Coding a Kalman filter for Navigation and Guidance of a Drone

Scenario: An autonomous drone is tasked to perform environmental monitoring by collecting data such as temperature, humidity, and wind speed using on-board sensors. At some time tw > t0, the battery level drops below a known safety-critical limit. To recharge, the drone has to land on a fixed-wing aircraft that is loitering nearby. However, the communication of the drone with the fixed-wing aircraft has been lost at some time tc, where t0 < tc < tw. In other words, the drone can not receive information about the states of the aircraft for t > tc, and the only available information to the drone about the states of the aircraft is the history of measurements in the time interval [t0, tc]. In this project, our goal is to step-by-step develop a complete navigation and guidance protocol for this drone to land on the fixed-wing aircraft using the available information from the on-board sensors so that it can charge its battery and resume its monitoring task. A detailed problem statement can be found here.

Here is the complete methodology of developing a solution for the problem:

At the conclusion of the project, a MATLAB code for implementing the methodology was coded from scratch. If you’re interested in the MATLAB code for the project, please reach out to me via the contact page.