LinearObserverModel

classdef LinearObserverModel < BaseObserverModel
%LINEAROBSERVERMODEL  Linear observer model
%   sysModel = LinearObserverModel(H, R) creates a class
%   representing an observer measuring a state x by the formula
%      z = H*x + v
%   where v is gaussian noise with mean 0 and covariance R.

    properties
        H  % linear transformation which applied to state gives measurement
    end
    
    methods
        function obsModel = LinearObserverModel(H, R, varargin)
            if nargin > 0
                assert(isnumeric(H));
                assert(isnumeric(R));
                h = @(x,t) (H*x);
                superargs = {h, R, varargin{:}};
            else
                superargs = {};
            end

            obsModel = obsModel@BaseObserverModel(superargs{:});
            
            if nargin > 0
                obsModel.H = H;
                obsModel.J_x = @(x,t) (H);
                obsModel.J_w = @(x,t) (0);
            end
        end
        
        function observation = simulate(this, state, curTime)
        % simulate a true state observation
        
            temp = this.H * state;
            observation = temp + this.cholR' * randn(size(this.cholR, 1), 1);
        end        
        
        function [S C innovation] = observerData(this, predMean, ...
                                                 predCov, meas, curTime)
            S = (this.H * predCov * this.H') + this.R;
            S = (S + S')/2;

            C = predCov * this.H';
            innovation = meas - this.H * predMean;
        end

    end
end