Research on the Cooperative Localization Model under Nearest Neighbor Criterionr
Xin Guan · Flight Dynamics · 2004
The problem of navigation has received considerable attention and has a wide variety of potential applications. A number of algorithms have been proposed which have been successfully employed in mobile robots, and unmanned aerial vehicles, etc. However, most algorithms are designed for a single platform. This paper presents current work on decentralized data fusion applied to the relative localization among multiple platforms. A novel nearest neighbor-based scheme is proposed to estimate the navigational states own from the range measurement to other platform. The model to calculate the pseudomeasurement and the concomitant error covariance matrix is deduced for the planar circumstance. The simulation results show that the new algorithm can steady navigational states estimate. Thus, at the mission level, multiple platform can move together sharing information with one another in order to produce more accurate and coherent estimates, and increase the chances to success.