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This paper presents a technique and its system that localizes a rotary-wing Micro Air Vehicle (MAV) in indoor environments even under Non-Line-of-Sight (NLoS) conditions. The technique is based on the system with the MAV having a wireless microphone and a ground station having multiple microphones. The technique identifies the location of the MAV in two-dimensional space by measuring the Time-of-Arrival (ToA) of acoustic signals caused by the rotation of blades at the MAV. The technique then applies an iterative algorithm that corrects the NLoS errors and computes the true ToA based on maps of known indoor environments in a computationally inexpensive manner. To suppress noise in the received signals and thus improve the robustness of ToA estimation, the generalized cross-correlation with phase transform and a bandpass filter is derived and applied. The performance of the proposed technique was examined experimentally by its comparison with three existing ToA-based localization techniques. Experimental results show the superiority of the proposed technique, demonstrating its potential for aiding indoor MAVs in autonomous navigation.

This paper presents Micro Aerial Vehicles (MAVs) and their cooperative systems including Unmanned Ground Vehicles (UGVs) and a Base Station (BS), which were primarily designed for the 1st US-Asian Demonstration and Assessment on Micro-Aerial and Unmanned Ground Vehicle Technology (MAV08). The MAVs are of coaxial design, which imparts mechanical stability both outdoor and indoor while obeying a 30 cm size constraint. They have carbon fibre frames for weight reduction allowing microcontrollers and various sensors to be mounted on-board for tele-operated and waypoint control. The UGVs are similarly equipped to perform their own search and tracking mission but also to support the MAVs by relaying data between the MAVs and the BS when they are out of direct range. The BS monitors the vehicles and their environment and navigates them autonomously or with humans in the loop through the developed GUI. The ability of the MAV in flight was demonstrated by showing continuous hovering. The efficacy of the overall system was validated by autonomously controlling two UGVs for cooperative search.