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In the recent past, there has been a lot of interest in developing UAVs (Unmanned Aerial Vehicles) to perform a variety of challenging tasks ranging from military defense, surveillance, environmental sensing, etc. This research is one that focuses on quadrotor UAVs deployed for environmental sensing in the oceans. We have developed an algorithm to autonomously control a quadrotor to track and land on the landing pad on a marine vehicle, an autonomous kayak. The algorithm takes up the challenge of tough landing conditions prevalent in the oceans due to winds and currents (causing the target to rock and drift). It has currently been developed for the commercially available AR Drone quadrotor. Landing pad sensing was achieved through image processing techniques using MATLAB. Testing has been carried out both indoors, and outdoors over open water, with a success rate of over 75%. This autonomous control algorithm for the quadrotor would enhance its operating region, preventing the need for it to fly back to the base station and thereby saving valuable flight time in far-off ocean deployments.