Collaborative image navigation simulation and analysis for UAVs in GPS challenged conditions

Abstract

Accurate and robust position, navigation, and time (PNT) data is a key-enabler for multi-platform collaborative sensing for a diverse array of military operations. The AFRL Collaborative Robust Integrated Sensor Positioning (CRISP) program has investigated techniques that leverage shared sensor data to enhance the availability of reliable PNT information for all platforms in a network, particularly those that experience GPS outages, utilizing electro-optical (EO) payload data in conjunction with GPS and inertial data. Rockwell Collins has developed an architecture for enabling continuous navigation capabilities for airborne platforms having disparate sensing capabilities in GPS challenged and denied conditions. In this study program the Rockwell Collins architecture was evaluated via a high-fidelity simulation environment. Navigation performance results for our solution were produced and presented by exercising our simulation with an AFRL-provided dataset. The performance results have shown that our collaborative image navigation architecture and implementation supports extended, GPS-level navigation accuracy in GPS Denied conditions.