Navigation parameter estimation from sequential aerial images

Abstract

This paper presents a method for navigation parameter estimation using sequential aerial images, where navigation parameters represent the velocity and position information of an aircraft for autonomous navigation. The proposed navigation parameter estimation system is composed of two parts: relative position estimation and absolute position estimation. Relative position estimation recursively computes the current velocity and position of an aircraft by accumulating navigation parameters extracted from two successive aerial images. However, simple accumulation of parameter values decreases reliability of the extracted parameters as an aircraft goes on navigating, resulting in a large position error. Therefore absolute position estimation is required to compensate for position error generated in the relative position estimation step. A hybrid absolute position estimation algorithm combining image matching and digital elevation model (DEM) matching is presented. In image matching, line segment matching or Hausdorff distance (HD) matching is employed whereas in DEM matching a new algorithm for absolute position estimation by minimizing the variance of displacements is proposed. Computer simulation with real aerial image sequences shows the effectiveness of the proposed algorithm.