16 August 2001 Application of fuzzy logic to target tracking in a cluttered environment
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Most of the real world engineering problems are imprecise and they carry a certain degree of fuzziness in the description of their nature. Fuzzy logic is a design methodology that can be used to solve real life problems. It has the advantage of lower development costs, superior features, and better end product performance. Fuzzy logic makes it possible to describe complex systems using expert experience and knowledge in English-like rules, which are easy to learn and use, even by non-experts. Fuzzy technique does not require system modeling or complex mathematical equations. The design methodology is to first understand and characterize the system behavior by using our basic knowledge and experience and then design the algorithm using the fuzzy rules that describe the relationship between its input and output. This is done by debugging the design through simulations and if the performance is not satisfactory we only need to modify or add some fuzzy rules. There exists considerable literature on target tracking based on the Kalman filtering and probabilistic data association (PDA) techniques. A few of these techniques can yield acceptable results in a high-density clutter environment due to the complexity of combined target and measurement to track association or due to the simplification assumed in these techniques. This paper presents the use of fuzzy association rules involved in data association of target measurements under a high-density clutter. The fuzzy tracker is used to track a target and its performance is compared with a standard PDA filter for various signal-to-noise ratios (SNR).
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Ahmed S. Gad, Ahmed S. Gad, Mohamad Farooq, Mohamad Farooq, S. Midwood, S. Midwood, } "Application of fuzzy logic to target tracking in a cluttered environment", Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); doi: 10.1117/12.436939; https://doi.org/10.1117/12.436939

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