Hava Trafik Tanımlama ve Teşhis Optimizasyonu için Bir Karar Destek Sistemi

Abstract

Developments in low-visibility, high-speed, precision-guided weapon and platform systems have introduced requirements on the performance of advanced surveillance, detection, tracking, identity and identification systems to support military command and control applications. The effectiveness of, and defense against, advanced weapon systems will depend largely on the timely availability of accurate and precise sensors and intelligence information. To cope with ever-increasing operational requirements and challenging mission environments, autonomous use of sensors will no longer be sufficient. Effective use of multi- and multi-spectral sensors, high situational awareness, planning support and an integrated command and control system have become increasingly important in order to make accurate and timely operational decisions since peacetime. Therefore, the development and fielding of effective multi-sensor, multi-target tracking (MSMTT) systems in an integrated manner, along with classification and identification systems, becomes essential for the effective detection, tracking and identification of increasingly complex targets in challenging operational environments. In this thesis, a fast, reliable and all-encompassing system based on multi-sensor working logic is proposed for the accurate identification and identity of aircraft. The proposed system consists of two layers, namely the lower layer and the upper layer. In the lower layer, only radar sensor data is considered, and unified data are obtained by fusing data obtained from different radars. The aim of the lower layer is to reduce the complexity created on the operator's screen by multiple radars seeing the same target while also obtaining a more balanced information about the target. Data association was performed using a method adopted from literature called the gating algorithm and data deemed suitable for merging were combined. In the upper layer, the gating process from the lower layer was repeated, but this time, data from other sensors (ESM, E/O, and ADS-B) were also included in this algorithm along with radars. The aim of the upper layer is to enable sensors to communicate with each other in real-time, providing the operator with more information about the target on the path to identity by utilizing data obtained from each other. At the end, a comparison was made between the proposed system and the system currently in use at command and control centers. As a result, it was observed that in the proposed system, the standard deviation of the data seen by the operator decreased compared to the current system, and the data update frequency increased.