Presents an integrated system for navigation parameter estimation using sequential aerial images, where the navigation parameters represent the positional and velocity information of an aircraft for autonomous navigation. The proposed integrated system is composed of two parts: relative position estimation and absolute position estimation. Relative position estimation recursively computes the current position of an aircraft by accumulating relative displacement estimates extracted from two successive aerial images. Simple accumulation of parameter values reduces the reliability of the extracted parameter estimates as an aircraft goes on navigating, resulting in a large positional error. Therefore, absolute position estimation is required to compensate for the positional error generated by the relative position estimation. Absolute position estimation algorithms using image matching and digital elevation model (DEM) matching are presented. In the image matching, a robust-oriented Hausdorff measure (ROHM) is employed, whereas in the DEM matching, an algorithm using multiple image pairs is used. Experiments with four real aerial image sequences show the effectiveness of the proposed integrated position estimation algorithm.

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.