This PDF file contains the front matter associated with SPIE Proceedings Volume 10636, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

Imaging for long-range target classification has its practical limitations due to the demand on high transverse sensor resolution connected to small pixel sizes, long focal lengths and large aperture optics. It is therefore motivated to look at other techniques like laser range profiling where the demand on transverse resolution is moderate but high in the depth domain.

Laser range profiling is attractive because it can be seen as an extension from an ordinary laser range finder. The same laser can also be used for active imaging when the target comes closer and is angular resolved. This paper will discuss laser profiling for target recognition both as a standalone method and in combination with low transverse resolution imaging. Example of both simulated and experimental data for stationary and in flight targets will be investigated and analyzed for target classification purposes.

Various drone detection systems (DDS) have been recently developed for civil and military applications. Such DDS are generally based on radio frequency (RF) radars, detecting control signals between drones and their pilots, drone's acoustic noise, optical surveillance, or a combination of these. However, existing DDS have safety critical gaps. For example, none of the current state-of-the-art technologies provide remote payload monitoring or verification. The registered payload of some commercial drones can be greatly increased by simple re-configuration procedures that may not be detected by current DDS. This study introduces patent-pending methods for remote identification and payload monitoring of standard and modified drones. Structural frequencies, measured by a long-range laser vibrometer, of commercial drones are proposed as a unique signature for remotely verifying registered specifications of a drone, e.g., payload capacity. In addition, a method is proposed to measure payload capacity of unknown drones based on their motion performance monitored via a motion dynamic model and a laser Doppler vibrometer. Preliminary flight tests have been successfully conducted for a group of standard and modified drones by the Institute of Flight Systems, DLR (German Aerospace Center).

This paper reviews early evaluations of the Neptec Technologies 3D LiDAR sensor’s capabilities for the security markets related to aerial and surface threats. Aerial threats are primarily focused on drone detection, while surface threats include perimeter security on the ground or over water. The OPAL LiDAR uses a Risley-prism pair mechanism to generate unique scan patterns, offering the advantage of rapid and tight coverage of the Field-of-View (FOV). Field trials were conducted for characterizing the detection capability of small drones, such as the DJI Phantom-3. The main variables for the testing included; distance from sensor to the drone, speed, and trajectory as well as specific LiDAR intrinsic settings. Similar field trials have been conducted for perimeter incursions over land and water. A predictive model has been developed for the probability of detection of small targets, taking into account the LiDAR’s optomechanical settings in relation to the target size and reflectivity. The results obtained from these trials is presented and compared to the predictive model.

The number of reported incidents caused by UAVs, intentional as well as accidental, is rising. To avoid such incidents in future, it is essential to be able to detect UAVs. LiDAR systems are well known to be adequate sensors for object detection and tracking. In contrast to the detection of pedestrians or cars in traffic scenarios, the challenges of UAV detection lie in the small size, the various shapes and materials, and in the high speed and volatility of their movement. Due to the small size of the object and the limited sensor resolution, a UAV can hardly be detected in a single frame. It rather has to be spotted by its motion in the scene. In this paper, we present a fast approach for the tracking and detection of (low) flying small objects like commercial mini/micro UAVs. Unlike with the typical sequence -track-after-detect-, we start with looking for clues by finding minor 3D details in the 360° LiDAR scans of scene. If these clues are detectable in consecutive scans (possibly including a movement), the probability for the actual detection of a UAV is rising. For the algorithm development and a performance analysis, we collected data during a field trial with several different UAV types and several different sensor types (acoustic, radar, EO/IR, LiDAR). The results show that UAVs can be detected by the proposed methods, as long as the movements of the UAVs correspond to the LiDAR sensor’s capabilities in scanning performance, range and resolution. Based on data collected during the field trial, the paper shows first results of this analysis.

We have demonstrated an optical scanner based on beam switching method fabricated on silicon photonics integrated circuit. Scanner is based on beam switching method. Scanner is composed of ring resonator multiplexer and grating array. Multiplexer determines the optical path and one of grating is selected for emitter. The scanning angle was 6 degree. Solid state scanner is suitable for Laser intensity direction and ranging (LIDAR) because of reliability and small factor. We fabricated and demonstrated an optical scanner based on beam switching method fabricated on silicon photonics integrated circuit. Scanner is all solid state and movement-free. Scanner is composed of ring resonator multiplexer and grating array. Multiplexer determines the optical path and one of grating is selected for emitter. LIDAR is promising sensor for automated cruising for automotive application and this report is considered to be a remarkable technology.

The designed laser radar (LADAR) system utilize a Geiger focal plane array (FPA) of 16x16 resolution which limits the field of view (FOV) of the system. To overcome this, an additional scanner module consists of 4 rotational wedges was placed in front of the optical system. Naturally, the cases to analyze as a part of the stray light analysis became extremely complex and abundant. To sort out the major cases out of all possible scenarios, the stray light analysis was performed separately according to the modules. The ghost analysis was performed backward from the FPA to the front of the optics.

A partial calibration technique for a 128 × 128 pin diode 3D flash LIDAR camera is presented. This paper presents dark non-uniformity correction (NUC) of a 3D flash LIDAR camera using dark frame subtraction. Dark frames are taken near threshold for intensity return to generate simultaneous trigger on a flash LIDAR camera, with trigger ramp set to zero for both range and intensity returns. Frames are cropped to a region of interest (ROI) and concatenated ideal dark intensity and dark range return into dark frames, processed into calibration files with nearest neighbor correction in dark intensity frames to correct out slowly varying, high intensity temporal noise when operating near threshold. Results and validation of applied NUC on 3D flash LIDAR camera are presented. We characterize a 3D flash LIDAR camera with PIN diode architecture including range walk, gain characterization in both intensity and range domains. Characterization of 3D flash LIDAR imager was performed using a fiber laser operating at 1550 nm, 20 μJ energy per pulse, TTL triggering, a pulse generator to generate time delay necessary for triggering the laser from the camera ARM signal, and an attenuator for fine control of the output signal. Time delay is relative to the range domain, whereas output signal is relative to the intensity domain.

The objective of this research is to model anisoplanatic atmospheric effects for synthetically generated Synthetic Aperture Ladar (SAL) data, and to evaluate the impact of these effects on target classification in SAL imagery. Although SAL wavelengths present key advantages in target exploitation, they are heavily susceptible to atmo- spheric turbulence; hence the inclusion of atmospheric effects in simulation is crucial. With utilization of an atmospheric modeling toolbox, we introduce the ability to model anisoplanatic atmospheric effects into a ray tracing simulation tool. We show image classification results as a function of atmospheric severity.

In order to develop LADAR-based sensors that satisfy the cost, size, weight, and power constraints imposed by increasingly demanding systems, new LADAR architectures need to be developed to support requirements in areas such as intelligence, surveillance, and reconnaissance. Knowledge of the spectral reflectivity of objects in a complex scene may prove useful to distinguish object from background, or even to identify partially occluded objects where a full set of identifying pixels may be impossible to measure. We present a novel LADAR architecture to enable spectral reflectivity measurement with a single pulse of a multispectral laser and a single receiver detector, eliminating spectrally dispersive elements which spatially multiplex the return signal to multiple detectors. This is accomplished by exploiting the wavelength-dependent temporal waveforms that arise from stimulated Raman scattering based multispectral laser sources to multiplex multispectral signals inside a single pulse envelope. With knowledge of these effects in a transmitted laser pulse, a measured pulse envelope at the receiver can be modeled as a sum of reflectivity-scaled spectral components, and the individual object reflectivities estimated. The system performance of this architecture is evaluated using measured pulses of a Raman-based multispectral fiber laser to simulate the measurement of objects of interest, including the influence of detector noise. System performance is quantified by calculating the target reflectivity estimation error as a function of signal-to-noise ratio, receiver bandwidth, and receiver sample rate, demonstrating the feasibility of a temporally multiplexed architecture.

Avalanche photodiodes operated in Geiger mode provide single-photon detection with excellent timing accuracy on a scalable semiconductor device platform, and they have been shown to enable high-rate collection of 3D LiDAR imagery from airborne platforms at extremely long (>10 km) stand-off distances. More recently, we have applied Geiger-mode technology to shorter range LiDAR systems designed for high-performance, low-cost automotive applications. The combination of two factors-single-photon sensitivity and the greater eye-safety of lasers at wavelengths beyond 1400 nm-provides disruptive automotive LiDAR range and resolution that will be essential to future autonomous vehicle navigation.

This paper presents research at the Army Research Laboratory (ARL) on a laser radar (LADAR) imager for surveillance from small unmanned air vehicles (UAV). The LADAR design is built around a micro-electro-mechanical system (MEMS) mirror and a low-cost pulsed erbium fiber laser to yield a low-cost, compact, and low-power system. In the simplest sense the LADAR measures the time-of-flight of a short laser pulse to the target and return as a means to determine range to a target. The two-axis MEMS mirror directs the light pulse to a point in the scene and establishes the angular direction to a pixel. The receiver looks over the entire region scanned by the laser and produces a voltage proportional to the amount of laser light reflected from the scene. The output of the receiver is sampled by an analog-to-digital convertor. The net result is a data file containing a range and a horizontal and vertical angle that identifies the position of every image voxel in the scene and its amplitude. This data is displayed on a computer using standard and stereo techniques to render a three-dimensional image of the scene. At this time, the LADAR operating parameters are set to form images of 256 (h) × 128 (v) pixels over a 15° × 7.5° field of view and 50 m range swath at a 5-6 Hz frame-rate to 160 m range. In the prior year, we built an initial flight package that we have flown in an auto-gyro that yielded encouraging imagery of ground targets at an altitude of roughly 100 m. Here we discuss progress to improve the performance of the LADAR to image at an altitude of 160 m and increase its mechanical robustness for extensive data collection activities.

We have built a small passively Q-switched solid-state laser with a volume of < 8 cm³ and a weight of < 20 g. The laser is passively Q-switched using a Cr⁴⁺ :YAG saturable absorber to generate pulses < 2 ns. The architecture is applied to different laser crystals such as Nd:YLF and Nd:YVO₄ that produced 2 mJ at 20 Hz and 0.3 mJ at 10 kHz, respectively. The laser is side-pumped by single or stacked diode bars using a unique pump cavity to homogenize the pump intensity in the laser rod as well as make the structure alignment insensitive when subjected to shock, vibration, and thermal cycling. The laser components can easily be modified to change the output wavelength to green, UV, or mid IR.

This paper reports an electrothermal MEMS mirror-based LiDAR system. The MEMS mirror has a low driving voltage of 9 V and a large mirror aperture of 2 mm in diameter. The working range of this system is 80 to 250 cm with a distance resolution of 7.2 cm. The complete LiDAR prototype can fit into a small volume of 100 mm×100 mm×60 mm with the weight under 100 g. The use of such a MEMS mirror can greatly reduce the weight, size and power of LiDAR modules, making it possible for small UAVs to carry LiDAR for accurate navigation.

The well-known Langley extrapolation technique produces measurements of atmospheric optical depth (AOD) by collecting direct sun irradiance at multiple zenith angles. One common application of this technique is used by sun photometers such as in NASA’s AErosol Robotic Network (AERONET). This large, spatially distributed network collects time averaging data from across the globe and applying Beer’s Law, produces hourly estimates of AOD. While this technique has produced excellent data, the dependence on direct sun irradiance requires cloudless skies and line-ofsight to the sun. Atmospheric LIDARs, on the other hand, can operate in the presence of clouds and can also produce range-resolved measurements of AOD by applying the same Langley technique. For aerosol LIDARs, this technique requires that the LIDAR be capable of producing high quality waveforms within the atmospheric coherence time and also be capable of taking measurements off zenith. At least two unique angles are required to produce data, although 3+ are recommended. This paper will present an overview of the Langley technique applied with a 1064 nm atmospheric aerosol LIDAR, an overview of the LIDAR hardware and capabilities, sample data collected by the LIDAR, and challenges associated with this technique. It will be shown that while this technique is useful, it requires measurements at all three angles to be made when the atmosphere is reasonably horizontally homogenous. Furthermore, the system optics, alignment, and laser power must be kept constant (keeping the LIDAR’s system constant the same for all measurements) for the data to be useful in a Langley analysis.

The major unknown in the global climate radiation balance calculations is the effect of aerosols. The extinction of aerosols depends upon the wavelength, size, concentration, composition, and to a lesser extent, shape of the aerosols. Thus, methods are needed to determine and model these quantities. The size distribution of larger aerosols can be monitored with multistatic lidar, at least in the spherical approximation. We can use this approximation in humid environments, and for old desert dusts in which the aspect ratio is typically below two. Aerosols that are small compared to the incident wavelength present a Rayleigh-like scattering dependence, and the size cannot be determined using multistatic lidar techniques. We discuss the analysis of true extinction from Raman lidar measurements at several wavelengths for determining the size distribution of aerosols. The Angstrom ratio, which is the natural log of the extinction ratio divided by the natural log of the wavelength ratio, has been used in column-integrated measurements to classify aerosols. Lidar backscatter Angstrom ratio measurements have also been used to classify aerosols as a function of range. However, the use for aerosol size distribution has not been investigated in detail before this work. We find, from Raman lidar measurements, Mie models of extinction and backscatter Angstrom ratios, that small aerosols make a significant contribution to optical scattering, and find that size information can be extracted from the lidar data.

Physical Sciences Inc. is developing an advanced, compact LIDAR capable of continuous mapping of atmospheric extinction to provide environmental situational awareness for high energy laser weapon operations by the Navy. The LIDAR uses a MicroPulse LIDAR architecture and combines a solid state Nd:YLF laser operating at 1 micron with photon counting detectors and advanced aerosol retrieval algorithms. We report on the design of the engineering prototype and provide a summary of the system performance demonstrated during the Comprehensive Atmospheric Boundary Layer Extinction / Turbulence Refinement eXperiment conducted at the Shuttle Landing Facility at Kennedy Space Center in June, 2017.

A wide-angle CCD camera based bistatic lidar (CLidar) is used to monitor aerosol profiles in the atmosphere of The Bahamas. A 2-Watt CW laser beam ranging from ground to zenith is captured in a single image by a camera fitted with a fisheye lens which is placed at a different location from the laser. Scattering altitude is determined simply from the geometry of the CLidar in contrast to monostatic lidar which requires expensive electronics to measure the time of flight of the returned signal. Each image contains both molecular and aerosol single angle scattering. A cloud free image is used to normalize the signal intensity to a model of molecular scattering at a region free of aerosol layer. Then molecular portion is subtracted to retrieve aerosol side scattering. An aerosol phase function was assumed to convert side scatter to aerosol extinction. Corrections due to transmission effects are then iteratively calculated until convergence is reached. Aerosol extinction drops off sharply above 1 km indicating the planetary boundary level which agrees well with the relative humidity measurements obtained from the radiosonde data of Nassau airport observation. Additionally, aerosols originated from the smoke of a charcoal grill operating near experimental site were efficiently detected near ground levels. Aerosol extinction at 20 m above sea level is 0.085 km^-1 during grilling compared to 0.03 km^-1 during no grilling. Excellent altitude resolution of the CLidar at the ground levels allows its use for in-situ environmental characterization without the overlap effects faced when using traditional lidar.

LIDAR provides precise information on the objects surveyed by sequentially measuring with high accuracy. The result is a georeferenced point cloud. Every point can be described by its coordinates, attributes, and its accuracy. However, the raw point cloud is not the final product. In order to retrieve information from the point cloud additional processing is applied like classification, filtering, and modelling. LIDAR systems with focal plane arrays acquire hundreds or even thousands of range readings with a single laser pulse. This provides intermediate point clouds with a tremendous point density. However, these point clouds are frequently extremely noisy. First of all, due to the high sensitivity of the detector down to the single-photon level, the point clouds show a lot of “points in the air”. Secondly, the ranging in itself is prone to a significantly higher level of range noise compared to linear waveform LIDAR. In order to still retrieve useful information these point clouds have to be pre-processed in order to reduce noise significantly. While “points in the air” can be disposed off by applying spatial density analysis, reducing range noise can only be tackled by some sort of spatial averaging. We discuss the impact of pre-processing of raw point cloud from focal-plane LIDAR with respect to changes applied to the information content and in comparison with point clouds delivered by state-of-the-art linear waveform-processing LIDAR systems.

CZMIL is an airborne multi-sensor system that exploits the data fusion paradigm to generate automated and high- resolution 3D environmental maps of coastal zones. CZMIL is used to map the near-shore environment for engineering and nautical charting applications on a recurring basis under the U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program. We have developed a mathematical framework, based on the contributing individual systematic and environmental parameters, for the estimation of Total Propagated Uncertainties (TPU) associated with CZMIL bathymetric data. We developed the TPU model based on the General Law of the Propagation of Variances. TPU is a critical metadata that characterizes the quality of a hydrographic survey. If there are issues with data integrity, TPU can be used as a diagnostic tool to provide insight and identify the particular lidar sub-system or processing module that is responsible. Moreover, because the overall ranging accuracy for any specific lidar bathymetric system is a function of water column properties, we have developed a simplified water-depth uncertainty model based on the different water types that CZMIL typically surveys. This depth uncertainty model is utilized in the TPU model. In this paper we will discuss the methodology, and list and discuss the CZMIL parameters that contribute to the uncertainty. We will also present TPU estimates for sample CZMIL datasets and compare theoretical and actual uncertainties. These actual or empirical uncertainties are estimated by comparing CZMIL positional data with ground truth.

Automated semantic labeling of complex urban scenes in remotely sensed 2D and 3D data is one of the most challenging steps in producing realistic 3D scene models and maps. Recent large-scale public benchmark data sets and challenges for semantic labeling with 2D imagery have been instrumental in identifying state of the art methods and enabling new research. 3D data from lidar and multi-view stereo have also been shown to provide valuable additional information to enable improved semantic labeling accuracy. In this work, we describe the development of a new large-scale data set combining public lidar and multi-view satellite imagery with pixel-level truth for ground labels and instance-level truth for building labels. We demonstrate the use of this data set to evaluate methods for ground and building labeling tasks to establish performance expectations and identify areas for improvement. We also discuss initial steps toward further leveraging this data set to enable machine learning for more complex semantic and instance segmentation and 3D reconstruction tasks. All software developed to produce this public data set and to enable metric scoring are also released as open source code.

Methods for the creation of Textured Digital Surface Models (TDSM), which are a 3D representation of a terrain surface, are of increasing interest. This paper investigates the prospects for the generation of higher resolution TDSMs using texel images taken from a low cost unmanned aerial system (UAS). Coarse measurements for attitude and position are obtained from a low cost GPS/IMU fitted into the UAS. Using these coarse measurements and the data from the texel image, the error in the camera position and attitude is reduced which helps in producing an accurate TDSM. The main reason for using texel images is that these images contain both 2D image data and 3D lidar data. Despite having many texel images as input, the out- put TDSM reported previously only has approximately same resolution as the input texel image. In this pa- per, we propose a method to combine these low resolution texel images to produce a TDSM with high resolution texture using multi-frame Wiener filter super- resolution. The final image has the resolution at the sub-pixel level instead of pixel level and because of this, the TDSM looks visually better. The improvement pro- vided by implementing super-resolution on the texture is reported and the final registered TDSM results are shown.

NASA’s Ice, Cloud and Land Elevation (ICESat-2) satellite is planned for launch in 2018 with the goal of providing a global distribution of elevation measurements to support many Earth science applications. The primary science mission is focused on the Polar Regions and will provide data to help understand controlling mechanisms of polar ice sheet mass balance, and investigate ice-ocean-atmosphere exchanges of mass, energy and moisture as it relates to sea ice thickness. ICESat-2 will also allow for terrain and canopy height retrievals as it operates continually throughout its orbit. The satellite will utilize a laser altimeter that provides signal detection sensitivities on the photon-level. This instrumentation allows for lower power and weight requirements to support a high repetition rate, multiple-beam configuration for improved spatial coverage as compared to previous missions. In order to develop the geophysical data product algorithms in preparation for launch, simulated data sets have been produced based on the statistical representation of the expected system performance. These data allow for data product quality analysis over specific types of ecosystems. This is of particular interest for vegetated regions, where canopy cover characteristics will directly affect the ability to retrieve terrain heights. This paper will discuss the expected ICESat-2 land/vegetation data product quality a selected ecosystem.

Flight quality solid-state lasers require a unique and extensive set of testing and qualification processes, both at the system and component levels to insure the laser's promised performance. As important as the overall laser transmitter design is, the quality and performance of individual subassemblies, optics, and electro-optics dictate the final laser unit’s quality. The Global Ecosystem Dynamics Investigation (GEDI) laser transmitters employ all the usual components typical for a diode-pumped, solid-state laser, yet must each go through their own individual process of specification, modeling, performance demonstration, inspection, and destructive testing. These qualification processes as well as the test results for the laser crystals, laser diode arrays, electro-optics, and optics, will be reviewed as well as the relevant critical issues encountered, prior to their installation in the GEDI flight laser units.

The Global Ecosystems Dynamics Investigation (GEDI) Lidar Mission will employ three lasers systems internally developed, built, and tested by the NASA Goddard Space Flight Center Lasers and Electro-Optics Branch. Once installed on the Japanese Experiment Module (JEM) on the International Space Station (ISS), the lasers, each coupled with a Beam Dithering Unit (BDU) will produce three sets of staggered footprints on the Earth's surface to accurately measure global biomass. Each of the lasers is a heritage Nd:Yag solid state design required to put out Q-switched pulses at a rate of 242 Hz with a minimum 10 mJ per pulse at a 1064 nm wavelength. During the project, an engineering test unit (ETU) was also built and tested to pave the way for the laser systems to be used in space. We report on the technical and programmatic requirements that drove the design and development of the lasers. Also presented is an update of the performance of the engineering test unit qualification and life-testing along with the status of the space flight lasers.

Ultra-compact, nanosecond-class spaceflight-compatible UV lasers are finding increasing application in laser desorption, excitation, and ionization analytical applications on planetary missions, such as the detection and characterization of potential molecular biosignatures on Mars or icy moon surfaces. A short pulsed, solid state, UV laser is under development with selectable pulse energy capabilities for optimized sample ion production at a planetary surface.

Space laser systems are widely used in communication, altimeter and Doppler radar. UV laser, which possesses high spectral resolution and provides with the detection of the parallel polarized molecular (Rayleigh) and particle (Mie) backscattered signals has promising use in atmosphere detection and Doppler radar. No orbiting satellite carrying with 355nm laser has yet been launched owing to the laser induced damage of coatings. Coatings for spaceborne laser system are widely used in spacecraft with laser system to improve the transmittance of the optical system and to adjust the laser beams. An effective way to improve the lifetime of the coatings and the resistance to the environment is to increase laser induced damage threshold (LIDT). The subsurface damage (SSD) of the substrate is one of the major harmful factors in laser induced damage. In our study, 355nm high-reflection (HR) and anti-reflective (AR) coatings deposited by dual-ion beam sputtering (DIBS) were stable and showed lit