Yapay sinir ağları ile hedef izleme

Bu çalışmada yapay sinir ağlarına (YSA) dayanan basit bir metod, hedef izleme işlemi için sunulmuştur. Kargo uçağı, savaş uçağı, bombardıman uçağı ve ticari uçaklar gibi değişik tipteki altı farklı gerçek uçak için, uçak radarlarından elde edilen pozisyon, hız ve ivme ölçüm veri kümeleri kullanılarak geri yayılım (G Y) algoritması ile YSA eğitilmiştir. YSA test sonuçları, ölçme sonuçları ile iyi bir uyumluluk içindedir. YSA sonuçları, hedef izlemede yaygın bir şekilde kullanılan Kalman filtresinin (KF) sonuçları ile de karşılaştırılmıştır. YSA kullanılarak hesaplanan sonuçların, KF kullanılarak elde edilen sonuçlardan çok daha iyi olduğu gösterilmiştir.

Target tracking with the use of artificial neural networks

In this work, a simple method for target tracking, based on artificial neural netvvorks, is presented. The back-propagation algorithm is used to train the netvvorks by using the measured position, velocity and acceleration data sets obtained from the aircraft radars for the six different real aircrafts such as cargo, bomber, fighter and commercial aircrafts. The test results of artificial neural netvvorks are in very good agreement with the measured results. The results of artificial neural netvvorks are also compared vvith the results of Kalman filter vvidely used in target tracking. it is shovvn that the results calculated by using artificial neural netvvorks are berter than those predicted by Kalman filter.

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