Synthesis of Road Networks by Data Conflation

摘要

For application including post disaster scenarios or unmapped areas of conflict, there is a need for rapid real-time synthesis of road networks. GMTI data in conjunction with the assumption that the vehicles move on roads, permit the use of target kinematics to estimate the underlying road network that the vehicles are constrained to. The approach employed for synthesizing the received data into a complete estimate of the road network is through the use of the Hough Transform, to identify line segments which collectively represent the road network. The Total Least Squares is used to characterize the uncertainty associated with this representation as well as provide a more accurate estimate. The uncertainty in each of the estimated parameters can then be approximated by the Cramer Rao lower bounds. Finally the identified segments are merged and connected to provide a more complete representation of the road network. The approach used here is iterative, for example, when new data within the area of interest is received, a better estimate of the road segment can be obtained and the overall road network is updated and allowed to grow in all directions.