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This thesis is concerned with the use of difference-frequency mixing and parametric amplification processes in nonlinear crystals to generate high pulsed energies in the near-infrared for use in laser radar. The processes have been investigated both theoretically and experimentally. A complete theoretical treatment of second-order nonlinear interactions between plane waves has been developed. The treatment allows for any intensity of wave and any size of phase mismatch between the waves. It is the first such treatment to give rise to completely analytical results. An analysis of the phase mismatch between beams propagating in a non-collinear geometry in a second-order nonlinear process has been carried out. This analysis leads to the concept of tangential phase matching which results in an enhancement in the acceptance angle of such an interaction and is therefore a valuable technique for use with divergent beams. It has been demonstrated theoretically, for the first time, that in a difference-frequency mixing interaction the tangential phase-matching condition occurs when the angle between the most divergent input beam and the generated beam is equal to the walkoff angle, but in the opposite direction. Some experimental investigations of these interactions have been conducted using lithium niobate. A large enhancement in the conversion efficiency of a difference-frequency mixing experiment has been observed when the tangential phase-matching condition was used. The properties of a parametric amplifier have also been investigated. A gain of 30 was observed for small signals and it was found that the divergence of the amplified beam was not significantly altered by the amplification process. The application of the results established in this thesis will enable future workers to perform more accurate calculations on second-order nonlinear interactions and to achieve higher conversion efficiencies in mixing processes between divergent beams.

This research presents methods and results of characterizing and correcting PIN photodiode 3D flash LiDAR cameras, with the goal of significantly simplifying and improving the calibration system design. 3D flash LiDAR detectors use time to digital conversion (TDC) circuits to estimate the time of flight of a pulse when a detection threshold is met. As the underlying time to digital conversion (TDC) circuits require more space and power, these circuits will cause, in high bus loading events, electronic crosstalk. These events are more likely to occur in situations where many detectors simultaneously trigger, something that can occur when viewing a flat object head-on with uniform illumination, thus limiting these sensors to image a full frame due to this simultaneous ranging crosstalk noise (SRCN). Solutions were devised including using a windowed region of interest to mitigate additional noise by preventing triggering on all of the focal plane array (FPA) except the windowed region, and methods using a checkerboard pattern for imaging the full frame, including using a physical target downrange and a spatial light modulator.

Velocity measurement inside of a wind tunnel is an extremely useful quantitative data for a multitude of reasons. One major reason is that velocity has a mathematical relationship with dynamic pressure which in turn influences all the aerodynamic forces on the test model. Many devices and methods exist for measuring velocity inside wind tunnels. At the same time, Doppler wind lidar (light detection and ranging) has been used for decades to make air speed measurements outdoors at long ranges. Lidar has been proven effective for many applications, and it has the potential to solve many of the problems faced by current velocimetry techniques inside wind tunnels. Despite this, minimal research has been performed with Doppler wind lidars inside wind tunnels. While multiple commercial systems exist for making air speed measurements at longer ranges, there are currently no widely available commercial devices designed to work well inside wind tunnels. In this research, initial work is described for the design and development of a continuous wave (CW), coherent wind lidar system. The system is for use as an alternative non-intrusive velocimetry method inside wind tunnels relying on the Doppler effect. A scaled down wind lidar designed to operate at much shorter ranges than current commercial wind lidars can be simpler, less expensive, and require less power. A first iteration of the design was constructed for proof of concept testing with a small-scale wind tunnel at low speeds (7.5-9 m/s). Testing showed that the lidar system could take one-dimensional speed measurements of seeded flow that closely matched Pitot static tube data. When not adding tracer particles to the flow, the lidar return signal was not strong enough for the photodetector used to measure the beat frequency. This research is focused on the process for designing the Doppler wind lidar system, constructing the experimental setup, and studying methods for data analysis. Results of testing presented in the paper and lessons learned were used to create a second iteration of the wind lidar design that can be built for future testing. Not all data analysis methods and experiments described herein were successful, but this documentation will be helpful to future researchers for improving the design and continuing to make progress on a much needed device for wind tunnel velocimetry.

Lidar is an increasingly prevalent technology for depth sensing, with applications including scientific measurement and autonomous navigation systems. While conventional systems require hundreds or thousands of photon detections per pixel to form accurate depth and reflectivity images, recent results for single-photon lidar (SPL) systems using single-photon avalanche diode (SPAD) detectors have shown accurate images formed from as little as one photon detection per pixel, even when half of those detections are due to uninformative ambient light. The keys to such photon-efficient image formation are two-fold: (i) a precise model of the probability distribution of photon detection times, and (ii) prior beliefs about the structure of natural scenes. Reducing the number of photons needed for accurate image formation enables faster, farther, and safer acquisition. Still, such photon-efficient systems are often limited to laboratory conditions more favorable than the real-world settings in which they would be deployed. This thesis focuses on expanding the photon detection time models to address challenging imaging scenarios and the effects of non-ideal acquisition equipment. The processing derived from these enhanced models, sometimes modified jointly with the acquisition hardware, surpasses the performance of state-of-the-art photon counting systems. We first address the problem of high levels of ambient light, which causes traditional depth and reflectivity estimators to fail. We achieve robustness to strong ambient light through a rigorously derived window-based censoring method that separates signal and background light detections. Spatial correlations both within and between depth and reflectivity images are encoded in superpixel constructions, which fill in holes caused by the censoring. Accurate depth and reflectivity images can then be formed with an average of 2 signal photons and 50 background photons per pixel, outperforming methods previously demonstrated at a signal-to-background ratio of 1. We next approach the problem of coarse temporal resolution for photon detection time measurements, which limits the precision of depth estimates. To achieve sub-bin depth precision, we propose a subtractively-dithered lidar implementation, which uses changing synchronization delays to shift the time-quantization bin edges. We examine the generic noise model resulting from dithering Gaussian-distributed signals and introduce a generalized Gaussian approximation to the noise distribution and simple order statistics-based depth estimators that take advantage of this model. Additional analysis of the generalized Gaussian approximation yields rules of thumb for determining when and how to apply dither to quantized measurements. We implement a dithered SPL system and propose a modification for non-Gaussian pulse shapes that outperforms the Gaussian assumption in practical experiments. The resulting dithered-lidar architecture could be used to design SPAD array detectors that can form precise depth estimates despite relaxed temporal quantization constraints. Finally, SPAD dead time effects have been considered a major limitation for fast data acquisition in SPL, since a commonly adopted approach for dead time mitigation is to operate in the low-flux regime where dead time effects can be ignored. We show that the empirical distribution of detection times converges to the stationary distribution of a Markov chain and demonstrate improvements in depth estimation and histogram correction using our Markov chain model. An example simulation shows that correctly compensating for dead times in a high-flux measurement can yield a 20-times speed up of data acquisition. The resulting accuracy at high photon flux could enable real-time applications such as autonomous navigation.

Imaging through obscurants is a critical issue for lidars looking through clouds, or human tissue. Traditionally Spatial heterodyne imaging has been performed with a low-bandwidth laser source that exhibits good coherence length characteristics. One of the drawbacks of using a low-bandwidth source with long coherence length is that signal return from all objects within the coherence length of the source mix equally well on the camera imaging the system. Broadening the bandwidth of the source shortens the coherence length of the system. This thesis intends to show that through careful system design, spatial heterodyne imaging can be performed in the presence of a broadband source, allowing significantly improved imaging in the presence of obscurants such as clouds or human tissue. The method used will be phase modulating the source with a pseudo-random bit sequence and matching the optical path lengths of the signal and local oscillator branches of the system. By matching the path lengths for a pseudo-random coded source we can image objects at specific distances related to the modulation speed and code length, while isolating the power of signal return from objects at other distances as a factor of the autocorrelation coefficient of the code.

The use of a saturated Semiconductor Optical Amplifier (SOA) as both a phase modulator and an amplifier for long range laser radar applications is explored. As will be discussed, this concept could reduce the hardware necessary to transmit high bandwidth pulses and allow for the transmission of shorter pulses that are less sensitive to the detrimental effects of target motion. After reviewing the concepts governing ranging, vibrometry, and synthetic aperture ladar, the nature of the phase and amplitude modulation from saturating an amplifier with a high peak power Gaussian pulse is explored. The key SOA parameters affecting the modulation of the output pulse are addressed and optimized, and their impact on the ideal pulse response of a laser radar system is explored. Proof of concept laboratory demonstrations using phase modulated pulses to interrogate stationary, vibrating, and translating targets are also presented. The concept of using a saturated SOA to enable short-pulse synthetic aperture ladar and vibrometry is also explored. This research will show that the range resolution of a ladar system can be optimized by saturating a SOA with a carrier lifetime that is one half the FWHM Gaussian input pulse duration, yielding a substantial improvement in range resolution that is highly insensitive to variations in the input pulse duration and energy.

In stretch processing (SP) both the local oscillator (LO) and the transmitted signal are linearly frequency modulated (LFM). A heterodyne detection process is performed using the LO and the received echo signal, which create a detected signal at a single difference-frequency. The frequency is proportional to the distance the received echo signal travels relative to the LO signal, and the range resolution is inversely proportional to the bandwidth making large bandwidth LFM chirps favorable. However, it is difficult to maintain linearity over a lager bandwidth LFM chirp. On the other hand small bandwidth LFM chirps can be easily produced, so the idea of segmenting the transmitted pulse into multiple small non-overlapping frequency LFM chirps was conceived. The extended frequency bandwidth is recovered in post processing. This technique is called multi-frequency stretch processing (MFSP). The procedure outlined is a practical method to achieve greater range resolution using less expensive technology. Another advantage of this technique is the similar modulation noise on each LFM chirp. The multiple signals are processed using an algorithm developed for extracting the additional bandwidth information. The range resolution is related to the time span and bandwidth of the LFM pulses. For n transmitted LFM chirped signals the range resolution is nearly n times longer. Moreover the required detection bandwidth of the echo signal is lower than for other LFM processing systems without a chirped LO signal.

Sparse frequency, linearly frequency modulated laser radar (ladar) signals achieve improved range resolution comparable to a larger signal bandwidth. From basic radar/ladar principles it is known that the bandwidth of a signal is inversely proportional to range resolution. Hence, the effective bandwidth of a ladar signal using sparse frequency techniques is larger than the bandwidth of each modulated laser frequency. Previous experiments have validated range resolution and peak to sidelobe ratio derived from models utilizing two segmented bandwidths. This thesis discusses the modeling with three segmented bandwidths. The model is verified against an experimental setup using three frequency offset lasers.The two segmented bandwidth, sparse frequency ladar signal is reexamined to include Doppler effects. The new modeling utilizes a coherent on receive setup allowing for phase information to be processed from the signal. The extracted phase information can be used to determine characteristics about a target, namely its speed and direction with respect to the receiver. This modeling was experimentally verified for cases where the target was next to the receiver, at a distance (simulated through a fiber delay line), and for multiple targets. As a final check of the modeling, the velocity determined from the phase information was compared against the velocity readout of a stage with a built in optical encoder.

As more data sources containing 3-D information are becoming available, an increased interest in 3-D imaging has emerged. Among these is the 3-D reconstruction of buildings and other man-made structures. A necessary preprocessing step is the detection and isolation of individual buildings that subsequently can be reconstructed in 3-D using various methodologies. Applications for both building detection and reconstruction have commercial use for urban planning, network planning for mobile communication (cell phone tower placement), spatial analysis of air pollution and noise nuisances, microclimate investigations, geographical information systems, security services and change detection from areas affected by natural disasters. Building detection and reconstruction are also used in the military for automatic target recognition and in entertainment for virtual tourism. Previously proposed building detection and reconstruction algorithms solely utilized aerial imagery. With the advent of Light Detection and Ranging (LiDAR) systems providing elevation data, current algorithms explore using captured LiDAR data as an additional feasible source of information. Additional sources of information can lead to automating techniques (alleviating their need for manual user intervention) as well as increasing their capabilities and accuracy. Several building detection approaches surveyed in the open literature have fundamental weaknesses that hinder their use; such as requiring multiple data sets from different sensors, mandating certain operations to be carried out manually, and limited functionality to only being able to detect certain types of buildings. In this work, a building detection system is proposed and implemented which strives to overcome the limitations seen in existing techniques. The developed framework is flexible in that it can perform building detection from just LiDAR data (first or last return), or just nadir, color aerial imagery. If data from both LiDAR and aerial imagery are available, then the algorithm will use them both for improved accuracy. Additionally, the proposed approach does not employ severely limiting assumptions thus enabling the end user to apply the approach to a wider variety of different building types. The proposed approach is extensively tested using real data sets and it is also compared with other existing techniques. Experimental results are presented.

This thesis explores a relatively new Solid Silver Thin Film Source technology, for the implementation of a novel High Precision Laser Radar Tracking device. The process which consists of a Ag+-Na+ ion exchange, is designed in two steps. It utilizes an initial electric field-aided ion exchange step for a predeposition, and a subsequent second diffusion step to force the profile latitude necessary for optimization of the device. While the entire project of implementing this device, consists of analyzing, processing, polishing and testing, this thesis covers only the process aspect in detail. The success achieved by obtaining the required Power Coupling Ratio curve on a Simple Coupler, demonstrates a novel integrated optic multimode feed for a Monopulse LIDAR application.