In this study, a methodology is developed to enhance additively manufactured surfaces for use as 3D printed optical mirrors. Utilizing vacuum deposition and pulse-reverse-current electroplating, a grain size smaller than one-tenth the wavelength can be achieved for mmWave, IR, visible, and UV. A shared-aperture, multispectral imaging system consisting of 3D printed optical mirrors is proposed for military and security applications. Being centered and aligned along the same optical axis provides the advantage of exploiting multi-beam target illumination while maintaining a consistent reference for image processing. With the use of additive manufacturing and surface treatment techniques, complex designs can be achieved to develop passive apertures with predictable resolution and dimensional tolerance. Optimization and integration of this surface methodology would enable the ability to additively manufacture multispectral optical systems.
Several methods of additive manufacturing are being investigated for construction of microwave and millimeter-wave antennas and electromagnetic structures. These include methods such as stereo lithography and fused deposition modeling. The impacts of surface roughness, performance of dielectric lenses, and 3D printed aperture antennas are studied. The limits and process of stereo lithography printing is assessed through experimentation using the Formlabs Form 2 printer to develop WR10 waveguide and aperture antennas operating at 94 GHz. Performance and pitfalls are reported for future consideration in exploiting and extending additive manufacturing technology for fabrication of such structures in the optical regime.
A fundamental problem in imaging remote sensing systems is that of scale and resolution. The ability to resolve an object at a distance requires a high resolution sensor, with pixels subtending a small portion of the total field-of-view (FOV) of the imaging system. Traditional approaches to addressing this challenge are fundamentally data limited. To this end, we implemented foveating data reduction models inspired by the bi-foveated vision of birds of prey. The development of such systems for multiple target detection and tracking for air-to-ground target acquisition is important for several defense applications. The relative merits and disadvantages of various optical imaging technologies as well as several image transformations, sampling schemes, and object tracking algorithms were explored. Variable focal lens controlled by pressure, external voltage, or microfluidics demonstrate potential for devices requiring high resolution within a specified range. The distortion, coma, and spherical aberrations that occur can be corrected through the use of adaptive optics and custom 3D printed lenses. In conjunction with the hardware aspects, algorithmic approaches were also considered. The use of dynamically generated, moving foveal regions was investigated for use in motion tracking and object detection algorithms. Through the use of imaging systems with exceptionally large fields of view and localized areas of high resolution, machine vision systems can be implemented with less computational and data overhead. The implementation of our system is suited to use in either unmanned aerial vehicle or autonomous vehicle applications.
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