Shengkai Zhang
ABSTRACT
We present WINS, a state estimator that fuses commodity Wi-Fi and an inertial sensor (IMU) to enable indoor autonomous flight of MAVs. It overcomes the lighting and environmental texture limitations of current vision-based approaches. WINS incorporates two modules: First, a real-time AoA estimation algorithm that outputs drift-free measurements up to 20 Hz to confine the drift of IMU. Second, a novel WiFi-inertial state estimator to let our highly nonlinear system work without the need of prior initializations and without knowing the position of Wi-Fi infrastructure (APs). The preliminary results show that WINS achieves a mean MAV's location accuracy of 61.7 cm with a maximum flying velocity of 1.27 m/s.
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