Indirect Fire Target State Estimation and Prediction Using Aerial Scout Vehicles

It is well known that target state estimation and prediction methods can have a substantial influence on the outcome of long range, precision-oriented engagements. Due to this fact, a collection of techniques and algorithms have been developed for the purpose of minimizing the delivery error caused by target motion over the flight time of a munition. These legacy compensation techniques have typically come from direct fire, accuracy-oriented assets such as main battle tanks and attack helicopters. However, with the proliferation of unmanned vehicles in the battle space, the target state estimation and prediction capabilities could be extended into the indirect fire domain. The work conducted within examines the challenge of utilizing a reconnaissance drone partnered with a decoupled weapon platform to track a target, predict its motion, and calculate a lead. The information presented within establishes the framework required to enable this capability, develops the individual solution components, and addresses the practical concerns of the implementation. Finally, modeling and simulation is utilized to validate the proposed methods and to draw conclusion on the feasibility of the specified approach.