Cheap joint probabilistic data association with neural network state filter for tracking multiple targets in cluttered environment

Turkmen, İLKE; Guney, Kerim

doi:10.1080/10798587.2007.10642966

Cheap joint probabilistic data association with neural network state filter for tracking multiple targets in cluttered environment

Atıf İçin Kopyala

Turkmen I., Guney K.

INTELLIGENT AUTOMATION AND SOFT COMPUTING, cilt.13, sa.3, ss.305-317, 2007 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 13 Sayı: 3
Basım Tarihi: 2007
Doi Numarası: 10.1080/10798587.2007.10642966
Dergi Adı: INTELLIGENT AUTOMATION AND SOFT COMPUTING
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.305-317
Erciyes Üniversitesi Adresli: Evet

Özet

In this paper a cheap joint probabilistic data association (CJPDA) with the neural network state filter (NNSF) is presented for tracking multiple targets in low and high cluttered environments. The state update step of the CJPDA filter (CJPDAF) is realized with the NNSF instead of Kalman filter. Through simulation, a comparison is made to show the performance difference between the CJPDA with NNSF (CJPDA-NNSF) proposed in this paper and the CJPDAF for different tracking scenarios. It was shown that the tracking performance of the proposed method is better than that of the CJPDAF.