Propagate the state distribution to the current time step using a Kalman filter prediction step. Parameters ---------- kf : kalman_filter.KalmanFilter The Kalman filter.
(self, kf)
| 107 | self.time_since_update += 1 |
| 108 | |
| 109 | def predict(self, kf): |
| 110 | """Propagate the state distribution to the current time step using a |
| 111 | Kalman filter prediction step. |
| 112 | Parameters |
| 113 | ---------- |
| 114 | kf : kalman_filter.KalmanFilter |
| 115 | The Kalman filter. |
| 116 | """ |
| 117 | self.mean, self.covariance = kf.predict(self.mean, self.covariance) |
| 118 | self.increment_age() |
| 119 | |
| 120 | def update(self, kf, detection): |
| 121 | """Perform Kalman filter measurement update step and update the feature |
nothing calls this directly
no test coverage detected