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Precise positioning of AUV plays an important role in the efficient and reliable underwater operation. The extended Kalman filter (EKF) is the most commonly used method, because this algorithm is easy to implement. However, EKF is only effective for nonlinear systems with approximate linearity, then truncation error is introduced. When the initial state error is large or the system model has high...
As the development of aerial mapping, obtaining the motion parameters of the mapping sensors mounted under the flexural wing of the aircraft is necessary to accomplish the mission. Airborne distributed position and orientation system (DPOS) could be applicable which is composed of master inertial navigation system (INS), several slave INSs and the global positioning system. The slave INS is mounted...
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...
In this paper, a Kalman filter with proportional gain and multiintegral (PMI) gains is proposed to inertial navigation system (INS) and global positioning system (GPS) integration. A generalized fault is first introduced to represent the unexpected inertial sensors’ biases resulted by environment condition changes or performance degradation of INS. Then, a linear time-varying system subject to fault...
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