Particle filter method

A particle filter and particle technology, applied in the field of nonlinear filtering, can solve the problems of poor filter performance and particle degradation

Active Publication Date: 2014-03-26
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

However, with the continuous iteration of particles, the particle filter will degenerate, which will make the filtering performance worse.

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[0027] The importance sampling method (that is, the method of obtaining the importance density function) has a great influence on the effect of particle filtering. If the importance sampling method is not suitable, it will cause serious particle degradation and affect the filtering effect. Among the existing particle filter algorithms, there are mainly EKF and UKF methods for generating importance density functions, but these two methods are computationally complex and have limited accuracy. The invention provides a particle filter method, which utilizes an improved particle filter algorithm to generate an importance density function from the particle filter, and obtains a new filter method called PF-PF.

[0028] The method steps are as follows:

[0029] Step 1, initialize the particles, particle weight Among them, x0 is the initial moment (t 0 time) collection of particles. for t 0 The i-th state vector (called particle) at time, N is the number of generated particles...

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Abstract

The invention provides a particle filter method. The method comprises the step 1 of initializing particles; the step 2 of obtaining a measurement value at the k moment, then utilizing the particle filter method to calculate a mean value and variance in a parallel mode in N particle filter process, then conducting approximate treatment to obtain an importance density function and extracting sampling particles; step 3 of calculating the importance weight of each sampling particle according to the importance density function obtained in the step 2; step 4 of conducting normalization processing on the importance weight obtained in the step 3; step 5 of conducting re-sampling according to the weight obtained after normalization processing in the step 4 to obtain a new particle sequence and step 6 of testing the probability density after calculating the particle sequence xik obtained in the step 5, and outputting a filter result. The particle filter method is simple in calculating process, and can solve the particle degeneracy problem to a certain degree and improve the particle filter performance.

Description

technical field [0001] The invention belongs to the technical field of nonlinear filtering, and in particular relates to a particle filtering method. Background technique [0002] Filtering is a technology accompanying signal transmission. The signal transmission process is inevitably affected by internal and external interference. In order to obtain the desired signal and eliminate interference, the signal must be filtered. For nonlinear systems, it is very difficult to obtain accurate optimal filtering solutions through Bayesian estimation. Commonly used nonlinear filtering methods mainly include extended Kalman filtering (EKF) and unscented Kalman filtering (UKF). However, these two nonlinear filtering methods are limited by the degree of nonlinearity and the type of noise. Therefore, some scholars have proposed a particle filter (PF) algorithm with a wide range of applications. Particle filter is a sequential Monte Carlo simulation method based on the Bayesian estimati...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H03H21/00
Inventor 夏元清蒲钒耿秀美邓志红付梦印闫莉萍
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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