Re: Kalman filtering with multiplicative noise

On Jul 21, 5:35 pm, "Bruno Luong" <b.lu...@fogale.fr> wrote:
> d...@myallit.com wrote in message
>
> You might consider Extended Kalman filtering (EKF). Be aware
> about the eventual non-stability of the scheme.
>

What do you mean by the eventual non-stability? I did look at the EKF,
there is some simple sample MATLAB code here:
http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=18189

But in the first few lines of this script it says:

% for nonlinear dynamic system:
%           x_k+1 = f(x_k) + w_k
%           z_k   = h(x_k) + v_k
% where w ~ N(0,Q) meaning w is gaussian noise with covariance Q
%       v ~ N(0,R) meaning v is gaussian noise with covariance R

so the EKF looks appropriate for non-linear process models and
measurement models that can be represented by any arbitrary functions
f(x) and h(x), but the noise is still assumed to be additive.