파티클 필터에 기반한 새로운 상태 예측 방법

A New Approach of State Estimation based on Particle Filter

  • 박성근 (연세대학교 전기전자공학부) ;
  • 류경진 (연세대학교 전기전자공학부) ;
  • 황재필 (연세대학교 전기전자공학부) ;
  • 김은태 (연세대학교 전기전자공학부)
  • 발행 : 2006.05.01

초록

A particle filter is one of the most famous filters. The reason why the particle filter is widely used is that particle deals with the state estimation problem for not only linear models with Gaussian noise but also the non-linear models with non-Gaussian noise and it receives great attention from many engineering fields. In the point of view state estimator, particle filter is feedforward observer. According to the characteristic of dynamic system, the feedforward observer can estimate real state. However, the speed of convergence of feedforward observer between the actual state and the estimated state cannot be satisfied. Since the particle filter is a sort of feedforward observer, the convergence speed of particle filter is slow, and the particle filter cannot estimate actual state like particle collapse problem. In order to overcome the limitation of particle filter as a kind of feedfoward estimator, we propose a new particle filter which has feedback term, called particle filter with feedback. Our proposed method is analyzed theoretically and studied by computer simulation. Comparisons are made with other filtering mehod.

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