UAV-based multi-sensor data fusion processing

Abstract

This article presents a mathematical model for an Unmanned Aerial Vehicle (UAV)-based, multi-sensor data integration. As background, this article first discusses the design and the implementation of a low-cost civilian UAV system, including its field flight validation, system calibration and mapping accuracy evaluation. Then, the photogrammetry-based mathematical model is developed. This multi-sensor, mathematical model reveals that the boresight matrix in a low-cost UAV system does not remain constant. This contradicts the practice in traditional airborne mapping systems where the boresight matrix is assumed to be a constant over an entire mission. Thus, to achieve highly accurate mapping, exterior orientation parameters (EOPs) for each video frame in a low-cost UAV mapping system have to be estimated. This model can achieve a planimetric mapping accuracy using 1-2 pixels when compared with the United States Geological Survey digital orthophoto quadrangles (USGS DOQ) orthophoto.