The performance analysis of extended Kalman filter on radar target tracking

Key Findings & Data:For this purpose, the obtained real radar datasets are used for extraction of the target motion model, observation model, processing noise and measurement noise equations based on experimental study respectively.

💡

Conclusion & Impact:The evaluation process is done for some processing and measurement noise level and successful results are obtained.

🔬Design:Modeling & Simulation

📍Scope:Comprehensive Sample

⚙️Variables:Domain Parameters

Abstract

In this study, the tracking performance of radar target tracking process by using extended Kalman filter is analyzed. For this purpose, the obtained real radar datasets are used for extraction of the target motion model, observation model, processing noise and measurement noise equations based on experimental study respectively. Extended Kalman filter algorithm is applied to the equations and the results of target tracking are evaluated. The evaluation process is done for some processing and measurement noise level and successful results are obtained.

🔖

Cite This Article

TÜRKOĞLU, İ., AVCI, E., POYRAZ, M. (2022). The performance analysis of extended Kalman filter on radar target tracking. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 6 - Sayı: 2, 147–155. https://ajindex.com/articles/543799

📄 Full Text PDF Viewer

Open in New Tab ↗

↗New Tab

📄

PDF görüntüleyici hazırlanıyor...

References (1)

. Mahafza, B., R., Radar Systems Analysis and Design Using, Chapman & Hall/CRC, United States of America, p.p.529, 2000. [2]. Ahern, J., Delisle, G. Y., etc., Radar, Lab-Volt Ltd., vol. 1, p.p. 4-7 Canada, 1989. [3]. Lana, “A., Multi-Target Tracking Algorithms Employing Both Kalman Filtering and Probabilistic Data Association”, M.Sc. Thesis, Istanbul Technical University, Graduate School of Natural and Applied Sciences, p.p.77, 2001. [4]. Gulec,U., Maneuvering Target Tracking, M.Sc. Thesis Gazi University Institute of Science and Technology, p.p.114, 2000. [5]. Blackman, S. S., Multi-target Tracking with Radar Application, Artech House, 1986. [6]. Dungate, D., Theobald, R., Nurse, F., “Higher-order Kalman filter to support fast target tracking in a multi-function radar system”, Target Tracking: Algorithms and Applications (Ref. No. 1999/090, 1999/215), IEE Colloquium on, 11-12 Nov. Page(s): 14/1 -14/3, 1999. [7]. Que, W., Peng, Y., Lu, D., Hou, X., “A new approach to data fusion for stealth targets tracking”, Radar 97 (Conf. Publ. No. 449), 14-6 Oct. 1997 Page(s): 657 -661, 1997. [8]. Salmond, D., “Target tracking: introduction and Kalman tracking filters”, Target Tracking: Algorithms and Applications (Ref. No. 2001/174), IEE, Volume: Workshop, Page(s): 1/1 -1/16 vol.2, 2001. [9]. Turkoglu, I., Arslan A., Feature Extraction Method Based On Power Spectrum of Ar Model And Artificial Neural Network For Target Classification In The Pulse Radars”, Gazi University, Technical Education Faculty, Journal of Polytechnic, 5(2), p.p. 121-127, (2002). [10]. Wilmut, M.J., Ozard, J.M., Woods, B., An efficient target tracking algorithm for matched field processing”, OCEANS '93. 'Engineering in Harmony with Ocean'. Proceedings, 18-21 Oct. 1993 Page(s): III/81 -III/85 vol.3, 1993. [11]. Mazor, E., Averbuch, A., Bar-Shalom Y. and Dayan, J., “Interacting Multiple Model Methods in Target Tracking: a survey”, IEEE Trans. on Aero Elec. Systems, Vol. 34, No.1, p.p. 103-119, 1998. [12]. Zhou, B. ve Bose, N., “An Efficient Algorithm for Data Association in Multi Target Tracking”, IEEE Trans. On Aero Elec Sys 31: (1), p.p. 458-468, 1995. [13]. Sun, H. Ve Chiang, S., “Tracking Multitarget in Cluttered Envirenment”, IEEE Trans. on Aerospace and Elec. Systems Vol. 28 No. 2, p.p.546-559, 1992. [14]. Chen, B., and friends, “Tracking of Multiple Maneuvering Targets in Clutter Using IMM/JPDA Filtering and Fixed-lag Smoothing”, Automatica 37, p.p. 239-249, 2001. [15]. Wang, T. C.