This PDF file contains the front matter associated with SPIE Proceedings Volume 9080, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

We introduce the term “multi-dimensional laser radar”, where the dimensions mean not only the coordinates of the object in space, but its velocity and orientation, parameters of the media: scattering, refraction, temperature, humidity, wind velocity, etc. The parameters can change in time and can be combined. For example, rendezvous and docking missions, autonomous planetary landing, along with laser ranging, laser altimetry, laser Doppler velocimetry, are thought to have aboard also the 3D ladar imaging. Operating in combinations, they provide more accurate and safer navigation, docking or landing, hazard avoidance capabilities. Combination with Doppler-based measurements provides more accurate navigation for both space and cruise missile applications. Critical is the information identifying the snipers based on combination of polarization and fluctuation parameters with data from other sources. Combination of thermal imaging and vibrometry can unveil the functionality of detected targets. Hyperspectral probing with laser reveals even more parameters. Different algorithms and architectures of ladar-based target acquisition, reconstruction of 3D images from point cloud, information fusion and displaying is discussed with special attention to the technologies of flash illumination and single-photon focal-plane-array detection.

In this paper, we discuss the development and operation of a scanning LADAR system. This system currently generates intensity and range images of a target with high spatial resolution located at a distance 5–10 m away from the sensor. The scanning LADAR system is designed with a purpose to generate polarization images of the target by integrating an in-line Stokes polarimeter in the receiver arm of the system. In this context, we have also discussed the basic design of the polarimeter using a liquid crystal retarder, and characterized the performance of the polarimeter for determining the polarization state of reflected light in the LADAR receiver.

A high precision laser altimeter was developed under the Autonomous Landing and Hazard Avoidance (ALHAT) project at NASA Langley Research Center. The laser altimeter provides slant-path range measurements from operational ranges exceeding 30 km that will be used to support surface-relative state estimation and navigation during planetary descent and precision landing. The altimeter uses an advanced time-of-arrival receiver, which produces multiple signal-return range measurements from tens of kilometers with 5 cm precision. The transmitter is eye-safe, simplifying operations and testing on earth. The prototype is fully autonomous, and able to withstand the thermal and mechanical stresses experienced during test flights conducted aboard helicopters, fixed-wing aircraft, and Morpheus, a terrestrial rocket-powered vehicle developed by NASA Johnson Space Center. This paper provides an overview of the sensor and presents results obtained during recent field experiments including a helicopter flight test conducted in December 2012 and Morpheus flight tests conducted during March of 2014.

The single photon sensitivity of Geiger-mode avalanche photo diodes (GmAPDs) has facilitated the development of LADAR systems that operate at longer stand-off distances, require lower laser pulse powers and are capable of imaging through a partial obscuration. In this paper, we describe a GmAPD LADAR system which operates at the eye-safe wavelength of 1541 nm. The longer wavelength should enhance system covertness and improve haze penetration compared to systems using 1064 nm lasers. The system is comprised of a COTS 1541 nm erbium fiber laser producing 4 ns pulses at 80 kHz to 450 kHz and a COTS camera with a focal plane of 32x32 InGaAs GmAPDs band-gap optimized for 1550 nm. Laboratory characterization methodology and results are discussed. We show that accurate modeling of the system response, allows us to achieve a depth resolution which is limited by the width of the camera’s time bin (.25 ns or 1.5 inches) rather than by the duration of the laser pulse (4 ns or 2 ft.). In the presence of obscuration, the depth discrimination is degraded to 6 inches but is still significantly better than that dictated by the laser pulse duration. We conclude with a discussion of future work.

Active imaging can be used for surveillance or target identification at long range and low visibility conditions. Its principle is based on the illumination of a scene with a pulsed laser which is then backscattered to the sensor. The signal to noise ratio and contrast of the object over the background are increased in comparison with passive imaging. Even though, range and field of view (FOV) are limited for a given laser power. A new active imaging system presented here aims at overcoming this limitation. It acquires the entire scene with a high-speed scanning laser illumination focused on a limited region, whereas at each scan the full frame active image is acquired. The whole image is then reconstructed by mosaicking all these successive images. A first evaluation of the performance of this system is conducted by using a direct physical model. This end-to-end model, realistic in terms of turbulence effects (scintillation, beam wandering ...), gives us a sequence of images a synthetic scenes. After presenting this model, a reconstruction method of the total scene is described. And the performances of this new concept are compared to those of a conventional flash active camera by using usual metrics ( SNR, MTF ...). For various mean laser powers, we quantify the gains expected in terms of range and field of view of this new concept.

We report a high average power pulsed Tm-doped fiber laser with one stage MOPA (master oscillation power amplifier) structure. The seed source is an AOM (acousto-optic modulation) Q-switched thulium fiber laser with an average power of 2W, the wavelength is 1996.7nm, and the line-width is about 0.1nm. By one stage MOPA, we obtain the maximum average output power of 16W with nanosecond pulse width at 41kHz repetition rate, the central wavelength is 1996.7nm, and the pulse width is less than 200ns, the polarization extinction ratio is better than 20 dB. The optical-tooptical conversion efficiency is 41%, and no nonlinear effect is observed.

We have developed the scanning laser sensor for underwater 3-D imaging which has the wide scanning angle of 120º (Horizontal) x 30º (Vertical) with the compact size of 25 cm diameter and 60 cm long. Our system has a dome lens and a coaxial optics to realize both the wide scanning angle and the compactness. The system also has the feature in the sensitivity time control (STC) circuit, in which the receiving gain is increased according to the time of flight. The STC circuit contributes to detect a small signal by suppressing the unwanted signals backscattered by marine snows. We demonstrated the system performance in the pool, and confirmed the 3-D imaging with the distance of 20 m. Furthermore, the system was mounted on the autonomous underwater vehicle (AUV), and demonstrated the seafloor mapping at the depth of 100 m in the ocean.

Atmospheric turbulence produces intensity modulation or "scintillation" effects on both on the outward laser-mode path and on the return backscattered radiation path. These both degrade laser radar (ladar) target acquisition, ranging, imaging, and feature estimation. However, the finite sized objects create scintillation averaging on the outgoing path and the finite sized telescope apertures produce scintillation averaging on the return path. We expand on previous papers going to moderate to strong turbulence cases by starting from a 20kft altitude platform and propagating at 0° elevation (with respect to the local vertical) for 100km range to a 1 m diameter diffuse sphere. The outward scintillation and inward scintillation effects, as measured at the focal plane detector array of the receiving aperture, will be compared. To eliminate hard-body surface speckle effects in order to study scintillation, Goodman's M-parameter is set to 10⁶ in the analytical equations and the non-coherent imaging algorithm is employed in Monte Carlo realizations. The analytical equations of the signal-to-noise ratio (SNRp), or mean squared signal over a variance, for a given focal plane array pixel window of interest will be summarized and compared to Monte Carlo realizations of a 1m diffuse sphere.

NASA’s Autonomous Landing and Hazard Avoidance Technologies (ALHAT) project is currently developing the critical technologies to safely and precisely navigate and land crew, cargo and robotic spacecraft vehicles on and around planetary bodies. One key element of this project is a high-fidelity Flash Lidar sensor that can generate three-dimensional (3-D) images of the planetary surface. These images are processed with hazard detection and avoidance and hazard relative navigation algorithms, and then are subsequently used by the Guidance, Navigation and Control subsystem to generate an optimal navigation solution. A complex, high-fidelity model of the Flash Lidar was developed in order to evaluate the performance of the sensor and its interaction with the interfacing ALHAT components on vehicles with different configurations and under different flight trajectories. The model contains a parameterized, general approach to Flash Lidar detection and reflects physical attributes such as range and electronic noise sources, and laser pulse temporal and spatial profiles. It also provides the realistic interaction of the laser pulse with terrain features that include varying albedo, boulders, craters slopes and shadows. This paper gives a description of the Flash Lidar model and presents results from the Lidar operating under different scenarios.

Optimized designs of the Navigation Doppler Lidar (NDL) instrument for Autonomous Landing Hazard Avoidance Technology (ALHAT) were accomplished via Interdisciplinary Design Concept (IDEC) at NASA Langley Research Center during the summer of 2013. Three branches in the Engineering Directorate and three students were involved in this joint task through the NASA Langley Aerospace Research Summer Scholars (LARSS) Program. The Laser Remote Sensing Branch (LRSB), Mechanical Systems Branch (MSB), and Structural and Thermal Systems Branch (STSB) were engaged to achieve optimal designs through iterative and interactive collaborative design processes. A preliminary design iteration was able to reduce the power consumption, mass, and footprint by removing redundant components and replacing inefficient components with more efficient ones. A second design iteration reduced volume and mass by replacing bulky components with excessive performance with smaller components custom-designed for the power system. Mechanical placement collaboration reduced potential electromagnetic interference (EMI). Through application of newly selected electrical components and thermal analysis data, a total electronic chassis redesign was accomplished. Use of an innovative forced convection tunnel heat sink was employed to meet and exceed project requirements for cooling, mass reduction, and volume reduction. Functionality was a key concern to make efficient use of airflow, and accessibility was also imperative to allow for servicing of chassis internals. The collaborative process provided for accelerated design maturation with substantiated function.

Photon counting lidar has an ultra-high sensitivity which can be hundreds even thousands of times higher than the linear detection lidar. It can significantly increase the system’s capability of detection rang and imaging density, saving size and power consumings in airborne or space-borne applications. Based on Geiger-mode Si avalanche photodiodes (Si-APD), a prototype photon counting lidar which used 8 APDs coupled with a 1×8-pixel fiber array has been made in June, 2011. The experiments with static objects showed that the photon counting lidar could operate in strong solar background with 0.04 receiving photoelectrons on average. Limited by less counting times in moving platforms, the probability of detection and the 3D imaging density would be lower than that in static platforms. In this paper, a latest fiber array coupled multi-channel photon counting, 3D imaging, airborne lidar system is introduced. The correlation range receiver algorithm of photon counting 3D imaging is improved for airborne signal photon events extraction and noise filter. The 3D imaging experiments in the helicopter shows that the false alarm rate is less than 6×10^-7, and the correct rate is better than 99.9% with 4 received photoelectrons and 0.7MHz system noise on average.

Optimized designs of the Navigation Doppler Lidar (NDL) instrument for Autonomous Landing Hazard Avoidance Technology (ALHAT) were accomplished via Interdisciplinary Design Concept (IDEC) at NASA Langley Research Center during the summer of 2013. Three branches in the Engineering Directorate and three students were involved in this joint task through the NASA Langley Aerospace Research Summer Scholars (LARSS) Program. The Laser Remote Sensing Branch (LRSB), Mechanical Systems Branch (MSB), and Structural and Thermal Systems Branch (STSB) were engaged to achieve optimal designs through iterative and interactive collaborative design processes. A preliminary design iteration was able to reduce the power consumption, mass, and footprint by removing redundant components and replacing inefficient components with more efficient ones. A second design iteration reduced volume and mass by replacing bulky components with excessive performance with smaller components custom-designed for the power system. Thermal modeling software was used to run steady state thermal analyses, which were used to both validate the designs and recommend further changes. Analyses were run on each redesign, as well as the original system. Thermal Desktop was used to run trade studies to account for uncertainty and assumptions about fan performance and boundary conditions. The studies suggested that, even if the assumptions were significantly wrong, the redesigned systems would remain within operating temperature limits.

Optimized designs of the Navigation Doppler Lidar (NDL) instrument for Autonomous Landing Hazard Avoidance Technology (ALHAT) were accomplished via Interdisciplinary Design Concept (IDEC) at NASA Langley Research Center during the summer of 2013. Three branches in the Engineering Directorate and three students were involved in this joint task through the NASA Langley Aerospace Research Summer Scholars (LARSS) Program. The Laser Remote Sensing Branch (LRSB), Mechanical Systems Branch (MSB), and Structural and Thermal Systems Branch (STSB) were engaged to achieve optimal designs through iterative and interactive collaborative design processes. A preliminary design iteration was able to reduce the power consumption, mass, and footprint by removing redundant components and replacing inefficient components with more efficient ones. A second design iteration reduced volume and mass by replacing bulky components with excessive performance with smaller components custom-designed for the power system. The existing power system was analyzed to rank components in terms of inefficiency, power dissipation, footprint and mass. Design considerations and priorities are compared along with the results of each design iteration. Overall power system improvements are summarized for design implementations.

In a typical waveform light detection and ranging (lidar) system, the received pulse can be represented by the convolution of the system impulse response, the outgoing pulse, and the underlying signal representing actual target interactions. Deconvolution is the process of removing the contribution of the system impulse response and outgoing pulse from the received signal, so that the true interactions may be seen. In many examples, deconvolution has been shown to expose fine structure within the waveform, which may be used to improve accuracy when estimating the vertical location of certain features. For instance, the exact location of the ground may be more accurately determined by separating the response of the ground from that of understory vegetation or vegetative ground cover. However, in order for the deconvolution to be successful, the impulse response and outgoing pulse must be known, and many deconvolution methods are sensitive to small errors in the estimation of these inputs. In this study, we propose a deconvolution method that uses a flat target response in place of the impulse response and outgoing pulse.

RIEGL LIDAR instruments are based on echo digitization and provide point cloud data by online waveform processing or full waveform data for external full waveform analysis or both. The advantages of online waveform processing of being fast and highly accurate for most typical target situation are made up by full waveform processing for demanding echo signal shapes when employing sophisticated algorithms. It is investigated how online waveform processing performs in turbid media and where the limitations are by analyzing experimental results when measuring in a fog chamber. An algorithm is proposed to determine the visibility range from the echo waveforms return of the medium.

The Eyesafe Ladar Test-bed (ELT) is an experimental ladar system with the capability of digitizing return laser pulse waveforms at 2 GHz. These waveforms can then be exploited off-line in the laboratory to develop signal processing techniques for noise reduction, range resolution improvement, and range discrimination between two surfaces of similar range interrogated by a single laser pulse. This paper presents the results of experiments with new deconvolution algorithms with the hoped-for gains of improving the range discrimination of the ladar system. The sparsity of ladar returns is exploited to solve the deconvolution problem in two steps. The first step is to estimate a point target response using a database of measured calibration data. This basic target response is used to construct a dictionary of target responses with different delays/ranges. Using this dictionary ladar returns from a wide variety of surface configurations can be synthesized by taking linear combinations. A sparse linear combination matches the physical reality that ladar returns consist of the overlapping of only a few pulses. The dictionary construction process is a pre-processing step that is performed only once. The deconvolution step is performed by minimizing the error between the measured ladar return and the dictionary model while constraining the coefficient vector to be sparse. Other constraints such as the non-negativity of the coefficients are also applied. The results of the proposed technique are presented in the paper and are shown to compare favorably with previously investigated deconvolution techniques.

A new development of on-board data processing platform has been in progress at NASA Langley Research Center since April, 2012, and the overall review of such work is presented in this paper. The project is called High-Speed On-Board Data Processing for Science Instruments (HOPS) and focuses on a high-speed scalable data processing platform for three particular National Research Council’s Decadal Survey missions such as Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS), Aerosol-Cloud-Ecosystems (ACE), and Doppler Aerosol Wind Lidar (DAWN) 3-D Winds. HOPS utilizes advanced general purpose computing with Field Programmable Gate Array (FPGA) based algorithm implementation techniques. The significance of HOPS is to enable high speed on-board data processing for current and future science missions with its reconfigurable and scalable data processing platform. A single HOPS processing board is expected to provide approximately 66 times faster data processing speed for ASCENDS, more than 70% reduction in both power and weight, and about two orders of cost reduction compared to the state-of-the-art (SOA) on-board data processing system. Such benchmark predictions are based on the data when HOPS was originally proposed in August, 2011. The details of these improvement measures are also presented. The two facets of HOPS development are identifying the most computationally intensive algorithm segments of each mission and implementing them in a FPGA-based data processing board. A general introduction of such facets is also the purpose of this paper.

Laser ranging measurements using incoherent pulse compression of complementary code pairs is reported. The two bipolar codes are converted to unipolar representations using a pulse position modulation algorithm, and used in succession in intensity modulation of a laser ranging source. Reflected echoes from a wall target are directly and incoherently detected. The cross-correlation between each of the two collected echoes and its respective, reference bipolar sequence, that is digitally stored at the receiver, is calculated. The two correlation functions are then added together. The off-peak aperiodic correlation functions of two codes sum up to zero, hence they are particularly suitable for low-sidelobe radar and laser ranging and detection systems. The scheme does not require the preservation of phase information in transmission or reception and provides superior sidelobe suppression compared with that of longer single codes. The code pairs are scalable to arbitrary lengths through simple procedures. Simulated and experimental ranging measurements in the presence of additive noise are discussed. The distance to the target could be recovered based on weak collected echoes, with an average optical power as low as 2 nW, without averaging over repeating measurements.

Protection of installations in hostile environments is a very critical part of military and civilian operations that requires a significant amount of security personnel to be deployed around the clock. Any electronic change detection system for detection of threats must have high probability of detection and low false alarm rates to be useful in the presence of natural motion of trees and vegetation due to wind. We propose a 3D change detection system based on a LIDAR sensor that can reliably and robustly detect threats and intrusions in different environments including surrounding trees, vegetation, and other natural landscape features. Our LIDAR processing algorithm finds human activity and human-caused changes not only in open spaces but also in heavy vegetated areas hidden from direct observation by 2D imaging sensors. The algorithm processes a sequence of point clouds called frames. Every 3D frame is mapped into a 2D horizontal rectangular grid. Each cell of this grid is processed to calculate the distribution of the points mapped into it. The spatial differences are detected by analyzing the differences in distributions of the corresponding cells that belong to different frames. Several heuristic filters are considered to reduce false detections caused by natural changes in the environment.

The creation of 3D imagery is an important topic in remote sensing. Several methods have been developed to create 3D images from fused ladar and digital images, known as texel images. These methods have the advantage of using both the 3D ladar information and the 2D digital imagery directly, since texel images are fused during data acquisition. A weakness of these methods is that they are dependent on correlating feature points in the digital images. This can be difficult when image perspectives are significantly different, leading to low correlation values between matching feature points. This paper presents a method to improve the quality of 3D images created using existing approaches that register multiple texel images. The proposed method incorporates relatively low accuracy measurements of the position and attitude of the texel camera from a low-cost GPS/INS into the registration process. This information can improve the accuracy and robustness of the registered texel images over methods based on point-cloud merging or image registration alone. In addition, the dependence on feature point correlation is eliminated. Examples illustrate the value of this method for significant image perspective differences.

Advances in LIDAR technology have made sub-meter resolutions from airborne instruments possible, enabling quick capture of fine 3D details over large areas. During collection, occluding objects may prevent a laser pulse from reaching regions where overlapping geometry is present, such as under tree canopies. This is particularly true given the near-nadir angles typically used by airborne LIDAR, since the limited number of unique angles does not ensure that all surfaces can be sensed. These missed surface detections decrease the overall quality of a dataset, but are not normally quantified due to a lack of ground-truth. Using information that is normally discarded about the LIDAR instrument position, we show how these unsampled regions can be identified by tracing the path of each laser pulse. A voxel representation provides the framework for computing the necessary statistics, and also allows for correct representations of overlapping geometry in complex environments. Based on this novel unsampled information we show how the fraction of total surfaces sensed and not sensed by the LIDAR can be estimated, giving a measurement of how completely all surfaces are sampled. Results are demonstrated for a real-world dataset, including the effects of voxel resolution and data density on the sampling completeness metric.

A novel approach using a support vector machine (SVM) is proposed to classify bare earth points in LiDAR point clouds. Using graph based segmentation, the LiDAR point cloud is segmented into a set of topological components. Several features establishing relationships from those components to their neighboring components are formulated. The SVM is then trained on the segment features to establish a model for the classification of bare earth and non bare earth points. Quantitative results are presented for training and testing the proposed SVM classifier on the ISPRS data set. Using the ISPRS data set as a training set, qualitative results are presented by testing the proposed SVM classifier on data downloaded from Open Topography; which covers a variety of different landscapes and building structures in Frazier Park, California. Despite the data being captured from different sensors, and collected from scenes with different terrain types and building structures, the results shown were processed with no parameter changes. Furthermore, a confidence value is returned indicating how well the unforeseen data fits the SVM’s trained model for bare earth recognition.

The advent of Light Detection and Ranging (LiDAR) point cloud collection has significantly improved the ability to model the world in precise, fine, three dimensional detail. The objective of this research was to demonstrate accurate, foundational methods for fusing LiDAR data and photogrammetric imagery and their potential for change detection. The scope of the project was to investigate optical image-to-LiDAR registration methods, focusing on dissimilar image types including high resolution aerial frame and WorldView-1 satellite and LiDAR with varying point densities. An innovative optical image-to-LiDAR data registration process was established. Comparison of stereo imagery point cloud data to the LiDAR point cloud using a 90% confidence interval highlighted changes that included small scale (< 50cm), sensor dependent change and large scale, new home construction change.

Change detection using remote sensing has become increasingly important for characterization of natural disasters. Pre- and post-event LiDAR data can be used to identify and quantify changes. The main challenge consists of producing reliable change maps that are robust to differences in collection conditions, free of processing artifacts, and that take into account various sources of uncertainty such as different point densities, different acquisition geometries, georeferencing errors and geometric discrepancies. We present a simple and fast technique that accounts for these sources of uncertainty, and enables the creation of statistically significant change detection maps. The technique makes use of Bayesian inference to estimate uncertainty maps from LiDAR point clouds. Incorporation of uncertainties enables a change detection that is robust to noise due to ranging, position and attitude errors, as well as "roughness" in vegetation scans. Validation of the method was done by use of small-scale models scanned with a terrestrial LiDAR in a laboratory setting. The method was then applied to two airborne collects of the Monterey Peninsula, California acquired in 2011 and 2012. These data have significantly different point densities (8 vs. 40 pts/m2) and some misregistration errors. An original point cloud registration technique was developed, first to correct systematic shifts due to GPS and INS errors, and second to help measure large-scale changes in a consistent manner. Sparse changes were detected and interpreted mostly as construction and natural landscape evolution.

Terrestrial LiDAR scans of building models collected with a FARO Focus3D and a RIEGL VZ-400 were used to investigate point-to-point and model-to-model LiDAR change detection. LiDAR data were scaled, decimated, and georegistered to mimic real world airborne collects. Two physical building models were used to explore various aspects of the change detection process. The first model was a 1:250-scale representation of the Naval Postgraduate School campus in Monterey, CA, constructed from Lego blocks and scanned in a laboratory setting using both the FARO and RIEGL. The second model at 1:8-scale consisted of large cardboard boxes placed outdoors and scanned from rooftops of adjacent buildings using the RIEGL. A point-to-point change detection scheme was applied directly to the point-cloud datasets. In the model-to-model change detection scheme, changes were detected by comparing Digital Surface Models (DSMs). The use of physical models allowed analysis of effects of changes in scanner and scanning geometry, and performance of the change detection methods on different types of changes, including building collapse or subsistence, construction, and shifts in location. Results indicate that at low false-alarm rates, the point-to-point method slightly outperforms the model-to-model method. The point-to-point method is less sensitive to misregistration errors in the data. Best results are obtained when the baseline and change datasets are collected using the same LiDAR system and collection geometry.

When LiDAR data are collected, the intensity information is recorded for each return, and can be used to produce an image resembling those acquired by passive imaging sensors. This research evaluated LiDAR intensity data to determine its potential for use as baseline imagery where optical imagery are unavailable. Two airborne LiDAR datasets collected at different point densities and laser wavelengths were gridded and compared with optical imagery. Optech Orion C200 laser data were compared with a corresponding 1541 nm spectral band from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Optech ALTM Gemini LiDAR data collected at 1064 nm were compared to the WorldView-2 (WV-2) 949 – 1043 nm NIR2 band. Intensity images were georegistered and spatially resampled to match the optical data. The Pearson Product Moment correlation coefficient was calculated between datasets to determine similarity. Comparison for the full LiDAR datasets yielded correlation coefficients of approximately 0.5. Because LiDAR returns from vegetation are known to be highly variable, a Normalized Difference Vegetation Index (NDVI) was calculated utilizing the optical imagery, and intensity and optical imagery were separated into vegetation and nonvegetation categories. Comparison of the LiDAR intensity for non-vegetated areas to the optical imagery yielded coefficients greater than 0.9. These results demonstrate that LiDAR intensity data may be useful in substituting for optical imagery where only LiDAR is available.

We design a kind of imaging LiDAR with sixteen channels, which consists of a fiber laser source, dual scanning galvanometers, range measurement circuits and information processing circuits etc. The image LiDAR provides sixteen range measurements for one laser shot and the distance accuracy of each channel is about 4cm. This paper provides a calibrate method to correct point cloud images captured with the multi-channel LiDAR. The method needs to construct different slanted planes to cover the imaging field, and establish precise plane equations in the known ground coordinates, then fit planes with point clouds data and calculate correction parameters of all channels through the error model. The image accuracy is better than 5cm processed by this calibration method.

Laser Rangefinders are well established components in various electro-optical fire control systems. Recent range finders are often operating at eye safe wavelengths around 1.5 μm which extend their utility. One such extension is the use of the sensor for atmospheric sensing based on the measured backscatter signal. The present paper investigates the use of an eye-safe laser rangefinder at 1.5 μm to obtain information on atmospheric attenuation at various paths in the atmosphere. This knowledge can in turn be used in combination with atmospheric and target/background models to estimate the performance of other EO sensors like TV and thermal imagers beside the laser range finder itself. Such information can be of great value both for estimating own sensor capabilities at a given moment as well as estimating the threat capability. One obvious example is ship defense where it is difficult to obtain visibility along a variable atmosphere especially in darkness. The paper will describe the experimental equipment and the results from measurements of atmospheric backscatter along various atmospheric paths. The backscatter curve is used to evaluate the extinction. This extinction values are compared with those deduced from a point visibility meter and from echo measurements against two similar nets positioned at 2 ranges from the sensor. The results indicated a good correspondence between these results. Finally the results are illustrated in a system perspective by estimating the performance for thermal IR and other EO sensors.

In this paper, we describe the development of a prototype differential absorption fluorescence lidar for nighttime tropospheric formaldehyde (H₂CO) concentration profiling. H₂CO has a strong absorption band in the 352-357nm region and fluoresces strongly in the 390-500nm region. Here, we obtain high sensitivity (∼0.1ppb) measurements of H₂CO profiles from differential fluorescence signals obtained by injection seeding a Nd:YVO laser and tuning its wavelength on and off the peak of a strong absorption line. The fluorescence signal strength is further improved by using a multi-line bandpass filter whose pass-bands are aligned to multiple fluorescence peaks of H₂CO. A H₂CO filled photo-acoustic absorption cell is utilized for tuning the seed laser wavelength to the center of absorption line.

In this paper, we describe the development of a three-beam elastic lidar that utilizes aerosol backscatter correlation to measure three-component wind profiles for detecting and tracking aircraft wake vortices; turbulence intensity and wind shear profiles. High-resolution time-resolved wind information can currently be obtained with ultrasonic or hot-wire anemometers suitable for local point measurements, or with Doppler wind lidars that only measure line-of-sight wind speeds and have to be scanned over large measurement cone angles for obtaining three-component winds. By tracking the motion of aerosol structures along and between three near-parallel laser beams, our lidar obtains three-component wind speed profiles along the field of view (FOV) of the lidar beams. Our prototype lidar wind profiler (LWP) has three 8-inch transceiver modules placed in a near-parallel configuration on a two-axis pan-tilt scanner to measure winds up to 2km away. Passively q-switched near-infrared (1030nm) Yb:YAG lasers generate 12 - 18ns wide pulses at high repetition rate (about 10KHz) that are expanded and attenuated to eye-safe levels. Sensitive low noise detection is achieved even in daytime using a narrow FOV receiver, together with narrowband interference filters and single photoncounting Geiger-mode Si detectors. A multi-channel scaler retrieves the lidar return with 7.8ns bins (∼1.2m spatial resolution) and stores accumulated counts once every 50ms (20 profiles/sec). We adapted optical flow algorithms to obtain the movement of aerosol structures between the beams. The performance of our prototype LWP was validated using sonic anemometer measurements.

A review of current lidar techniques summarizes present capabilities to: (1) measure atmospheric concentrations of most major and several minor molecular species using Raman scattering and DIAL techniques, (2) detect and measure concentrations of certain trace level species, (3) characterize active dynamical processes in the troposphere based upon using water vapor as a tracer, and (4) describe interesting thermodynamic properties based upon rotational Raman temperature profiles, multi-wavelength aerosol distributions, and changes in the phase states of water. Advances in lasers and detectors have extended the range of wavelengths available through the ultraviolet, visible, and infrared spectrum by using tunable laser techniques and supercontinuum broad spectrum lasers. Prior studies are reviewed, several applications for the technology are suggested which extend the techniques proposed to future investigations. In particular, the extension of tunable laser sources into the ultraviolet region has opened opportunities to use resonance Raman techniques, which provide greatly increased sensitivity for certain molecular species, such as hydrocarbons. The developments of supercontinuum lasers and tunable OPO lasers has enabled long-path trace concentration measurements of molecular spectra lines to detect and measure the concentrations of many species, as well as to distinguish any interfering species.

Identification of atmospheric aerosol species and their chemical composition may help to trace their source and better estimate their impact on climate and environment. Optical scattering of aerosols depends primarily on aerosol chemical composition, size distribution, particle shape and the wavelength used. Extraction of features due to the aerosol complex refractive index from scattering spectroscopy at a single angle of observation allows composition identification via the spectral fingerprint, as shown computationally with Mie calculations of the optical scattering. Size-dependent scattering effects are eliminated by using near-forward scattering, such as in the scattering aureole. The only features of the aerosol aureole scattering spectra that very rapidly with wavelength are associated with the composition, so the aureole can give a reliable identification of aerosol composition.

The latest flight demonstration of Doppler Aerosol Wind Lidar (DAWN) at NASA Langley Research Center (LaRC) is presented. The goal of the campaign was to demonstrate the improvement of DAWN system since the previous flight campaign in 2012 and the capabilities of DAWN and the latest airborne wind profiling algorithm APOLO (Airborne Wind Profiling Algorithm for Doppler Wind Lidar) developed at LaRC. The comparisons of APOLO and another algorithm are discussed utilizing two and five line-of-sights (LOSs), respectively. Wind parameters from DAWN were compared with ground-based radar measurements for validation purposes. The campaign period was June – July in 2013 and the flight altitude was 8 km in inland toward Charlotte, NC, and offshores in Virginia Beach, VA and Ocean City, MD. The DAWN system was integrated into a UC12B with two operators onboard during the campaign.

High stability and energy-efficient TE–CO₂ laser pulse clipper using gas breakdown techniques for high spatial resolution chemical plume detection is presented. The most dominant time constant, attributed to TE–CO₂ unclipped laser pulses, is its nitrogen tail which extends for several microseconds beyond the gain-switched spike. Near-field scattered signal, produced by unclipped laser pulses, interferes with the weak signal backscattered from the long range and far field atmospheric aerosols which ultimately degrades the range resolution of LIDARS to some hundreds of meters. Short laser pulses can be obtained by various techniques such as mode locking, free induction decay, pulse slicing with electro-optic switched. However, output pulses from these require further amplification for any useful application due to their very low energy content. This problem is circumvented in this work by the use of a plasma clipper that achieves high range-resolved remote sensing in the atmosphere. Complete extinction of the nitrogen tail is obtained at pressures extending from 375 up to 1500 Torr for nitrogen and argon gases and approximately 10⁵, for helium. Optimum pressures for helium, argon, and nitrogen, that provide the best stability of the transmitted energy and complete extinction of the nitrogen tail, are identified. Excellent range resolutions can be achieved with TE–CO₂ laser-based LIDAR systems. Clipped laser pulses are also field tested.

The purpose of this research is to evaluate scintillation fluctuations on optical communication lasers and evaluate potential system improvements to reduce scintillation effects. This research attempts to experimentally verify mathematical models developed by Andrews and Phillips [1] for scintillation fluctuations in atmospheric turbulence using two different transmitting wavelengths. Propagation range lengths and detector quantities were varied to confirm the theoretical scintillation curve. In order to confirm the range and wavelength dependent scintillation curve, intensity measurements were taken from a 904nm and 1550nm laser source for an assortment of path distances along the 1km laser range at the Townes Laser Institute. The refractive index structure parameter (Cn²) data was also taken at various ranges using two commercial scintillometers. This parameter is used to characterize the strength of atmospheric turbulence, which induces scintillation effects on the laser beam, and is a vital input parameter to the mathematical model. Data was taken and analyzed using a 4-detector board array. The material presented in this paper outlines the verification and validation of the theoretical scintillation model, and steps to improve the scintillation fluctuation effects on the laser beam through additional detectors and a longer transmitting wavelength. Experimental data was post processed and analyzed for scintillation fluctuations of the two transmitting wavelengths. The results demonstrate the benefit of additional detectors and validate a mathematical model that can be scaled for use in a variety of communications or defense applications. Scintillation is a problem faced by every free space laser communication system and the verification of an accurate mathematical model to simulate these effects has strong application across the industry.

We introduce a new concept of the Internal Anisotropy (IA) for the homogeneous and isotropic random fields. IA reflects the hidden structures that can exist in the samples of the random field, and are not revealed by the simplest, single and two-point statistical moments. There is presently no established theory of the IA, and no quantitative metrics of IA are available. It is understood, however, that IA cannot be present in any stationary isotropic Gaussian random field, or any single-point transformations of it. We illustrate the IA concept on a simple toy model of two-dimensional random field, and show that IA can affect the third and higher-order multipoint statistical moments. We generate samples of the random irradiance distributions for the plane wave passed through a phase screen with the quasi- Kolmogorov statistics. Visual evaluation suggests the presence of the IA in the irradiance samples. The statistical analysis reveals that the three-point third moment of irradiance exhibit the features consistent with the IA, especially in the focusing conditions. Conditional probabilities of the irradiance gradient components also proved to be sensitive to the IA. We discuss the role of the IA for optimal placement of the multiple receivers of the FSO system using the spatial diversity for fade mitigation.

We simulate the propagation of both a partially spatially coherent infra-red (IR) and a visible laser beam through a turbulent atmosphere, and we compare the intensity fluctuations produced in the simulation to the intensity fluctuations that are observed in both maritime and terrestrial environments at the US Naval Academy. We focus on the effect of the level of turbulence and the degree of the beam's spatial coherence on the receiver scintillations, and we compare the probability density function (PDF) of the intensity in our simulation to the experimental data. We also investigate the effect of optical beam spreading on the coherent and partially coherent laser beams along the propagation path.

Experiments were conducted over a retro-reflecting link using both a monostatic and a bistatic laser interrogator that operated over adjacent terrestrial paths of ranges between 2 and 4km. Data communications parameters were monitored on the bistatic channel and irradiance measurements were recorded on both interrogators simultaneously. The off-axis bistatic receiver was 75mm in diameter and showed the advantage of both aperture averaging and uncorrelated irradiance components in comparison with the 28mm receiver used in the on-axis monostatic system. The normalized flux variance measured in the bistatic receiver peaked at a value close to 1 while the on-axis system saw corresponding levels of about 10 under sunlit midday conditions.

Atmospheric turbulence causes the receive signal intensity on free space optical (FSO) communication links to vary over time. Scintillation fades can stymie connectivity for milliseconds at a time. To approach the information-theoretic limits of communication in such time-varying channels, it necessary to either code across extremely long blocks of data – thereby inducing unacceptable delays – or to vary the code rate according to the instantaneous channel conditions. We describe the design, hardware implementation, and system performance of an FSO modem that employs low-density parity-check (LDPC) coding in an incremental redundancy (IR) hybrid automatic repeat request (HARQ) protocol. Independent tests performed by the U.S. Government demonstrate that our protocol effectively adapts the LDPC code rate to match the instantaneous channel conditions. For links with fixed throughput, this translates to the longest possible range in the presence of optical scintillation; for links with fixed range, this translates to the highest possible average throughput. By leveraging an LDPC that is amenable to low-complexity, high-throughput implementation in hardware, our modem is able to provide throughputs in excess of 850 Mbps on links with ranges greater than 15 kilometers.

IERUS Technologies, Inc. and the University of Alabama in Huntsville have partnered to perform characterization and development of algorithms and hardware for adaptive optics. To date the algorithm work has focused on implementation of the stochastic parallel gradient descent (SPGD) algorithm. SPGD is a metric-based approach in which a scalar metric is optimized by taking random perturbative steps for many actuators simultaneously. This approach scales to systems with a large number of actuators while maintaining bandwidth, while conventional methods are negatively impacted by the very large matrix multiplications that are required. The metric approach enables the use of higher speed sensors with fewer (or even a single) sensing element(s), enabling a higher control bandwidth. Furthermore, the SPGD algorithm is model-free, and thus is not strongly impacted by the presence of nonlinearities which degrade the performance of conventional phase reconstruction methods. Finally, for high energy laser applications, SPGD can be performed using the primary laser beam without the need for an additional beacon laser. The conventional SPGD algorithm was modified to use an adaptive gain to improve convergence while maintaining low steady state error. Results from laboratory experiments using phase plates as atmosphere surrogates will be presented, demonstrating areas in which the adaptive gain yields better performance and areas which require further investigation.

In order to better understand laser beam propagation through the analysis of the fluctuations in scintillation data, images from a 30 frame per second monochrome camera are utilized. Scintillation is the effect of atmospheric turbulence which is known to disrupt and alter the intensity and formation of a laser signal as it propagates through the atmosphere. To model and understand this phenomenon, recorded video output of a laser upon a target screen is inspected to determine how much of an effect the atmospheric turbulence has disrupted the laser signal as it has been propagated upon a set distance. The techniques of data processing outlined in this paper moves toward a software-based approach of determining the effects of propagation and detection of a laser based on the visual fluctuations caused by the scintillation effect. With the aid of such visual models, this paper examines the idea of implementing mathematical models via software that is then validated by the gathered video data taken at Kennedy Space Center.

Optical modulating retro-reflectors (MRRs) can allow free space optical (FSO) links to platforms too small to carry a conventional FSO terminals. However, retro-reflectors suffer from very high optical scintillation due to the double-pass nature of the link. For links near the ground, scintillation indices greater than 10 are often observed during daytime hours. This strong scintillation causes deep and frequent fades. Spatial and temporal diversity can be powerful tools to reduce the effects of scintillation on MRR links. Experiments were conducted in which several retro-reflectors were simultaneously illuminated to measure the fade statistics of retroreflector links. The dependence of scintillation on the number and spacing of these retro-reflectors was measured. Under optimal conditions the scintillation index was shown to decrease approximately linearly with the number of retroreflectors. The recorded intensity waveforms were analyzed to determine the frequency, duration and depth of fades. The effects of using temporal diversity, in which duplicate data packets are sent multiple times, was analyzed to determine the reduction in required margin as a function of the number of times a packet was resent, and the spacing in time between packets. The analysis showed that spatial and temporal diversity, used in combination, can reduce the required margin for MRR links in strong turbulence by more than 20 dB.

In free space optical communication, photodetectors serve not only as communications receivers but as position sensitive detectors (PSD) for pointing, tracking, and stabilization. Typically, two separate detectors are utilized to perform these tasks but recent advances in the fabrication and development of large area, low noise avalanche photodiode (APD) arrays have enabled these devices to be used both as PSDs and as data communication receivers. This combined functionality allows for more flexibility and simplicity in optical assembly design without sacrificing the sensitivity and bandwidth performance of smaller, single element data receivers. This work presents a large area, five element concentric avalanche photodiode array rated for bandwidths beyond 1GHz with a measured carrier ionization ratio of approximately 0.2 at moderate APD gains. We discuss the integration of this array in a bi-static optical interrogator where it acts as a data receiver and provides position information for pointing and stabilization. In addition to front-end and digital electronics design, we also describe the optical assembly design and the development of a pointing and stabilization algorithm.

The Georgia Tech Research Institute (GTRI) is developing a transportable multi-lidar instrument known as the Integrated Atmospheric Characterization System (IACS). The system will be housed in two shipping containers that will be transported to remote sites on a low-boy trailer. IACS will comprise three lidars: a 355 nm imaging lidar for profiling refractive turbulence, a 355 nm Raman lidar for profiling water vapor, and an aerosol lidar operating at 355 nm as well as 1.064 and 1.627 µm. All of the lidar transmit/receive optics will be on a common mount, pointable at any elevation angle from 10 degrees below horizontal to vertical. The entire system will be computer controlled to facilitate pointing and automatic data acquisition. The purpose of IACS is to characterize optical propagation paths during outdoor tests of electro-optical systems. The tests are anticipated to include ground-to-ground, air-to-ground, and ground-to-air scenarios, so the system must accommodate arbitrary slant paths through the atmosphere, with maximum measurement ranges of 5-10 km. Elevation angle scans will be used to determine atmospheric extinction profiles at the infrared wavelengths, and data from the three wavelengths will be used to determine the aerosol Angstrom coefficient, enabling interpolation of results to other wavelengths in the 355 nm to 1.627 µm region.

Tele-operated robots used for Explosive Ordnance Disposal (EOD) are ordinarily controlled using a radio frequency (RF) link. Use of RF links on the battlefield presents several challenges including spectrum allocation and jamming effects (both by the enemy and friendly forces). Several solutions have been attempted including electrical or fiber optic umbilicals and spread spectrum radios with varying degrees of success. Modulating Retro-reflector Free Space Optical (MRR-FSO) communications links avoid these effects entirely but are limited to line of sight operation. We have developed a system consisting of an MRR-FSO link with a tracking optical terminal, a conventional RF link and a deployable pod to provide a relay node bridging the FSO link to the operator and the RF link to the robot. The MRRFSO link provides the capability to operate the robot in the presence of jamming while the RF link allows short range non line of sight operation. The operator uses the MRR-FSO link to drive the robot to a position downrange outside the influence of the jammer or other interference. Once the robot is positioned downrange near the area of operation the pod is deployed. This allows the robot to maneuver freely including venturing beyond line of sight using the short range RF link to maintain communications between the vehicle and pod while the FSO link maintains connectivity between the pod and the operator.

High bandwidth, fast deployment with relatively low cost implementation are some of the important advantages of free space optical (FSO) communications. However, the atmospheric turbulence has a substantial impact on the quality of a laser beam propagating through the atmosphere. A new method was presented in [1] and [2] to perform bit synchronization and detection of binary Non-Return-to-Zero (NRZ) data from a free-space optical (FSO) communication link. It was shown that, when the data is binary NRZ with no modulation, the Haar wavelet transformation can effectively reduce the scintillation noise. In this paper, we leverage and modify the work presented in [1] in order to provide a real-time streaming hardware prototype. The applicability of these concepts will be demonstrated through providing the hardware prototype using one of the state-of-the-art reconfigurable hardware, namely Field Programmable Gate Arrays, and highly productive high-level design tools such as System Generator for DSP from Xilinx.