Using a MLAT Surveillance System to Locate Unmanned Aerial Vehicles Flying as a Swarm

Multilateration currently appears a promising technique for the location of dynamic controlled objects. Radar surveillance systems face a limitation due to the low resolution of radars. This paper proposes to use a MLAT surveillance system based on multilateration to address the UAV location problem. Algorithms for determining coordinates based on statistical theory of optimal filtration are considered. For the problem at hand, we performed a statistical simulation of the Kalman filtration algorithm. Our analysis of findings from numerical experiments shows that the proposed algorithm is capable of solving the problem of high-precision positioning and can be used to determine the position of unmanned aerial vehicles flying in a swarm.