Reliability indexed sensor fusion (RISF) is a new estimation techique which uses process and measurement noise covariances as the reliability index in an adaptive Kalman filter framework. In RISF, noise covariances are assumed to be highly uncertain and determined by engineering knowledge. The uniform boundedness of the RISF with incorrect noise covariances is proved in the sense that the error covariance is bounded if specified conditions are satisfied. The RISF technique is then applied to the vehicle longitudinal and lateral velocity estimation. Multiple sensors, such as the whell speed sensors, the accelerometers, the yaw rate sensor, and the steering angle sensor, are used for the velocity estimation. Test results show the accuracy of the vehicle velocity estimation by the proposed RISF technique.

Issue Section:
Technical Papers
Keywords:
sensor fusion, adaptive Kalman filters, filtering theory, vehicle dynamics, covariance matrices, nonelectric sensing devices, velocity measurement, reliability
Topics:
Errors, Noise (Sound), Reliability, Sensors, Vehicles, Kalman filters
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