Optimum-path-to-go Guidance for Air-to-Ground Munition

Abstract:
BAI has developed an Optimal Path to Go (OPTG) guidance approach capable of generating "near-optimal" guidance commands in real time. Polynomial neural networks are interrogated on-line at regular intervals to obtain the optimal commands, given the current state of the vehicle.

Problem:
The Hydra-7 munition currently under development at Lockheed Martin Missile and Fire Control Advanced Projects required an optimal guidance law that minimized the Kinetic energy loss in the vertical plane. Such a guidance law maximizes the impact velocity and thus the effectiveness of the munition. However, the computational burden of generating real-time optimal commands for a dynamic system such as this is beyond the capability of existing hardware.

Solution:
BAI has developed an Optimal Path to Go (OPTG) guidance approach capable of generating "near-optimal" guidance commands in real time. Using the calculus of variations, a database of neighboring optimal trajectories is generated off-line. Rather than interrogating this database on-line, the trajectories are encoded in a set of polynomial neural networks. These networks are then used on-line to generate near-optimal commands. This approach is also being applied to NASA fleet of Reusable Launch Vehicles for the approach to landing phase of the mission.