Passive Aircraft Altitude Estimation using Computer Vision

Abstract: This thesis presents a number of methods to estimate 3D structures with a single translating camera. The camera is assumed to be calibrated and to have a known translation and rotation.Applications for aircraft altitude estimation and ground structure estimation ahead of the aircraft are discussed. The idea is to mount a camera on the aircraft and use the motion estimates obtained in the inertia navigation system. One reason for this arrangement is to make the aircraft more passive, in comparison to conventional radar based altitude estimation.Two groups of methods are considered, optical flow based and region tracking based. Both groups have advantages and drawbacks.Two methods to estimate the optical flow are presented. The accuracy of the estimated ground structure is increased by varying the temporal distance between the frames used in the optical flow estimation algorithms.Four region tracking algorithms are presented. Two of them use canonical correlation and the other two are based on sum of squared difference and complex correlation respectively.The depth estimates are then temporally filtered using weighted least squares or a Kalman filter.A simple estimation of the computational complexity and memory requirements for the algorithms is presented to aid estimation of the hardware requirements.Tests on real flight sequences are performed, showing that the aircraft altitude can be estimated with a good accuracy.