Tracking highly maneuverable targets in clutter using interacting multiple-model fuzzy-logic-based tracker

Ahmed S. Gad; Mohamad Farooq

doi:10.1117/12.477613

31 July 2002 Tracking highly maneuverable targets in clutter using interacting multiple-model fuzzy-logic-based tracker

Ahmed S. Gad, Mohamad Farooq

Proceedings Volume 4729, Signal Processing, Sensor Fusion, and Target Recognition XI; (2002) https://doi.org/10.1117/12.477613
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The algorithm has the ability to estimate the state of a dynamic system with several modes which can switch from one mode to another. It is also considered to be the best compromise between the complexity and the performance. It is mainly used for tracking highly maneuvering targets in the presence of clutter by invoking the Probabilistic Data Association (PDA) in the estimator structure, also called IMM-PDA. Recently, it has been shown that the PDA technique does not perform well when tracking targets at low signal to noise ratios (SNR). An alternative technique to data association is the Fuzzy Data Association (FDA) which has the ability to track targets in clutter and in a low SNR environment. In this paper, an IMM-FDA technique is proposed for tracking highly maneuvering targets in clutter and in a low SNR environment. Simulations have been conducted to compare the performance of the proposed approach with that of the IMM-PDA. A typical scenario for a highly maneuvering target is considered as a tracking example. The simulation results reveal that both the trackers perform well when tracking the maneuvering target at high SNR. At low SNR, only the IMM-FDA is able to track the target accurately.

Citation Download Citation

Ahmed S. Gad and Mohamad Farooq "Tracking highly maneuverable targets in clutter using interacting multiple-model fuzzy-logic-based tracker", Proc. SPIE 4729, Signal Processing, Sensor Fusion, and Target Recognition XI, (31 July 2002); https://doi.org/10.1117/12.477613

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