This PDF file contains the front matter associated with SPIE Proceedings Volume 11410, including the Title Page, Copyright information, and Table of Contents.

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. However, not every small flying object is a potential threat and therefore the object not only has to be detected, but classified or identified. Typical 360° scanning LiDAR sensors, like those developed for automotive applications, can be deployed for the detection and tracking of small objects in ranges up to 50 m. Unfortunately, the verification and classification of the detected objects is not possible in most cases, due to the low resolution of that kind of sensor. In visual images a differentiation of flying objects seems more practical. In this paper, we present a method for the distinction between UAVs and birds in multi-sensor data (LiDAR point clouds and visual images). The flying objects are initially detected and tracked in LiDAR data. After detection, a grayscale camera is automatically pointed onto the object and an image is recorded. The differentiation between UAV and bird is then realized by a convolutional neural network (CNN). In addition, we investigate the potential of this approach for a more detailed classification of the type of UAV. The paper shows first results of this multi-sensor classification approach. The high number of training data for the CNN as well as the test data of the experiments were recorded at a field trial of the NATO group SET-260 ("Assessment of EO/IR Technologies for Detection of Small UAVs in an Urban Environment").

Micro unmanned aerial vehicles (MUAV) have become increasingly popular during the last decade due to their access to a wide consumer market. With the increasing number of MUAV, the unintended and intended misuse areas has risen as a potentially increasing risk. To counter this threat, surveillance systems are under development which will monitor the MUAV flight behavior. In this context, the reliable tracking and prediction of the MUAV flight behavior is crucial to increase the performance of countermeasures. In this paper, we discuss electro-optical computational imaging methods with a focus on the ability to perform a tracking and prediction of the three dimensional (3D) flight path. In first experimental investigation, we recorded and analyzed image sequences of a MUAV quad-copter flying at low altitude in laboratory and in outdoor scenarios. Our results show, that we are able to track the three dimensional flight path with high accuracy and we are able to give a reliable prediction of the MUAV flight behavior within the near future.

Atmospheric optical turbulence can be characterized as refractive index variations along a beam's propagation path due to local fluctuations in temperature and humidity. Turbulence randomly perturbs the wavefront of a beam traveling through the medium, leading to effects such as scintillation and beam wandering. Wave optics simulations use phase screens and Fourier techniques to accurately model phase change of light sources as they travel through turbulence. Georgia Tech Research Institute has enhanced the open-source wave optics toolbox known as WavePy to accurately simulate the propagation of a laser beam over a path length of time- evolving horizontal turbulence. The simulation tool incorporates an optimization routine designed to accept scenario parameters and return receiver and source plane sampling parameters that ensure accuracy and fidelity of the simulation output. This simulation tool is designed to minimize the potential for common faults of wave optics simulations, including: phase-wrapping of the atmospheric phase screens over time, energy loss of the beam over the propagation path, and aliasing of scintillation effects at the receiver plane. This simulator has applications towards informing the design of detectors that can accommodate the changing angle of divergence of the beam as it approaches the detector, which is an important consideration for systems such as laser beam rider missile guidance systems. Initial results towards modeling the effects of varying beam parameters and simulation conditions are presented and analyzed.

The F-35 Lightning II has a powerful combat laser designator operating at a wavelength and energy levels that are damaging to the human eye at a pulse level. Due to the faceted design of the Electro Optical Targeting System housing, unwanted Stray Laser Energy beams are emitted in uncontrolled directions. These beams are powerful enough to damage the human eye. Care must therefore be taken to ensure that observers on the ground are not unintentionally blinded. Using a general procedure where the hazard distance is determined by the length of the strongest Stray Laser Energy beam in any direction impedes the ability of the Royal Norwegian Air Force to train in Norway due to the size of the firing ranges and the limits to the maneuvering envelope. We have developed a Monte Carlo based model to determine the hazard "footprint" on the ground for typical flight patterns. The model incorporates several stochastic variables to catch the variations of an execution. The model also incorporates terrain data to evaluate if a beam will hit the actual terrain around a specified target. By running enough instances of the model, it is possible to generate an estimate for the probability of being hit by a beam for ground observers. Analysis has been performed for the unaided eye, binoculars of size 7x50mm and binoculars of size 20x120mm. By evaluating the risk level in accordance with guidelines provided by the The Norwegian Radiation and Nuclear Safety Authority, we have expanded the possibility for training using the combat laser in Norway.

The atmospheric boundary layer is typically characterized by a higher water vapor content and higher temperature than the free troposphere above it. Its height increases as the size of convection cells grow during the morning due to surface heating, stabilizes during the day, and it collapses as the energy input decreases in the evening. The marine boundary layer emphasizes these aspects. The large temperature gradients, humidity gradients and shear at the top of the boundary layer impact several processes, such as changes in both propagation properties as a function of wavelength and aerosol size distributions. We use Raman lidar to measure the gradients, and investigate several data inversion techniques to determine the best approach to obtain a high accuracy, for high SNR profiles of these gradients. Methods include anisotropic averaging between height and range, and averaging only to the level required for a specific target SNR. Examples that benefit from different time and range averaging will be given. The methods for gradient calculations and the interaction with pre- or post-averaging are also investigated. We model the impact of gradient-profile measurement from errors in the refraction of radar beams as a measure of quality requirements.

Atmospheric methane trends over the last few years have been increasing at a rate of 7-12 parts per billion (ppb) per year after brief a pause in the first decade of this century. The reasons for the pause and subsequent increase remains unclear. Thus, there is a critical need for additional, precise and accurate methane observations to understand the natural and anthropogenic processes that drive the trends in atmospheric methane and to constrain its sources, and sinks. At NASA Goddard Space Flight Center (GSFC), in collaboration with Freedom Photonics Inc., we have been developing a lidar to measure atmospheric methane using Integrated Path Differential Absorption (IPDA) from an airborne platform as a precursor to a future space mission. In this paper we present the design of a laser transmitter operating at ~1651 nm based on a newly developed Distributed Bragg Grating (DBR) seed laser and an Optical parametric oscillator (OPO). The DBR is rapidly step-tuned over the methane absorption at several discrete wavelengths. This multi-wavelength approach enables us to sample the entire methane lineshape and reduce systematic errors.

In this paper, we describe a method for automatic extrinsic self-calibration of an operational mobile LiDAR sensing system (MLS), that is additionally equipped with a POS position and orientation subsystem (e.g., GNSS/IMU, odometry). While commercial mobile mapping systems or civil LiDAR-equipped cars can be calibrated on a regular basis using a dedicated calibration setup, we aim at a method for automatic in-field (re-)calibration of such sensor systems, which is even suitable for future military combat vehicles. Part of the intended use of a mobile LiDAR or laser scanning system is 3D mapping of the terrain by POS-based direct georeferencing of the range measurements, resulting in 3D point clouds of the terrain. The basic concept of our calibration approach is to minimize the average scatter of the 3D points, assuming a certain occurrence of smooth surfaces in the scene which are scanned multiple times. The point scatter is measured by local principal component analysis (PCA). Parameters describing the sensor installation are adjusted to reach a minimal value of the PCA's average smallest eigenvalue. While sensor displacements (lever arms) are still difficult to correct in this way, our approach succeeds in eliminating misalignments of the 3D sensors (boresight alignment). The focus of this paper is on quantifying the influence of driving maneuvers and, particularly, scene characteristics on the calibration method and its results. One finding is that a curvy driving style in an urban environment provides the best conditions for the calibration of the MLS system, but other structured environments may still be acceptable.

In the past decades significant improvement of the performance of III-V Geiger-mode APDs (GmAPD) has been achieved in Near Infrared (NIR) and Short Wavelength Infrared (SWIR) wavelengths. In order to meet the challenge to GmAPDs in visible wavelength for some special military and space applications, Acqubit developed a GaAs-based InGaP APD with a substrate removal structure. With a proprietary mesa passivation process, very low dark current, ~0.5 nA in a 50 um diameter device or 25 uA/cm2, was demonstrated just before breakdown at room temperature. Sufficient device thickness ensured an external quantum efficiency (QE) about 50% at 532 nm without a bottom reflector. The combination of mesa structure and substrate removal process greatly suppressed the array pixel crosstalk and afterpulsing while maintaining a high QE and photon detection efficiency (PDE). In this paper we will report the progress of the GmAPD detectors and arrays with low DCR and high PDE at 532 µm.

Optically transparent antennas are an enabling technology for creating single aperture radio frequency (RF)/Electro- Optical (EO)/Infra-red (IR) sensing and communication systems. Multi-sensor information processing, simplified alignment, resiliency to jamming, and lower size, weight, and power (SWaP) are all among the potential benefits realized by a multi-modal aperture. However, the ability to have highly transmissive optical imaging, LIDAR, and/or communication systems at the same time in the same physical footprint as low loss antenna systems for RADARs, communication, and/or radiometers results in a complex set of competing requirements and engineering tradeoffs. Of course, the exact requirements will depend on the nature of the individual systems which are being utilized in the aperture. For instance, a LIDAR-RADAR common aperture will have very different requirements than a short-wave infra-red (SWIR) imaging system with a microwave communication system. This paper will address some of these competing requirements and begin to investigate some of the limiting factors in operating these systems. For example, micro-meshed conductors have demonstrated the potential as an optically transparent conductor that is well suited to both RF and EO/IR performance. However, the RF power handling capacity of the micro mesh may limit the maximum output power of the RF system. At the same time, it has been shown that the micro mesh is highly transmissive, but the effects of the micro mesh on the point spread system of the optical system have not been characterized. These considerations will be discussed in the context of a LIDAR-RADAR common aperture for autonomous vehicle applications.

In a wide variety of applications, including free-space communications, target illumination, and radar (laser, microwave, millimeter wave, etc.), an electromagnetic pulse is collected by a receiver and converted to an electronic signal. This electronic pulse is then amplified before it is processed into digital data, tracking information, or range and velocity values. In this paper it is shown that an optimum amplification half-power bandwidth—in terms of maximum signal-to-noise ratio (SNR)—can be determined, based almost exclusively on the full width at half maximum (FWHM) of the pulse and the roll-off rate of the amplifier at frequencies above the high-frequency cutoff. The shape of the pulse and the specific amplification filter (e.g. Butterworth, Chebyshev, Elliptic, etc.) has little effect on the optimum bandwidth. For example, if the amplifier includes a low-pass first-order Butterworth filter whose half-power frequency is Δν, a pulse whose FWHM is Δt will be amplified at the maximum possible SNR if Δν = 0.146/Δt. This assumes that any noise in the system is essentially white, in that the total noise is proportional to the square root of the amplification bandwidth. It should be noted, and is discussed in this paper, that the maximum SNR may not lead to the ideal bandwidth, since it with distort the shape of the input pulse. This distortion alters the shape of the pulse and may affect the calculation of the pulse centroid, which is particularly important in range and velocity calculations. This may lead to an increase in the optimum bandwidth.

A pulse driver based on inductive storage and discharge is developed for driving short 1-5ns current pulses through laser diodes. This driver overcomes the laser diode impedance matching challenge by coil discharge through the laser diode which produces a high compliance 100V open circuit pulse current source. The pulse driver is demonstrated in a laser ranging experiment which employs linear PD amplifier and time gated receiver. The aim of this laser ranging system is immunity to optical interference and capability of ranging through reflecting objects that are not of interest, like water surface or vegetation.

We show a fast settling digital laser controller with pulse width modulation (PWM) current drive output. By using self learning feed forward and delayed proportional integral and differential (PID) feedback control, the drive current settles faster than the digital control loop execution time. The feed forward model is updated based on parameters learned from stable feedback operation. Pulse modulation settling time and stable high efficient CW operation is made possible with this approach. The laser diode controller is well suited for pulse modulation or electrical gating of high power laser diodes due to its high efficiency and over dampened settling.

Publisher’s Note: This conference presentation, originally published on 27 April 2020, was withdrawn on 8 June 2020 per author request.

Systems of silicon-germanium atoms (Si-Ge) are well-known as semiconductors. Since the electrons of a Si-Ge system are bounded, external quantum effects are negligible. We hold the volume constant while varying all other parameters, such as pressure, temperature, germanium chemical potential (or germanium concentration), energy, mole number and atomic bond structure, resulting in an observation of hysteresis in the system.

Total Propagated Uncertainty (TPU) has been a very important topic of research and developments in the last five years in the bathymetric lidar community. To date, two models coexist to estimate the TPU of a bathymetric lidar system. One would rely on an analytical approach based on the General Law Of Propagation Of Variance (GLOPOV) whereas the other relies on a probabilistic and modeling approach based on water surface simulation, Monte Carlo and Ray-tracing principles. We propose a new hybrid method that is based on the GLOPOV and the Law of Large Number (LLN). This new approach includes several innovative mathematical concepts and computational tools that help to overcome known challenges and limitations whilst improving the computation speed. For instance, an analytical TPU estimation relies on the Jacobian and Covariance matrices associated to the LiDAR system. The estimation the Jacobian matrix, i.e. the partial derivatives of the LiDAR equation’s vector function, remains a difficult task. Therefore, we’ve developed an equation parser and a code generator tool that evaluate the partial derivatives of any equation system and produce the GPU code for its evaluation. The Covariance matrix also has its own challenges and we propose new approaches to estimate some of the sigma values. The probabilistic model based on Monte Carlo simulation and ray tracing is inherently intensive in terms of computation and therefore slow. The use of the LLN offers a scalable and robust approach to estimate parameters and coefficients of the model. Finally, we will present an attempt to adapt the Quality Factor introduce by Lurton and Augustin in 2009 for the Multibeam echosounder systems. This factor has the potential to deliver an objective way to assess the bathymetric performance of any Airborne Bathymetric Lidar based on waveform analysis.

We report on a fully integrated, light-weight, and compact airborne laser scanner system for combined hydrographic and topographic surveying. To handle target situations with complex echo signals the entire digitized echo waveforms can be stored on the removable data storage card for subsequent full waveform analysis. Storing the entire waveform allows for pre-detection averaging, which increases SNR (Signal to Noise Ratio) and thus performance. Waveform averaging can also be applied onboard in order to apply signal detection and online waveform processing with averaged waveforms. The user can choose any combination of online waveform processing, offline single waveform processing, or offline waveform processing with stacked waveforms. We discuss the performance gain that can be achieved by waveform stacking and by different methods of waveform processing and waveform analysis using a typical topo-bathymetric dataset.

We report a high-energy, high-average power burst-mode picosecond laser system, which is designed for space debris laser ranging. Pulses from a Nd : YVO₄ mode-locked oscillator are first stretched by a piece of volume Bragg gratings (VBG) and then pass through an improved Michelson interferometer splitting system to obtain burst-mode pulses, which the relative amplitude and time-delay interval of each 4-pulse in bursts can be adjusted and controlled. A regenerative amplifier (RA), as a pre-amplifier, is adopted to decrease the repetition frequency of the seed beam from 80MHz to 1 KHz and raises the energy to millijoule-level. In order to reduce the performance requirement of the damage threshold of subsequent optical components and maximize the extraction of pulse energy, the Gaussian output beam of the RA is converted into a ring shaped pattern beam using an aspheric lenses reshaping system with the conversion efficiency of 93%. After a two-stage master oscillator power amplifier with 4f imaging systems, the pulse envelope energy is up to 100 mJ with the pulse duration of ~100 ps. To obtain high power green light, we compared the conversion efficiency of three crystals. When the fundamental frequency power is 80W, the second harmonic conversion efficiency of the first crystal (LBO, 6×6×10, Θ=90°, Φ=11.4°) is only about 50%, as well as the second (GTR-KTP, 7×7×7, θ=90°, Φ=23.5‡). But the conversion efficiency of the last crystal (LBO, 6×6×15, θ=90°, Φ=0°), reaches 68% and the output power of 532 nm as high as 50 W is obtained.