Comparison of passive position localization methods based on direction finding

It is very important to achieve passive position localization quickly in terms of efficient usage of electronic support (ES) and electronic attack (EA) systems utilized in defense industry. Traditionally, passive position localization can be done by intersecting target direction finding data based on triangulation method. However, this is inefficient in terms of computation time since big amount of direction finding data is processed at once. Furthermore, the algorithms based on triangulation method require direction finding data covering certain sector which is a problematic issue in the sense of tracking updated position of the target continuously. In this study, passive position localization is analyzed by using extended Kalman filtering (EKF) technique which can be a solution for high computational requirements and timing disadvantages. Moreover, a geolocation method applied by making weighted averaging over blocked data (Block-WIVE) is expressed. Performances of the algorithms are compared over simulation data obtained under various scenarios.