Tracking of invader drone using hybrid unscented Kalman-Continuous Ant Colony Filter (HUK-CACF)

Abstract

Splendid Unmanned Aerial Vehicle (UAV) applications upshot its enormous use in densely inhabited areas, which is a matter of concern. In such areas, a proper tracking system is required to track an unauthorized/invader drone to ensure safety. With the flexibility of reaching inaccessible places, an Unmanned Aerial Vehicle Mounted Adaptable Radar Antenna Array (UAVMARAA) could be used. In this regard, a Hybrid Unscented Kalman-Continuous Ant Colony Filter (HUK-CACF) is proposed to estimate the position of the invader drone efficiently. Simulation results demonstrate the efficiency and robustness of the proposed filter for tracking system compared to the existing filters in terms of success rate. Further, for various Adaptable Radar Antenna Array (ARAA) patterns such as Uniform Linear Array (ULA), Uniform Rectangular Array (URA), and Uniform Circular Array (UCA), analysis is done for pertaining actual tracking effect for various parameters such as bearing, Doppler shift, ranging, and Radar Cross Section (RCS) by considering wobbling and mutual coupling (MC) effect. The result shows that the proposed filter outperforms in all the scenarios. Among the various ARAA, URA performs better than the other configurations.