classDefinitions.py 文件源码

def predictAisMeasurements(self, scanTime, aisMeasurements):
        import pymht.models.pv as model
        import pymht.utils.kalman as kalman
        assert len(aisMeasurements) > 0
        aisPredictions = AisMessageList(scanTime)
        scanTimeString = datetime.datetime.fromtimestamp(scanTime).strftime("%H:%M:%S.%f")
        for measurement in aisMeasurements:
            aisTimeString = datetime.datetime.fromtimestamp(measurement.time).strftime("%H:%M:%S.%f")
            log.debug("Predicting AIS (" + str(measurement.mmsi) + ") from " + aisTimeString + " to " + scanTimeString)
            dT = scanTime - measurement.time
            assert dT >= 0
            state = measurement.state
            A = model.Phi(dT)
            Q = model.Q(dT)
            x_bar, P_bar = kalman.predict(A, Q, np.array(state, ndmin=2),
                                          np.array(measurement.covariance, ndmin=3))
            aisPredictions.measurements.append(
                AIS_prediction(model.C_RADAR.dot(x_bar[0]),
                               model.C_RADAR.dot(P_bar[0]).dot(model.C_RADAR.T), measurement.mmsi))
            log.debug(np.array_str(state) + "=>" + np.array_str(x_bar[0]))
            aisPredictions.aisMessages.append(measurement)
        assert len(aisPredictions.measurements) == len(aisMeasurements)
        return aisPredictions