A Basic Convergence Result for Particle Filtering, Report no. LiTH-ISY-R-2781

نویسندگان

  • Xiao-Li Hu
  • Thomas B. Schön
  • Lennart Ljung
چکیده

The basic nonlinear ltering problem for dynamical systems is considered. Approximating the optimal lter estimate by particle lter methods has become perhaps the most common and useful method in recent years. Many variants of particle lters have been suggested, and there is an extensive literature on the theoretical aspects of the quality of the approximation. Still, a clear cut result that the approximate solution, for unbounded functions, converges to the true optimal estimate as the number of particles tends to in nity seems to be lacking. It is the purpose of this contribution to give such a basic convergence result.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Basic Convergence Result for Particle Filtering, Report no. LiTH-ISY-R-2824

The basic nonlinear ltering problem for dynamical systems is considered. Approximating the optimal lter estimate by particle lter methods has become perhaps the most common and useful method in recent years. Many variants of particle lters have been suggested, and there is an extensive literature on the theoretical aspects of the quality of the approximation. Still a clear cut result that the a...

متن کامل

Basic Convergence Results for Particle Filtering Methods: Theory for the Users, Report no. LiTH-ISY-R-2914

This work extends our recent work on proving that the particle lter converge for unbounded function to a more general case. More speci cally, we prove that the particle lter converge for unbounded functions in the sense of L-convergence, for an arbitrary p ≥ 2. Related to this, we also provide proofs for the case when the function we are estimating is bounded. In the process of deriving the mai...

متن کامل

A robust particle filter for state estimation -- with convergence results, Report no. LiTH-ISY-R-2822

Particle lters are becoming increasingly important and useful for state estimation in nonlinear systems. Many lter versions have been suggested, and several results on convergence of lter properties have been reported. However, apparently a result on the convergence of the state estimate itself has been lacking. This contribution describes a general framework for particle lters for state estima...

متن کامل

Forgetting in Marginalized Particle Filtering and its Relation to Forward Smoothing, Report no. LiTH-ISY-R-3009

The problem of degeneracy in marginalized particle filtering is addressed. In particular, we note that the degeneracy is caused by loss of entropy of the posterior distribution and design maximum entropy estimates to prevent this. The main technique used in this report is known as forgetting. It is shown that it can be used to suppress the problem with degeneracy, however, it is not a proper cu...

متن کامل

New Convergence Results for Least Squares Identification Algorithm, Report no. LiTH-ISY-R-2904

The basic least squares method for identifying linear systems has been extensively studied. Conditions for convergence involve issues about noise assumptions and behavior of the sample covariance matrix of the regressors. Lai and Wei proved in 1982 convergence for essentially minimal conditions on the regression matrix: All eigenvalues must tend to in nity, and the logarithm of the largest eige...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007