Distributed Beacon Requirements for Branch Point Tolerant Laser Beam Compensation in Extended Atmospheric Turbulence

Branch point tolerant phase reconstructors can vastly improve adaptive optic system performance in extended atmospheric turbulence. This thesis explores the performance bounds of two such reconstructors Goldstein\u27s algorithm and hidden phase. A least squares reconstructor is implemented for comparison. System performance is presented for various scenarios, including correction time-delays, wave-front sensor noise, and extended beacons. These scenarios are of interest for laser communication and directed energy systems such as Airborne Laser. Performance bounds are obtained through wave-optics simulation. The extended beacon propagation geometry approximates the USAF AFRL-DE North Oscura Peak range. Results show that branch point tolerant reconstructors outperform least squares for equal correction time-delays. These reconstructors can be made somewhat tolerant to wave-front sensor error. For the case of an incoherent extended beacon, branch point information is lost and the branch point algorithms perform on par with least squares. A coherent extended beacon preserves branch point information, but also induces branch point errors due to coherent speckle. Still, the branch point reconstructors tend to maintain a 1-2 order of magnitude performance advantage over least squares in strong turbulence. While implementation challenges remain, this thesis demonstrates the potential of branch point tolerant phase reconstructors on laser communication and weapons systems

Guidance on marine protected area protection level assignments when faced with unknown regulatory information

Strong human use regulations are an important precondition for marine protected area (MPA) effectiveness. Distinguishing MPAs based on their protection levels has shown advantages, but the availability of regulatory information about allowed activities is a major roadblock towards completing assessments at scale. Here, using a California case study, we explore assigning MPA protection levels following the regulation-based classification system (RBCS) under different scenarios of incomplete regulatory information. In the first group of scenarios (A), only readily available information was used, i.e., information contained in direct MPA implementing regulations and management plans. In the second group (B), information was limited to the activities in ProtectedSeas' Navigator that matched those in the RBCS. From group A, 99% and 100% correct classification of fully and highly protected areas, respectively, were obtained when treating unknown aquaculture, bottom exploitation, and bottom extraction as 'prohibited' and boating, anchoring, and fishing activities as 'allowed'. High classifi-cation accuracy was also obtained for moderately, poorly, and unprotected areas. From group B, 92% and 94% correct classification of fully and highly protected areas were obtained when using the same assumptions for non -fishing activities but using Navigator's Level of Fishing Protection (LFP) score to guide assumptions about un-known fishing activities. Correct classification rates were poorer with different assumptions. Regulation-based MPA evaluation systems can reliably identify fully and highly protected areas in the face of unknown infor-mation, when assumptions about unknown information are guided by contextual indicators such as generally regulated human activities and/or overall level of fishing restriction.info:eu-repo/semantics/publishedVersio

Hue-saturation-value feature analysis for robust ground moving target tracking in color aerial video

ABSTRACT Ground moving target tracking in aerial video presents a difficult algorithmic challenge due to sensor platform motion, non-uniform scene illumination, and other extended operating conditions. Theoretically, trackers which operate on color video should have improved performance vs. monochromatic trackers by leveraging the additional intensity channels. In this work, ground moving targets in color video are characterized in the Hue-Saturation-Value (HSV) color space. Using segmented real aerial video, HSV statistics are measured for multiple vehicle and background types and evaluated for separability and invariance to illumination change, obscuration, and aspect change. HSV statistics are then calculated for moving targets from the same video segmented with existing color tracking algorithms to determine HSV feature robustness to noisy segmentation