The objective of the autonomous navigation and sensing experiment research (ANSER) project is to demonstrate decentralized data fusion (DDF) and simultaneous localization and map building (SLAM) across multiple uninhabited air vehicles (UAVs). To achieve this objective, the project specifies the development of four UAVs, where each UAV houses up to two terrain sensors and an INS/GPS navigation system. The terrain sensors include a scanning radar, laser/vision and standard vision system. The DDF concept has to be shown to be effective both on a single UAV and on multiple UAVs. The proof of the concept will lie in the ability of the DDF structure to conduct multi-target tracking problems as well as SLAM. To obtain this goal, a number of subgoals are required, most of which have never been attempted before on a research level. The objective of this paper is to present these goals as an overview of the ANSER project along with some simulated and real-time results.

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In wildlife radio tagging, small radio transmitters attached to animals are located by human operators using directional antennas and analog receivers which provide audio output. The location of the transmitter is determined by listening to the signal and scanning the area while closing in. This procedure can be very tedious, especially in rough terrain. Searching radio tags with autonomous unmanned aerial vehicles (UAVs) offers a number of advantages, including better line-of-sight signal reception, terrain-independence and faster localization. In this paper we continue upon previous work by presenting a received-signal-strength (RSS) sensor implementation based on a modified commercial wildlife tracking receiver that is designed to operate on an autonomous fixed-wing UAV. Furthermore, an extension of the search and tracking framework for multiple targets that are undistinguishable from the sensors' point of view is proposed. After a brief system overview and a summary of the particle filter based approach, the signal processing theory and realization of the RSS sensor are outlined, including strategies for frequency tracking and receiver gain control. The paper also presents experimental results.