UAV-BASED MULTI-SENSOR DATA FUSION FOR TIME-CRITICAL DISASTER RESPONSE

摘要

We present a mathematical model for a UAV-based, multi-sensor data integration. As a background, we first discuss the design and the implementation of a low-cost civilian UAV system, including its field flight validation, system calibration, and mapping accuracy evaluation. Then, this photogrammetry-based mathematical model is developed. The field flight tests demonstrate that the designed low-cost UAV is capable of collecting clear and high-resolution video. The UAV can be controlled and navigated remotely and video stream and navigation data strings, including position and attitude, can be downlinked to the ground control station in real-time. The present multi-sensor, mathematical model reveal 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 a high-accurate mapping, EOPs of each video frame in a low-cost UAV mapping system have to be estimated. The present model can achieve a planimetric mapping accuracy using 1-2 pixels when compared with the USGS DOQ orthophoto.