Transactions on Control, Automation and Systems Engineering

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Exponential Stability of th PDAF with a Modified Riccati Equation a Cluttered Environment

  • Kim, Young-Shik (Department of Mechanical and Intelligent Systems Engineering, Pusan National University) ;
  • Hong, Keum-Shik (School of Mechanical Engineering and Research Institute of Mechanical Technology, Pusan National University)
  • Published : 2000.12.01
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Abstract

The probabilistic data association filter(PDAF) is known to provide better tracking performance than the standard Kalman filter(KF) in a cluttered environment. In this paper, the stability of the PDAF of Fortmann et al[7], in the presence of uncertainties with regard to the origin of measurement, is investigated. The modified Riccati equation derived by approximating two random terms with their expectations is used to prove the stability of the PDAF. A new Lyapunov function based approach, which is different from the quantitative evaluation of Li and Bar-Shalom[7], is pursued. With the assumption that the system and observation noises are bounded, specific tracking error bounds are established.

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References

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