A novel outlier recognition method in surveying data is presented based on Shannon information entropy. The probability distribution of surveying data does not need to be known or hypothesized in this method, and it i...A novel outlier recognition method in surveying data is presented based on Shannon information entropy. The probability distribution of surveying data does not need to be known or hypothesized in this method, and it is not only accurate but also convenient to calculate in this method compared with statistical recognition method.展开更多
Navigation is a critical requirement for the operation of Autonomous Underwater Vehicles（AUVs）.To estimate the vehicle position,we present an algorithm using an extended Kalman filter（EKF） to integrate dead-reckon...Navigation is a critical requirement for the operation of Autonomous Underwater Vehicles（AUVs）.To estimate the vehicle position,we present an algorithm using an extended Kalman filter（EKF） to integrate dead-reckoning position with acoustic ranges from multiple beacons pre-deployed in the operating environment.Owing to high latency,variable sound speed multipath transmissions and unreliability in acoustic measurements,outlier recognition techniques are proposed as well.The navigation algorithm has been tested by the recorded data of deep sea AUV during field operations in a variety of environments.Our results show the improved performance over prior techniques based on position computation.展开更多
文摘A novel outlier recognition method in surveying data is presented based on Shannon information entropy. The probability distribution of surveying data does not need to be known or hypothesized in this method, and it is not only accurate but also convenient to calculate in this method compared with statistical recognition method.
基金financially supported by the National Natural Science Foundation of China(Grant No.51309215)
文摘Navigation is a critical requirement for the operation of Autonomous Underwater Vehicles（AUVs）.To estimate the vehicle position,we present an algorithm using an extended Kalman filter（EKF） to integrate dead-reckoning position with acoustic ranges from multiple beacons pre-deployed in the operating environment.Owing to high latency,variable sound speed multipath transmissions and unreliability in acoustic measurements,outlier recognition techniques are proposed as well.The navigation algorithm has been tested by the recorded data of deep sea AUV during field operations in a variety of environments.Our results show the improved performance over prior techniques based on position computation.
