Cheap joint probabilistic data association with adaptive neuro-fuzzy inference system state filter for tracking multiple targets in cluttered environment

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Atıf İçin Kopyala

Turkmen I., Guney K.

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, cilt.58, sa.5, ss.349-357, 2004 (SCI-Expanded)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 58 Sayı: 5
• Basım Tarihi: 2004
• Doi Numarası: 10.1078/1434-8411-54100254
• Dergi Adı: AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
• Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
• Sayfa Sayıları: ss.349-357
• Erciyes Üniversitesi Adresli: Evet

Özet

The cheap joint probabilistic data association (CJPDA) with the adaptive neuro-fuzzy inference system state filter (ANFISSF) is presented for tracking multiple targets in the presence of low and high cluttered environments. The state update step of the CJPDA filter (CJPDAF) is realized with the ANFISSF instead of Kalman filter. The adaptive neuro-fuzzy inference system (ANFIS) has the advantages of expert knowledge of fuzzy inference system and learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the backpropagation algorithm, is used to identify the parameters of ANFIS. The tracks estimated by using the method proposed in this paper for different tracking scenarios are in very good agreement with the original tracks.