Optimization of aimpoints for coordinate-seeking weapons

Abstract

The objective of this thesis is to develop a program that makes use of three types of damage functions to optimize the weapon aimpoints of multiple coordinate-seeking weapons against a unitary target in order to achieve the highest probability of damage (PD). A MATLAB program is used as the coding tool for the development of this algorithm and the optimization process. The program works by first taking in the number of weapons used and arranging them in a fixed uniform spacing on a circle centered on the assumed target location. Then, the weapon characteristics such as the radius of the circle containing the weapon aimpoint, impact angle, dependent (aiming) and independent (ballistic) errors are taken into account, before utilizing each of the three damage functions representing the weapon. A Monte-Carlo simulation method is used to calculate the PDs at incremental radii of weapon placements from the target. Since the damage functions differ in terms of fidelity (accuracy), a comparison in terms of optimal aimpoint radius for the highest PD is made for the results generated for all three damage functions. The simulated results demonstrated that the optimal aimpoint radii for the maximum PD are slightly different for each damage function. In addition, the maximum PD at the optimal aimpoint radius generated for each damage function is lowest for a damage function that has the greatest fidelity (accuracy), which is consistent with the calculated results for single weapons against unitary targets. Also as expected, generating a PD using a higher fidelity damage function takes a longer time than that of a lower fidelity damage function. As such, the user of this program has to take into account the accuracy requirements and time limitations before selecting the damage function to be used to generate the PD.