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The challenge in the Autonomous Underwater Vehicle (AUV) navigation technology is how to ensure precise localization accurately. Extended Kalman filter (EKF) is the most widely used navigation method. Despite its long successful application, EKF has a number of problems in application, for instance, the system motion model usually not appropriate to be described as a linear system. This paper proposed...
Autonomous underwater vehicles (AUVs) work in complex marine environments, and sensors play an important role in AUV systems. Therefore, research on sensor failure diagnosis technology is important for improving the reliability of AUV systems. In this paper, a new method combining phase space reconstruction and extreme learning machine (ELM) is proposed. This method is applied to predict sensor output...
An effective and accurate navigation algorithm is the critical to achieve the purpose of precise localization and autonomous navigation for Autonomous Underwater Vehicle (AUV). Extended Kalman Filter (EKF) is one of the most popular methods, because it is easy to implement. In spite of its wide applications, it still suffers from two major drawbacks as follows: (1) the noise covariance matrixes are...
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