Robust target tracking algorithm for MAV navigation system

Micro Aerial Vehicles (MAV´s) are becoming ubiquitous with its ever increasing applications in defense, space and environmental sectors. In real time scenario, MAV´s are expected to perform autonomously and development of intelligent algorithms meant for pattern recognition and object tracking are most demanding. This work concentrates on the development of vision based navigation system for real time target tracking using MAVs. The target is identified based on its color feature and various color models namely RGB, Normalized RGB, HSI, YUV, YIQ, YCbCr, CIELAB and CIELUV are considered for thresholding analysis. The idea is to frame an effective image processing algorithm concerning thresholding time and accuracy. In addition, the robustness of the color models for various noises such as fast fading, gaussian blur, jpeg, jp2k and white noise are also investigated. Simulation results suggests that, Y based color models exhibits less thresholding time, good accuracy and robust to noise. The target tracking algorithm is developed using optimum color model and justified through real time experimentation. A MATLAB (Matrix Laboratory) based navigation system is developed encompassing micro camera, A/V transmitter and receiver unit, flight controller, image processing system and other interfacing circuits. The navigation system is successfully tested in our lab environments and it is proven to be a realizable and a cost effective solution.