Particle filter based on frame difference method i
2016-08-23
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Application background
The so-called particle filter is to find a set of random samples in the state space to approximate the probability density function, using the sample mean instead of integral calculation, and then obtain the system state of the minimum variance estimation process, the image of these samples is called "particle", so called particle filter.Key Technology
Although the probability distribution of the algorithm is an approximate one, but because of the characteristics of the non parametric, it can get rid of the problem of nonlinear filtering. It must satisfy the Gauss distribution. It can be expressed more widely than Gauss model. Therefore, particle filter can be used to accurately express the posterior probability distribution of measurement and control, which can be used to solve the SLAM problem.matlab
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