Department Publications

This paper presents a sound source localization method using an irregular microphone array embedded in a drone. Sound source localization is an integral function of drone audition systems which enables various applications of drones such as search and rescue missions. However, the audio recordings using the on-board microphones obscure the sound emitted by a source on the ground due to drone generated motor and propeller noise, thus leading to an extremely low signal-to-drone noise ratio (SdNR). In this paper, we propose a cross-correlation based direction of arrival (DOA) estimation technique using the time difference of arrival (TDOA) at different microphone pairs, with noise angular spectrum subtraction. Through the measured current-specific drone noise spectrum, noise suppression has been achieved from the multi-channel recordings. Experimental results show that the proposed method is capable …

This paper addresses the problem of deploying unmanned aerial vehicles (UAVs) to assist data collection and transmission in wireless sensor networks (WSNs). A multi-UAV deployment algorithm is proposed for an energy-constrained network to minimize the maximum transmit power of the sensor node (SN), while satisfying data rate and transmit power constraints. The problem is divided into two subproblems, namely, UAV-SN association, and UAV positioning. First, the UAV-SN association is addressed using a customized Gale-Shapley algorithm. Then, the 2D positions of the UAVs are decided using a modified pattern search algorithm. The two subproblems are solved alternatively in an iterative manner to obtain a near-optimal solution. Compared to baseline algorithms, the proposed solution results in at least 4-fold and 4.5-fold reductions in the number of iterations required for convergence, and the maximum …

This paper compares the two take-off methods; vertical take-off and bird take-off for quad-plane unmanned aerial vehicles. Energy consumption and flying quality of the two methods are assessed. Often, the quad-plane aerial vehicles take off vertically using the quad mode, and when the reference altitude is reached the plane mode kicks in. The rarely used bird take-off mode, uses both quad and plane modes kick in together at the take-off so that the UAV gains the altitude and airspeed symultaneously lower energy. The experiments were carried out with a 1.35kg quad-plane on a two short flights conducted back-to-back under similar environmental conditions. It has been found from the flight data that the bird take-off helps quad-plane to fly 10.8\% more distance for a unit of energy than with the vertical take-off. It was also observed that the VTO method shows sudden altitude drop during the quad to plane control …

Mobile users may experience frequent service outages or poor quality of service in rural areas due to the scarcity of base stations in the proximity. Therefore, a cost effective and flexible solution is introduced in this paper with unmanned aerial vehicles (UAVs) and terrestrial base stations (TBSs), coexisting under a stochastic network with the combination of millimeter waves and non-orthogonal access (NOMA) techniques. This is achieved by deploying both the UAVs (millimeter wave frequencies) and TBSs (sub-6 GHz frequencies) in the same system, and selecting the transmitter based on a user association scheme. The maximum signal-to-interference-plus-noise ratio (SINR) and the closest transmitter user association schemes are compared using extensive simulations to identify the most suitable scheme in terms of the outage probability and the achievable downlink rate. The results show that the closest …

The quadrotor is an under-actuated nonlinear system that poses challenges in modeling and controller design. This work uses the translational (Newtonian) and rotational (Eulerian) dynamics of the quadrotor to build a decoupled control system. A linear quadratic Gaussian (LQG) regulator is used as the controller, and two extended Kalman filters are used for state estimation in the two dynamic models. The entire design process from modeling to flight simulation is presented. Model linearization while preserving controllability, state-space modeling under gravity disturbance, feedforward compensation, LQR gain adjustment, actuator dynamics, sensor system for observability, adaptation of extended Kalman filter, and its limitations are presented.