Work

Path planning with uncertainty for aircraft under threat of detection from ground-based radar

Year: 2025

Type: article

Abstract: Mission planners for aircraft operating under the threat of detection by ground-based radar systems are concerned with the probability of detection. Current path planning methods for such scenarios consider the aircraft pose, radar position, and radar parameters to be deterministic and known. This paper presents a framework for incorporating uncertainty in these quantities into a radar detection model that is used by a path planner. The developed path planner evaluates the radar detection risk in the presence of uncertainties and uses linear covariance analysis to efficiently generate error budgets. The error budgets identify the contribution of each source of uncertainty (e.g., sensor measurement noise, radar position uncertainty) to the overall variability in the probability of detection. The framework is applied to a modified visibility graph path planner that uses the detection risk and its variability to calculate path adjustments to maintain the detection risk below a specified threshold. The results show that the framework is effective at providing actionable information to the mission planner that improves the final planned path and reduces the detection risk.

Source: The Journal of Defense Modeling and Simulation Applications Methodology Technology

DOI: 10.1177/15485129251327178

Authors: Austin Costley, James Swedeen, Greg Droge, Randall Christensen, Robert C Leishman

Institutions: Utah State University, Draper Laboratory

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Air Force Research Laboratory

Award: G8764003594