Trajectory Optimization for Target Localization and Sensor Bias Calibration with Bearing-Only Information

Abstract

The problem of trajectory optimization of an unmanned aerial vehicle (UAV) for static target localization with biased bearing measurements is considered. The angular bias in sensor measurements is modeled as an additive constant in the observation model and jointly estimated with the position of the target. The necessary conditions for system observability of this estimation problem is first derived analytically with geometrical interpretations provided. The trajectory of UAV is designed based on the Fisher Information Matrix (FIM) considering physical constraints to enhance the system observability. Simulation results with Monte-Carlo runs are presented to demonstrate the improvement in target localization with biased measurements by UAV trajectory optimization.