<title>System for real-time generation of georeferenced terrain models</title>

Abstract

A growing number of law enforcement applications, especially in the areas of boarder security, drug enforcement and antiterrorism require high-resolution wide area surveillance from unmanned air vehicles. At the University of Massachusetts we are developing an aerial reconnaissance system capable of generating high resolution, geographically registered terrain models (in the form of a seamless mosaic) in real-time from a single down-looking digital video camera. The efficiency of the processing algorithms, as well as the simplicity of the hardware, will provide the user with the ability to produce and roam through stereoscopic geo-referenced mosaic images in real-time, and to automatically generate highly accurate 3D terrain models offline in a fraction of the time currently required by softcopy conventional photogrammetry systems. The system is organized around a set of integrated sensor and software components. The instrumentation package is comprised of several inexpensive commercial-off-the-shelf components, including a digital video camera, a differential GPS, and a 3-axis heading and reference system. At the heart of the system is a set of software tools for image registration, mosaic generation, geo-location and aircraft state vector recovery. Each process is designed to efficiently handle the data collected by the instrument package. Particular attention is given to minimizing geospatial errors at each stage, as well as modeling propagation of errors through the system. Preliminary results for an urban and forested scene are discussed in detail.

A Novel System for Correction of Relative Angular Displacement between Airborne Platform and UAV in Target Localization

“…These methods, which are based on sensor data fusion, involve the complex issue of fleet route control [14,15,16] and need coordination among multiple UAVs, thus resulting in a higher hardware cost, more task time in most of the cases, and a greater risk in case of emergency. These exceptions apart, methods based on Kalman filter, Recursive Least Squares (RLS) filter, nonlinear filter [3,6,17,18] and methods based on video sequence [19,20,21,22,23,24] are also proposed to estimate the location. Most of these use the same aircraft at different time to improve the accuracy, but the optimization process requires time, that cannot meet the real-time requirement.…”

Incremental, orthorectified and loop-independent mosaicking of aerial images taken by micro UAVs

“…Automatic mosaicking by 3D-reconstruction and epipolar geometry [8], [14], combining global positioning system (GPS), inertial measurement unit (IMU) and video sensors for external distortion correction and geo-referencing [3], waveletbased stitching [17], triangulated irregular network registration and perspective correction [13] and high altitude imaging and mosaicking [19], [5], [10], [13] are some of those examples. Schultz et al [11] use a digital elevation model to mosaic images taken from an airplane. Hruska et al [7] introduce an appropriate platform for small UAVs to be able to provide high resolution and georeferenced images by exploiting GPS and IMU.…”

Digital elevation map building from low altitude stereo imagery

“…DEMs are of course very common in geographic information systems, for which low resolution maps are usually derived from aerial or satellite imagery (radar, lidar or vision -e.g. see [6]). Roboticists also paid a lot of attention to the building of such maps [7,8,9], but to our knowledge only a few contribution are related to the building of very high resolution DEMs using low altitude imagery [10].…”