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add set_state to kalman filter for the case we know the initial state (#246)
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@ -36,6 +36,13 @@ namespace dlib
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void set_process_noise ( const matrix<double,states,states>& Q_) { Q = Q_; }
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void set_measurement_noise ( const matrix<double,measurements,measurements>& R_) { R = R_; }
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void set_estimation_error_covariance( const matrix<double,states,states>& P_) { P = P_; }
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void set_state ( const matrix<double,states,1>& xb_) {
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xb = xb_;
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if (!got_first_meas) {
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x = xb_;
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got_first_meas = true;
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}
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}
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const matrix<double,measurements,states>& get_observation_model (
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) const { return H; }
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@ -93,6 +93,18 @@ namespace dlib
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understand what you are doing.)
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!*/
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void set_state (
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const matrix<double,states,1>& xb
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);
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/*!
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ensures
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- #get_predicted_next_state() == xb
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- If update() is never called with a measurement
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#get_current_state() == get_predicted_next_state()
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(Can be used when the initial state is known, or if the state needs to be corrected
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before the next update())
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!*/
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const matrix<double,measurements,states>& get_observation_model (
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) const;
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/*!
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