Diffuse Gaussian Multiple-Shot Patterns
MetadataShow full item record
When multiple weapons are fired at a single target, it may not be best to fire all weapons directly at the target on account of errors common to all shote. The probability of hitting the target can sometimes be increased by firing the weapons in a pattern around the target, rather than at directly at it. This observation leads naturally to the problem of finding the optimal pattern. The optimization problem is in general difficult because even calculating the hit probability for a given pattern usually requires numerical integrals. One excpetion is when errors are noromally distributed and the damage function takes on a compatible "Diffuse Gaussian" form. In that case, the hit probability can be expressed as an analyric function of the pattern's aimpoints, and conventional methods used to optimize it. This paper describes the required mathematics for a general diffuse Gaussian form, thus generalizing previous work.
Military Operations Research, 8(3), 2003, pp.59-64.
Showing items related by title, author, creator and subject.
ben Yoash, Roey (Monterey, California: Naval Postgraduate School, 2016-09);Stealth and high endurance make submarines ideally suited to a variety of missions, and finding ways to detect, track, and, if necessary, acquire and attack them has long been a topic of research. In this thesis, we study ...
Neo, Yong Shern (Monterey, California: Naval Postgraduate School, 2013-09);The main objective of the thesis is to develop an unclassified MATLAB-based Weapons Systems Effectiveness program with user-friendly Excel-based Graphical User Interface to evaluate the effectiveness of Air-to-Surface (AS) ...
Automatic target recognition statistical feature selection of non-Gaussian distributed target classes Wilder, Matthew J. (Monterey, California. Naval Postgraduate School, 2011-06);Target and pattern recognition systems are in widespread use. Efforts have been made in all areas of pattern recognition to increase the performance of these systems. Feature extraction, feature selection, and classification ...