NUMERICA CORPORATION — Department of Defense SBIR Phase I: All sensors are less than perfect in their perception of the environment, including knowle

Description

All sensors are less than perfect in their perception of the environment, including knowledge of their own position and orientation. These errors lead to inaccuracies in fulfilling their responsibilities, and less than optimal performance in support of warfighters. When sensors in a network seek to share their information with each other, such errors can be compounded, offsetting much of the gain to be had from fusing information from multiple sensors. Target tracking using data from a network of sensors offers challenges of its own, especially if the network nodes want to maintain a Single Integrated Air Picture (SIAP). Fortunately, there are recently developed statistical methods for estimating the systematic errors, mitigating the remaining stochastic errors, and efficiently maintaining SIAP among the members of a sensor/tracking network. Numerica is at the forefront of the research and development of these algorithms, and we propose to adapt and extend these methods to develop an integrated data registration system for networked aircraft for the US Navy.