This PDF file contains the front matter associated with SPIE Proceedings Volume 11744 including the Title Page, Copyright information, and Table of Contents.

Light Detection and Ranging (LIDAR) is a popular sensing technique to measure static and dynamic objects with applications in many areas of defense technology including robotics, aircraft navigation and guidance systems, autonomous vehicles and aircraft landing systems, as well as tracking and measuring attitude of hypersonic objects. Despite widespread use of LIDAR to map out objects and environments, there remains a need for advanced analytic techniques to recover quantitative information about objects from LIDAR data, for example, the position and trajectory of a foreign object. One major class of LIDAR systems are those that produce so-called point-cloud data, which is a threedimensional sampling of a scene. Technical demands for extraction of geometric parameters from point-cloud spatial models are increasing as 3D LIDAR sensors and their application technology is continuously developed and popularized. While classical techniques for feature extraction and estimation exist, these existing techniques are currently inadequate to recover geometric parameters with desired accuracy for precision applications. To address this challenge, we developed an algorithm based on principal component analysis (PCA) to extract precise geometric parameters from LIDAR point-cloud data of objects including pitch, yaw, roll and xyz-position, as well as the rates of change of these parameters. We present the basis of this algorithm, as well as initial results using point cloud data of a rotating cylindrical object. The results suggest that PCA-based analysis could provide a robust and high precision approach for recovering object position and orientation, particularly when combined with other analytical approaches such as machine learning.

LIDAR-based measurement systems can overcome several limitations in comparable technologies for the measurement and mapping of 3D static and dynamic objects in any given reference frame. As a result, they present distinct advantages for the determination of target velocity, acceleration, roll, pitch, yaw and position from long distances. Continuous, precise sensing and monitoring of remote targets has applications in various areas including military and commercial systems from ground, air or space. In this manuscript, we present the use of Maximum-Likelihood Estimation (MLE) methods for the extraction of precise object orientation and position information from a “waveform-sensing” LIDAR detector, where the finely-sampled (> GHz) temporal waveform of the signal generated by the diffuse-reflected laser pulse (i.e., laser pulse reflected off of the object and returned to collection optics) is used. In this method, multiple waveforms generated by the return pulse from various detectors stationed at optimized specific positions are collected. The time-of-flight (TOF), shape and the duration of waveforms indicate the radial extent of the object and distance to the receiver. Position and orientation are then extracted from the waveforms using MLE. First, we describe the forward-model simulation tool to generate LIDAR waveform data for an arbitrary object position and orientation. Next, we present a brief introduction into MLE followed by the application of this method to the extraction of position and orientation parameters from the simulated LIDAR data. Finally, results are presented to demonstrate the accuracy of the proposed method in recovering the input object orientation and position under presence of noise.

A bathymetric LiDAR system’s emitted laser pulse is affected by many system specific and environmental variables, including sea water scattering and absorption, seafloor reflectance and rugosity, in-air attenuation, electronic bandwidth and noise, among others. These factors influence the captured, digitized waveform which can be used to estimate seafloor depth and sea water properties. Understanding how these parameters influence bathymetric LiDAR waveforms and extracting estimates of these parameters is important in developing more accurate analysis techniques as well as creating data products that are associated with georectified coordinates. However, estimating more than ten parameters from a collection of waveforms that may or may not have correlated parameters is challenging. This paper details a post-processing technique used to estimate bathymetric environmental parameters through robust simulation of airborne LiDAR data that models laser beam propagation in a specific bathymetric environment. To create an initial waveform, the simulator is seeded with known parameters and with reasonable estimates for unknown parameters. Then, using optimization algorithms, the unknown parameters are iteratively adjusted, creating a waveform that minimizes error between it and an associated truth waveform. By estimating these unknown values for many waveforms within a geographic area, the distributions of the environmental factors can be characterized for future analysis.

This paper presents the expansion of dark-frame non-uniformity correction (DFNUC) techniques to include compensation for thermal drift in a 128×128 PIN diode 3D flash LiDAR camera. Flash LiDAR cameras are operated in various climates, which makes thermal compensation necessary in the dark NUC algorithm. The thermal excitation of electrons has a significant effect on the dark current in an InGaAs PIN photodetector and on the CMOS readout circuitry, thus impacting the output image. This is a well-known phenomenon in imaging sensors and various algorithms have been established to address thermal drift. This paper adapts a linear model for dark signal calibration used in infrared cameras for the calibration of a PIN diode flash LiDAR camera in both intensity and range return. The experimental process involves collecting dark frames in increments of the internal camera temperature from 22°C to 36°C using thermoelectric (TE) cooling modules. A linear trendline is developed for each individual pixel based on the average frame return, which suppresses the random temporal noise and isolates the dark signal return. The trendline helps form a model for the dark frame offset as a function of temperature, which is used for the dark-frame NUC process. The dark-frame NUC with thermal drift compensation is then evaluated by correcting dark frames at various operating temperatures. Finally, illuminated scenes captured by the camera with a 5.91ns, 842.4μJ pulsed laser at 5Hz are corrected at multiple operation temperatures to show the effectiveness of the dark non-uniformity correction algorithm.

We have successfully tested 290 μm diameter, 2.4 micron wavelength, Extended InGaAs photodiodes coupled with single mode fiber using 50 MeV Protons at both dry ice temperature (-75 °C) and room temperature (20 °C). The devices were reverse biased at 100 mV during the radiation run and their leakage current was continuously monitored insitu during the exposure. These devices find multiple applications in space for spectroscopy and sensing, inter-satellite optical communication links, rapid Doppler shift LIDAR, as well as inter-planetary and Earth-to-Moon communication links. Several photodiodes were tested using 50 MeV Protons with an average flux level of 2.11 × 10⁷ protons/cm² /s, for a total fluence of 1.0 × 10¹¹ protons/cm² and total dose of 20 krad (water). Pre- and post-radiation results were also measured for leakage current vs. voltage, responsivity (quantum efficiency), and bandwidth of the Extended InGaAs photodiodes. All devices were found to be fully functional at normal operating conditions and at both dry ice and room temperature.

Fibertek is under contract with Nasa Langley for the development of a laser transmitter for water vapor differential absorption lidar (DIAL) measurements. Water vapor plays a central role in feedback mechanisms linking components and processes in the Earth’s atmosphere. Studying atmospheric water vapor content is important for understanding global energy transport and climate change. The driving design parameter for the water vapor DIAL application is a narrow single frequency linewidth with wavelength tunability that is coincident with a water vapor absorption line. Fibertek has developed a frequency doubled seeded single frequency resonantly pumped ErYAG laser system that can probe water vapor lines in the 822-823nm band. As an added benefit, the laser fundamental wavelength at 1645nm allows for probing atmospheric methane, which also plays an important role in climate change research. The laser emits 3mJ at 1645nm and 3mJ at 822nm at 1kHz with beam quality on the order of M²=1.6. Fibertek has packaged the ErYAG laser in an environmentally hardened housing for an airborne DIAL application. This paper will present current results of the ErYAG laser work, progress in increasing the output power, efficiency, and reliability of the laser to meet requirements for a follow-on space qualifiable laser and plans for environmental testing the system.

Fibertek, Inc designed, built, and tested an ultra-compact, lightweight flash lidar laser transmitter for NASA's entry, descent, and landing applications. The laser transmitter can be used in various commercial applications that benefit from SWaP improvements. The laser transmitter has a volume of .5 Liters, weighs .810 kilograms, and has a power draw less than 20W. The system produces an output pulse energy >10mJ, a pulse-width of about 5ns at a pulse repetition frequency of 5-30 Hz, and a beam quality of M2< 2. The use of additive manufacturing in the design of the space qualifiable laser is a key innovation that allowed us to reduce the size and weight of the laser transmitter. Fibertek, in partnership with researches at the Pennsylvania State University Center for Innovative Materials Processing, developed state-of-the-art additive methods to manufacture our topology optimized bench and covers. The laser transmitter combines our ultra-compact resonator and electronics into a single deliverable TRL-5 Package. We achieved a 5x reduction in volume from previous generation Fibertek flash lidar transmitters with a weight under a kilogram. Another innovation is the development of an athermal integrating-box pump head design. The pump head design allows the laser transmitter to operate over a wide range of temperatures with purely conductive cooling. We tested a temperature range of 15C to 50C without significant change in performance. The athermal design allows the laser transmitter to perform in a wide range of environments.

A range-compensating lens (RCL) design used in the return channel for active optical sensors, e.g., range-finders and LiDARs, has been developed by Mudge [Appl. Opt., 58(28), 7921-7928, (2019)] and detailed using raytrace methods by Phenis et al. [Proc. of SPIE, 11125(111250J), (2019)]. The motivation of the lens is to reduce the return signal with targets (objects) relatively near and boost the signal at far range targets by combining lens elements in parallel rather than in series. Using the techniques provided, a designer can develop a lens requiring a detector with less dynamic range and/or extend the far range limit while maintaining the minimum target distance. We provide a design of a two-element RCL, implementation, and a comparison with experimental results. With this foundational step, further flatting of the return signal curve as a function of range can now be done utilizing a three- or multi-element RCL design.

Light Detection and Ranging (LiDAR) is a form of remote sensing that utilizes laser scanners to produce a 3D point cloud of an environment by recording the number of laser pulse returns and measuring the backscattered energy as a function of time. LiDAR transect data were collected over the Monterey Peninsula and the Point Lobos Reserve. An experiment was conducted in the creation of a transect, a very high point density profile, by restricting the scan mirror with the initial goal of better understanding foliage penetration by LiDAR. Because of the high point density of the transect, the data were binned to create synthetic waveforms and to help reduce redundant points. However, the binning introduces sharpness in the data that distorts the typical wave shape in the synthetic transforms. A Bayesian Markov random field model captures the structure in the dataset and helps to offset the sharpness introduced during the binning. After fitting a Markov random field model using Markov chain Monte Carlo, classification methods were applied to distinguish objects in the landscape. These techniques should extend to true waveform data.

In this paper, we report the results of investigations on the drone ballistic carriers being developed by our research team and we address specifically the concept of compact laser altimeter dedicated to the ballistic carriers. One of the main challenges facing the implementation of the mortar launched altimeter is to ensure its reliable operation after extremely high launch shock accelerations. This requirement determines the optical concept and materials selection and optimization. Recent mortar gun tests demonstrated that the optical and electronic sub-systems of the first altimeter prototype can withstand launch accelerations of at least 5000g.

At the beginning of 2018 a landslide was triggered in the Reina del Cisne (Cuenca - Ecuador) following the cut that was applied to a hillside for the construction of a small access road. From May to June 2018, the period of analysis of this work, the landslide has caused structural damage to several homes, deterioration of a field and the total collapse of the road that caused it. Field visits and the comparison of point clouds obtained with a terrestrial laser scanner (LiDAR) in the months of May and June 2018 have highlighted the high activity of this landslide. This article introduces the process that was performed to compare the point clouds obtained. The results show the feasibility of using terrestrial laser scanner (LiDAR) for early detection of landslides.