are evaluated. With the knowledge acquired in the analysis of such a forward polarimetric imaging process, a method for retrieval of the inherent optical properties of the water and the target polarization is explored.

There is a large diversity of phase functions for the computer simulation of light under water. Some papers look at the influence of these phase functions on the results of computer simulations of the remote sensing reflectance. We study the influence of these phase functions on the computer simulation of the resulting image of a target illuminated by a laser. For these simulations we are only interested in those parts of the light that reach the camera position. Therefor we investigate the influence of the phase function on the image. We use a Monte Carlo Simulator with several Fournier-Forand, Henyey-Greenstein phase functions. The resulting signals at the receiver of these simulations are compared to a simulation with a Petzold function that is based on measurements of the phase function.

Temperature microstructure in the ocean can lead to localized changes in the index of refraction and can distort underwater electro-optical (EO) signal transmission. A similar phenomenon is well-known from atmospheric optics and generally referred to as “optical turbulence”. Though turbulent fluctuations in the ocean distort EO signal transmission and can impact various underwater applications, from diver visibility to active and passive remote sensing, there have been few studies investigating the subject. To provide a test bed for the study of impacts from turbulent flows on underwater EO signal transmission, and to examine and mitigate turbulence effects, we set up a laboratory turbulence environment allowing the variation of turbulence intensity. Convective turbulence is generated in a large Rayleigh- Bénard tank and the turbulent flow is quantified using high-resolution Acoustic Doppler Velocimeter profilers and fast thermistor probes. The turbulence measurements are complemented by computational fluid dynamics simulations of convective turbulence emulating the tank environment. These numerical simulations supplement the sparse laboratory measurements. The numerical data compared well to the laboratory data and both conformed to the Kolmogorov spectrum of turbulence and the Batchelor spectrum of temperature fluctuations. The controlled turbulence environment can be used to assess optical image degradation in the tank in relation to turbulence intensity, as well as to apply adaptive optics techniques. This innovative approach that combines optical techniques, turbulence measurements and numerical simulations can help understand how to mitigate the effects of turbulence impacts on underwater optical signal transmission, as well as advance optical techniques to probe oceanic processes.

Temperature measurement is one of the key quantifies in ocean research. Temperature variations on small and large scales are key to air-sea interactions and climate change, and also regulate circulation patterns, and heat exchange. The influence from rapid temperature changes within microstructures are can have strong impacts to optical and acoustical sensor performance. In this paper, we present an optical fiber sensor for the high-resolution and high-speed temperature profiling. The developed sensor consists of a thin piece of silicon wafer which forms a Fabry-Pérot interferometer (FPI) on the end of fiber. Due to the unique properties of silicon, such as large thermal diffusivity, notable thermo-optic effects and thermal expansion coefficients of silicon, the proposed sensor exhibits excellent sensitivity and fast response to temperature variation. The small mass of the tiny probe also contributes to a fast response due to the large surface-tovolume ratio. The high reflective index at infrared wavelength range and surface flatness of silicon endow the FPI a spectrum with high visibilities, leading to a superior temperature resolution along with a new data processing method developed by us. Experimental results indicate that the fiber-optic temperature sensor can achieve a temperature resolution better than 0.001°C with a sampling frequency as high as 2 kHz. In addition, the miniature footprint of the senor provide high spatial resolutions. Using this high performance thermometer, excellent characterization of the realtime temperature profile within the flow of water turbulence has been realized.

The Glider Observation STrategies (GOST) system provides real-time assistance to ocean glider pilots by suggesting preferred ocean glider waypoints based on ocean forecasts and their uncertainties. Restrictions on waterspace, preferred operational areas, and other glider trajectories are also taken into account. Using existing operational regional Navy Coastal Ocean Model (RNCOM) output, demonstrations of glider waypoint calculation are ongoing in Navy operational areas. After the ocean forecast models and GOST components run at the Navy DoD Supercomputing Resource Center (Navy DSRC), GOST-suggested glider paths are transferred to the Glider Operations Center (GOC). The glider pilots at the GOC import this information into their Unmanned Systems Interface (USI), developed at the University of Washington, Applied Physics Laboratory (APL-UW) to evaluate the suggested glider paths, make adjustments, and update waypoints for the gliders. The waypoints being sent are visualized and analyzed using graphic capabilities to convey guidance uncertainty developed under a grant to the University of New Orleans (UNO) and added under the Environmental Measurements Path Planner (EMPath) system within GOST. USI forwards automatic messages from the gliders with recent glider location, speed, and depth to GOST for the next cycle. Over the course of these demonstrations, capabilities were added or modified including use of initial glider bearing, preferred path, refinement of glider turn frequency, correction of glider speed, and introduction of glider rendezvous locations. Automation has been added with help from the modeling group at the Naval Oceanographic Office (NAVOCEANO). GOST supports NAVOCEANO’s ongoing efforts to direct and recover gliders, to safely navigate in changing ocean conditions, and to provide feedback to improve ocean model prediction.

Based on observations and modeling studies we have evaluated the impact of submesoscale processes on the development and intensification of offshore narrow (5-10km wide) phytoplankton filaments during summer time in the Monterey Bay, CA. We have demonstrated that, submesoscale processes (surface frontogenesis and nonlinear Ekman transport) lead to the development of very productive phytoplankton patches along the edges between the cold jet and warm anticyclonic eddy. Our results illustrate that during persistent upwelling favorable winds, submesoscale processes can modulate the development and intensification of offshore narrow (5-10km wide) phytoplankton filaments. These processes can incubate the phytoplankton population offshore (as for example, bioluminescent dinoflagellates during August 2003). These offshore phytoplankton filaments can migrate onshore during relaxed winds following the upwelling, and be an additional source of phytoplankton bloom development in and around Monterey Bay. Therefore, the discussed offshore phytoplankton filaments may be a factor in the Bay ecosystem health, as for example, in the development of such events as harmful algae blooms (HABs). All these emphasize the importance of further observational and modeling studies of these submesoscale processes which impact the development and intensification of offshore phytoplankton filaments.

Several semi-analytic models exist for the inherent optical properties of sea water, at least for Case 1 waters. In these waters, models based on chlorophyll-a concentration seem to be fairly successful. For passive remote sensing, the critical properties are the backscattering coefficient and the zenith diffuse attenuation coefficient. The former describes the total scattering at angles > 0.5π steradians. The diffuse attenuation coefficient is not strictly an inherent optical property, because it depends on the sun angle. The zenith diffuse attenuation coefficient, defined as the attenuation of a diffuse source located at the zenith, depends only on the optical properties of the water. The observed remote sensing reflectance can be estimated from these two parameters and the solar zenith angle. Most of the investigations to date have assumed that the chlorophyll concentration does not vary with depth. This assumption is often quite good, because of the limited penetration of light into sea water. We will consider the case of intense thin plankton layers on a shallow pycnocline, where this assumption might not be valid. For active remote sensing, an additional parameter is important. This parameter is the volume scattering function at a scattering angle of π steradians, which is the sum of contributions from sea water and particles in the water. The sea water contribution is known. The particulate contribution can be modeled as the product of the scattering coefficient, which depends on chlorophyll concentration, and the phase function at π steradians, which does not.

In the past few years, we have demonstrated how the surface return measured by the active instruments onboard CloudSat and CALIPSO could be used to retrieve the optical depth and backscatter phase function (lidar ratio) of aerosols and ice clouds. This methodology lead to the development of a data fusion product publicly available at the ICARE archive center using the Synergized Optical Depth of Aerosols and Ice Clouds (SODA & ICE) algorithm¹. This algorithm, also allowing to derive ocean surface wind speed, has been extended to include dense cloud surface return to analyze aerosol and cloud properties above such clouds. This low level data fusion of CALIPSO and CloudSat ocean surface echoes has been used by several researchers to explore different research paths. Among them, we can cite: • A new characterization of the lidar ratio of cirrus clouds² • The analysis of the precipitable water and development of a new Millimeter-Wave Propagation Model for the W-Band observations (EMPIRIMA³) • The analysis of the lidar ratio of sea-spray aerosols⁴, and of Aerosol multilayer lidar ratio and extinction⁵ • A contribution to the retrieval of the subsurface particulate backscatter coefficients of phytoplankton particles⁶ In this paper, we present the main features of SODA & ICE, summarizing some of the results obtained. This low level data fusion of CALIPSO and CloudSat ocean surface echoes has been used by several researchers to explore different research paths. Among them, we can cite: A new characterization of the lidar ratio of cirrus clouds² The analysis of the precipitable water and development of a new Millimeter-Wave Propagation Model for the W-Band observations (EMPIRIMA³) The analysis of the lidar ratio of sea-spray aerosols⁴, and of Aerosol multilayer lidar ratio and extinction⁵ A contribution to the retrieval of the subsurface particulate backscatter coefficients of phytoplankton particles⁶ In this paper, we present the main features of SODA & ICE, summarizing some of the results obtained.

Integrity Applications Incorporated (IAI) collected electro-optical polarimetric imagery (PI) to evaluate its effectiveness for detecting oil on water. Data was gathered at multiple sun angles for vegetable oil and crude oil to demonstrate PI sensitivity to different liquids and collection geometries. Unique signatures for oil relative to water were observed. Both oils consistently displayed higher degree of linear polarization (DOLP) values than water, which was expected based on the lower index of refraction of water (1.33) relative to vegetable oil and crude oil (1.47 and 1.47-1.57, respectively). The strength of the polarimetric signatures was found to vary as a function of collection angle relative to the sun, with peak linear polarizations ranging from 40-70% for crude oil and 20-50% for vegetable oil. IAI found that independently scaled DOLP was particularly useful for discriminating these liquids, because it demonstrated the least sensitivity to collection angle, compared to other PI products. Specifically, the DOLP signature of vegetable oil was approximately 20% lower than for crude oil, regardless of collection angle. This finding is consistent with the lower index of refraction values for vegetable oil compared to crude. Based on the promising results presented here, IAI recommends further testing and development of PI for oceanic remote sensing applications such as oil spill/leak detection and for supporting oil cleanup efforts. With additional work, PI may also be applicable to other oceanic environmental issues such as detection of agricultural runoff or effluent from industrial facilities or watercraft.

Radiometric performance of MODIS and VIIRS sensors is superior to that of the AVHRR, thanks to improved design and implementation of stringent pre-launch sensor characterization efforts and in-flight monitoring practices. Nevertheless, the imagery of the measured brightness temperatures (BT) and derived sea surface temperatures (SST) from multi-detector MODIS and VIIRS instruments is subject to striping artifacts. A robust adaptive destriping algorithm recently introduced by Bouali and Ignatov1 was optimized and operationally implemented at NOAA to remove striping artifacts in the VIIRS BT data. Destriped BTs are used as input into the NOAA Advanced Clear-Sky Processor for Oceans (ACSPO) SST system. The algorithm is also run with MODIS data onboard Terra/Aqua, in an experimental mode. We demonstrate improved image quality of VIIRS and MODIS BTs in bands centered at 3.7, 11 and 12 μm, and significant improvements in the derived SST imagery. The algorithm proves capable of removing the striping noise, while preserving the fine natural contrasts of the original satellite imagery. It was also tested to remove striping artifacts from the VIIRS and MODIS “optional SST” bands, centered at 4 and 8.5 μm. Destriping is critically important for several SST applications relying on accurate BT or SST gradient data, including ocean front detection and pattern recognition improvements to ACSPO cloud mask. We present the results of statistical characterization of striping artifacts in the VIIRS and MODIS thermal IR bands under various observational conditions. Our implementation of destriping is computationally efficient, adding only a fraction of time to the SST data processing flow. It is currently used at NOAA with VIIRS operations and reprocessing efforts.

Full-swath Sea Surface Temperature (SST) derived from data acquired by the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on-board the Suomi-National Polar-orbiting Partnership (S-NPP) satellite produces significant overlap between consecutive orbits at all latitudes. In this study, we use those overlap regions to evaluate VIIRS SST, as inconsistencies between SST values from consecutive orbits are indications of likely degraded quality. The studies investigate two sources of inconsistencies: those resulting from the response of the SST equations when observing a scene from differing view angles and those caused by undetected data contamination. This study will present results for two VIIRS SST products: one from the Naval Oceanographic Office (NAVOCEANO), which is assimilated in the Navy Ocean Models, and the Advanced Clear-Sky Processor for Oceans (ACSPO) product from the National Oceanic and Atmospheric Administration (NOAA) Center for Satellite Applications and Research (STAR). Global statistics based on drifting buoys for both NAVOCEANO and NOAA products complete the analysis.

The uncertainty of the Advanced Clear-Sky Processor for Oceans (ACSPO) Sea Surface Temperature (SST) products from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite is examined using consecutive orbital overlaps in coastal waters of the Gulf of Mexico. The overlapping region on the left and right side of the VIIRS swath at 23-35 degree latitude covers approximately 500 pixels, which occur within 100 minutes and can provide a total of 4 SST products (2 day and 2 night) per day. By assuming the ocean SST should be similar on each side of the swath in this short time period, diel changes are examined and the uncertainty of SST retrieval is determined by comparing with buoy-derived SST. The VIIRS ACSPO product from NOAA STAR was used to determine the difference in SST within the overlapping regions. These SST changes are evaluated between consecutive orbits to validate the accuracy of SST algorithms on each side of the swath at high sensor angles. The SST product differences across the swath can result from surface glint, sensor angular impacts and sensor characteristics such as half angle mirror side (HAM) and calibration. The absolute diurnal SST changes that can occur within 100 minutes are evaluated with the buoy and VIIRS-derived SST. Sensitivity of the SST to water types is evaluated by measuring diurnal differences for open ocean, shelf and coastal waters. The 100 minute VIIRS SST overlap shows the capability to monitor the diurnal ocean heating and cooling which are associated with water mass optical absorption. The seasonal trends of the difference in SST at the overlaps for these water masses were tracked on a monthly basis. The unique capability of using the same VIIRS sensor for self-characterization can provide a method to define the uncertainty of ocean products and characterize the diurnal changes for different water types.

Multichannel regression algorithms are widely used in retrievals of sea surface temperature (SST) from infrared brightness temperatures (BTs) observed from satellites. The SST equations typically include terms dependent on the difference between BTs observed in spectral bands with different atmospheric absorption. Such terms do account for variations in the variable atmospheric attenuation, but may introduce additional noise in the retrieved SST due to amplification of the radiometric noise. Some processing systems (e.g., the EUMETSAT OSI-SAF) incorporate noise suppression algorithms, based on spatial smoothing of the differential terms in the SST equations. A similar algorithm is being tested for the potential use in the NOAA Advanced Clear-Sky Processor for Oceans (ACSPO). The ACSPO smoothing algorithm aims to preserve natural variations in SST field, while minimizing distortions in the original SST imagery, at a minimal processing time. This presentation describes the ACSPO smoothing algorithm and results of its evaluation with the SST imagery, and with the in situ matchups for NOAA and Metop AVHRRs, Terra and Aqua MODISs, and SNPP/JPSS VIIRS.

The MODIS advanced sensor contains 16 channels in the thermal infrared band, makes it an attractive instrument for atmospheric and oceanic sciences. Even for satellite-derived sea surface temperature (SST) retrievals, the dynamics of atmospheric conditions are intended to be characterized by the satellite measurement sufficiently to retrieve good quality SST. The Group for High Resolution SST (GHRSST), which is an international scientific body, provides MODIS SST to date using only two and/or three channels by employing regression method. The few coefficients used in regression based retrieval methods are unable to compensate for wide atmospheric variability and as a result, significant errors are embedded in the retrieved SST. We will demonstrate in this work that the MODIS SST can be retrieved with approximately double the accuracy compared GHRSST operational SST, by using more channels and our physical deterministic-based modified total least squares (MTLS) method. This study also includes the SST4/NLSST and optimal estimation based SST retrieval for comparison purposes. The information content and noise analysis of these retrievals, and the retrieval error due to the quality of cloud detection is discussed.

AVHRR clear-sky brightness temperatures (BTs) over ocean and derived sea surface temperatures (SSTs) are produced at NOAA from several polar and geostationary sensors, including AVHRRs onboard US NOAA and European MetOp satellites. Analyses in the Monitoring of IR Clear-sky Radiances over Oceans for SST system (MICROS; www.star.nesdis.noaa.gov/sod/sst/micros/) suggest that artifacts in SSTs are strongly linked to anomalies in BTs. To attribute anomalous BTs to calibration information reported on L1b data, NOAA established another online system, Sensor Stability for SST (3S; www.star.nesdis.noaa.gov/sod/sst/3s/). The 3S monitors orbital statistics of calibration gains and offsets in AVHRR SST bands, along with the onboard measurements of blackbody temperature, blackbody view count (BC) and space view count (SC), from which the gain and offset are calculated. Sun and moon geometry configuration, which may affect the BC and SC, is also monitored, as well as the length of the “satellite night” (part of the orbit, when the satellite is in the Earth shadow and AVHRR calibration is presumably more accurate). Currently, the 3S displays time series of all statistics for NOAA-15 to -19, MetOp-A and -B. This presentation describes the 3S system.

An understanding of environmental variability (stability/instability) is important to support operational planning of expeditionary warfare and littoral operations, as well as for preparing the Recognized Environmental Picture (REP). Specifically, the identification of environmentally stable/unstable areas helps the planning of maritime operations, increasing their likelihood of success. The purpose of the paper is to describe a methodology to form and interpret an initial spatial-temporal variability characterization of maritime areas from Remote Sensing (RS) and Numerical Ocean Model (NOM) data. As a case study, the analysis of the sea surface tem- perature (SST) in the Black Sea from historical time-series of RS imagery and NOM data is considered. The results of the analysis are validated with in situ measurements from moorings. Identification of gaps of geospatial information is also done in this study. The analysis is focused on monthly spatial-temporal variability of the SST, generating stability maps displaying the geospatial distribution of environmentally stable/unstable areas along a year. The results show how the proposed methodology captures the temporal variability of the SST in the Black Sea, being compared with in situ measurements, and provides useful information for the identification of environmentally stable/unstable areas. The results show a general agreement in the variability with both RS and NOM data, when RS imagery may be used for the present analysis, i.e. when low cloud coverage is given. This paper demonstrates that when RS imagery gaps are not negligible (e.g. due to high cloud occurrence in winter season), these gaps could be filled with NOM data.