Fuzzy Logic Applications to Fire Control Systems

The paper objective is to study and solve one of the problems encountered in the development of a fire control system. Fire control encompasses all operations required to apply fire on a target. We can not cover in this paper the whole set of mathematical problems in which fire control applications can be divided. Therefore, we will focus in one of the initial phases, the target detection problem. In general, the application of a segmentation algorithm to a data set as a preprocessing of the data previous to an unsupervised classification algorithm improves the probability of detection. The paper presents such a combination. Expert information about the encounter classes will be used for a supervised classification of the example picture. In the first place, we will use a segmentation algorithm to found the natural homogeneous classes in the data. These classes will be explored by an unsupervised clustering algorithm. The unsupervised classification will be performed on the segmented image. Once the classes have been determined that way the classification will be done over the original image.

I. Introduction

Fire Control encompasses all operations required to apply fire on a target. Usually Fire Control systems can be characterized as either Tactical or Technical. Tactical Fire Control Systems are Command, Control and Intelligence Systems that focus on the planning and evaluation aspects of Fire Control. Tactical Fire Control Systems are responsible for activities such as identifying targets based on data from multiple sources, prioritizing targets, assigning specific weapons for use against specific targets and assessing damage after striking.