Abstract: Due to the poor adaptive capacity of long-range autonomous underwater vehicles (AUV) for general behavior of the environment, a square-root unscented kalman filter (SUKF) based modeling is proposed. In the offline model of general behavior of the environment, some parameters are time-varying, or not possible to be predicted, these parameters must be estimated and predicted through the information detected by the sensors. According to the sensor’s information online and model offline, SUKF is used to estimate the state and parameter about the general behavior of the environment in real time. Modeling for behavior environment of AUV is the main work, taking propulsion system as an example, a model structure of fault used actuator effectiveness factors (AEFs) is constructed, then the SUKF is used for on-line joint estimation of both the states and AEFs parameters of AUV. Simulators are conducted by using the model of long-range AUV, and the results show the validity of the algorithm. Finally, the factors that affect the performance for estimation of SUKF are analyzed.

Key words: Actuater effectiveness factors(AEFs), General behavior of the environment, Joint estimation, Long-range autonomous underwater vehicles(AUV), Square-root unscented kalman filter(SUKF), Driving parameters Material parameters Performance parameters