Kinetic Energy Weapon Guidance Utilizing Fuzzy Logic

Conventional guidance algorithms for exoatmospheric kinetic energy weapons are based on algorithms developed for endoatmospheric missile systems. With the appropriate assumptions and definitions, the algorithms can be shown to be optimal. Although they perform well under limited circumstances, the algorithms perform poorly in the general case because of inefficient use of imprecise information about the target, inefficient management of fuel resources, and a general lack of robustness. An algorithm which is better matched to the particular requirements of the exoatmospheric KEW guidance problem is needed. Fuzzy logic decision theory is shown to be directly applicable to this problem with the appropriate selection of fuzzy set definitions and membership functions. The objective of this research effort is to develop a guidance algorithm based of fuzzy logic by selecting fuzzy constraint sets, constraint weights, and the fuzzy decision function. This algorithm will then be demonstrated and its performance compared to conventional guidance algorithms through the use of an existing 6DOF simulation. The benefit of the algorithm in terms of reduced fuel utilization, decreased miss distance, increased robustness, and ease with which supplemental constraints can augment performance will be demonstrated.