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Sea Current and Wind as Additional Factors in Computing the Fuzzy Ship Domain Minimum Safe Distance
Felipe P. Vista IV,Chang Goo Lee,Hak Tae Kim,Kil To Chong,Kim Young Chul 대한전자공학회 2010 ICEIC:International Conference on Electronics, Inf Vol.1 No.1
Collision alert system aboard ship usually determines if another vessel is inside its fixed minimum safe distance to alert the navigators. Utilizing the existing method of augmenting this fixed minimum safe distance with a minimum fuzzy safe distance is a great way to improve the safety factor. Incorporating the effects of water current and the wind as additional factors in addition to ship size, ship speed and sea state in computing the minimum fuzzy safe distance is proposed. Simulation results show that the proposed additional factors gave satisfactory results.
Vista, Felipe P.,Chong, Kil To Hindawi Limited 2018 Journal of sensors Vol.2018 No.-
<P>This paper describes the design, development, and implementation of a real-time sensor fusion system that utilizes the classification and weighing plus extended Kalman filter algorithm to derive heading for navigation using inexpensive sensors. This algorithm was previously tested only through postprocessing using MATLAB and is now reprogrammed using Qt and deployed on a Linux-based embedded board for real-time operation. Various data from inexpensive sensors such as global positioning system devices, an electronic compass, and an inertial measurement unit were utilized to ultimately derive a more reliable and accurate heading value. The algorithm flow can be described with the GPS values first being evaluated and classified which are then fused with the EC heading using classification and weighing, whose result is then passed through an EKF to fuse with the IMU data. Real-time tests and trials were done to prove the operational capability of the developed process. The complete setup and configuration processes of the systems for development and deployment via Qt are also provided for those interested to replicate the process.</P>
Fusing Multiple Inexpensive GPS Heading Data via Fuzzified Ad-Hoc Weighing
Vista IV, Felipe P.,Lee, Deok Jin,Chong, Kil To Trans Tech Publications, Ltd. 2015 Applied Mechanics and Materials Vol.776 No.-
<P>Applying the same principle behind the Ad-hoc weighing used in fusing data from two inexpensive GPS and an electronic compass (EC) brought up the problem of numerous conditions when trying to fuse data from three GPS devices. Fusing data from two GPS and one EC required at least thirty-two (32) conditions while using three GPS would require 182 conditions that would have entailed a complex set of programming codes. Fuzzy logic was explored as a possible candidate to replace the hard-coding of if-then-statements but still perform the ad-hoc algorithm as desired. The GPS Fix and HDOP (horizontal dilution of precision) values are utilized to derive the corresponding weight to be assigned to the individual GPS as well as the overall fused GPS data. Experimental tests using actual GPS data showed the effectivity of the proposed method.</P>
Design of an EKF-CI based Sensor Fusion for Robust Heading Estimation of Marine Vehicle
VISTA FELIPE PATINO,이덕진,정길도 한국정밀공학회 2015 International Journal of Precision Engineering and Vol.16 No.2
An efficient approach for deriving accurate pose and heading values through multi-sensor fusion of data from several inexpensivesensors (such as multiple GPS (Global Positioning Systems), EC (electronic compass), rate gyro) is presented. The proposed multisensorfusion approach is composed of several sub-methods namely initial heading calculation, classification and weighing (CnW),extended Kalman filter (EKF) and then covariance intersection (CI) algorithms. The consecutive implementation of the sub-methodsgives an accurate heading value with lesser RMSE (root mean square error) compared to the original GPS COG (course over ground)and EC. Several experimental tests were done to confirm the good performance of the proposed process.
Vista IV, Felipe P.,Chong, Kil To Hindawi Limited 2019 Journal of sensors Vol.2019 No.-
<P>This paper describes the design and real-time implementation of a proposed algorithm for deriving an accurate heading system by fusing data from various inexpensive sensor devices that is comparable to more expensive maritime navigation systems. The proposed algorithm is a 3-Stage Classification N’ Weighing (CnW) Heading System with forward azimuth (FAz) and extended Kalman filter (EKF). Data from three Global Positioning System devices, an inertial measurement unit, and an electronic compass were fed into the algorithm that can be generally described as Classification N’ Weighing-Stage 1 → forward azimuth → Classification N’ Weighing-Stage 2 → extended Kalman filter → Classification N’ Weighing-Stage 3. The proposed algorithm is shown to be comparably accurate as an expensive marine navigation system, and it has less processing time compared to our previous work. The Qt-anywhere-based system developed on a Linux desktop was successfully downloaded onto an Ubuntu Linux-embedded board for real-time implementation. Important notes related to device naming problems when deploying the system on a Linux-embedded board are also given as reference for those interested to address it.</P>