Payload size and weight are critical factors for small Unmanned Aerial Vehicles (UAVs). Digital color-infrared photographs were acquired from a single 12-megapixel camera that did not have an internal hot-mirror filter and had a red-light-blocking filter in front of the lens, resulting in near-infrared (NIR), green and blue images. We tested the UAV-camera system over two variably-fertilized fields of winter wheat and found a good correlation between leaf area index and the green normalized difference vegetation index (GNDVI). The low cost and very-high spatial resolution associated with the camera-UAV system may provide important information for site-specific agriculture.

A system utilizing Global Positioning System signals for three-axis attitude determination of a low-Earth-orbiting spacecraft is described. Measurements of wavefront aspect made by observing the phase differences of the same signal received at two separated antennas are processed by a Kalman filter to produce an estimate of vehicle attitude, body rate, disturbance torque, and antenna phase center shift. Factors affecting system accuracy are examined, including global positioning system satellite visibility, number of receiving antennas, and attitude error observability, which is strongly a function of vehicle dynamic motion. The Global Positioning System hardware suite is described as is a typical application to a momentum biased, nadir pointing spacecraft. A high-fidelity computer simulation is used to demonstrate that the global positioning system sensor can lend adequate attitude determination accuracy to this class of missions.

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