The concept of enabling drone-swarm engagement simulations using particle-dynamics models and near-neighbors tracking algorithms, motivated by SDI battle management, is examined. The general approach of using particle-dynamics models and near-neighbors tracking algorithms for modeling drone-swarm engagements is similar to nonequilibrium molecular-dynamics modeling of mixing dissimilar particulate materials. With respect to particle-dynamics representation of swarm-engagements, fundamental quantities that can represent characteristics of drone interactions, are interparticle potential functions, which are a function of drone-drone separation, the types of drones interacting, and the nature of the interaction. These potential functions provide formal representation of both deterministic and non-deterministic dronedrone interaction scenarios. The complexity of drone-swarm engagements, similar to that of SDI scenarios, characterized by small time-periods of engagement, multiple types of blue-red force interactions, and the requirement of near-neighbor target tracking, suggest that such a tool be necessary. The utility of the tool in creating potential-theory based control algorithms for swarm-on-swarm engagements is demonstrated using particle-dynamics simulations.
Advanced camouflage patterns, consisting of highly detailed camouflage patterning, require additional methodologies for color evaluation, which is with respect to realistic field conditions. A quantitative metric for evaluation of comouflage patterns, as viewed under realistic field conditions, is “apparent color,” which is the combination of all visible wavelengths (380-700 nm) of light reflected from large camouflage-pattern samples (≥1m2 ) for a given standoff distance (25-100 ft). Camouflage patterns lose resolution with increasing standoff distance, and eventually all colors within the pattern combine and thus appear monotone (the “apparent color” of the camouflage pattern). This paper presents a case-study analysis of apparent camouflage-pattern color using segment-weighted reflectance spectra for the purpose of evaluating apparent color of advanced camouflage patterns with respect to realistic field conditions. Simulation of apparent camouflage-pattern color using this methodology is based on decomposition of camouflage-pattern reflectance with respect to component segments of camouflage patterns.
Advanced camouflage patterns for military applications consist of highly detailed camouflage patterning and multiple tonal (blended) colors. The complexity of these camouflage patterns establishes a need for additional test methodologies for color and pattern evaluation. One metric for evaluation is apparent color, which is the combination of all visible wavelengths (380-700 nm) of light reflected from large (≥1m2) fabric sample sizes for a given standoff distance (25-100 ft). This follows in that camouflage patterns lose resolution with increasing standoff distance, and eventually all colors within the pattern appear monotone (the “apparent color” of the camouflage pattern). The concept of apparent color, however, is based on far-field and statistical characteristics of camouflage patterns. In contrast, the concept of apparent camouflage pattern is to be associated with intermediate distances between observer and target. Accordingly, quantitative metrics for camouflage-pattern viability based on apparent patterns should be different than those for apparent color, thus providing additional criteria for evaluation. This paper presents discussion and prototype simulations based on the concept of apparent camouflage pattern for model development relevant to evaluating camouflage fabrics.
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