Adaptive and interval Kalman filtering techniques in autonomous surface vehicle navigation: a survey
نویسنده
چکیده
This paper reviews the Kalman Filter (KF) as a tool for navigation systems, with focus on uninhabited surface vehicle (USV) navigation. The most common types of sensors being used on such vessels are identified, the KF being at the centre of the data-fusion algorithm. However, some of the limitations of the KF are noted, such as its performance degradation when inaccurate noise statistics are assumed, therefore justifying the use of adaptive techniques to enhance its robustness. The use of such adaptive mechanisms applied to the KF is evidenced in ongoing USV navigation research. A review of the theoretical background of the interval Kalman filter (IKF) is given, and its potential advantage to overcome the limitations posed by the ordinary KF in the face of incomplete knowledge of system dynamics and noise models is discussed. Though the IKF is proposed as a solution to overcome these shortcomings of the ordinary KF, its lack of usage in actual navigation systems is accounted for by the inherent difficulties of its practical implementation. These difficulties are outlined and focus the direction of the research that is required for its successful implementation. USVs are rationalised to constitute ideal platforms on which to develop, test, and prove the effectiveness of IKF-based navigation systems.
منابع مشابه
Design and Experimental Evaluation of integrated orientation estimation algorithm Autonomous Underwater Vehicle Based on Indirect Complementary Filter
This paper aims is to design an integrated navigation system constituted by low-cost inertial sensors to estimate the orientation of an Autonomous Underwater Vehicle (AUV) during all phases of under water and surface missions. The proposed approach relied on global positioning system, inertial measurement unit (accelerometer & rate gyro), magnetometer and complementary filter technique. Complem...
متن کاملGPS/INS Integration for Vehicle Navigation based on INS Error Analysis in Kalman Filtering
The Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in the recent decade. The Micro Electrical Mechanical Sensors (MEMS) successfully solved the problems of price, size and weight with the traditional INS. Therefore...
متن کاملSensor Fusion Based on Fuzzy Kalman Filtering for Autonomous Robot Vehicle
This paper presents the m e w of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-0 environment and is of particular importance for guidance, navigation, and control of flyi...
متن کاملFuzzy Adaptive Kalman Filtering for INS/GPS Data Fusion
This paper is an attempt to generalize the results obtained earlier and presents the method of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-D environment and is of parti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012