Ship track estimation using GPS data and Kalman Filter
- Resource Type
- Conference
- Authors
- Assaf, Mansour H.; Petriu, Emil M.; Groza, Voicu
- Source
- 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Instrumentation and Measurement Technology Conference (I2MTC), 2018 IEEE International. :1-6 May, 2018
- Subject
- Bioengineering
Engineering Profession
General Topics for Engineers
Signal Processing and Analysis
Instrumentation and measurement
Extended Kalman Filter
tracking
sensors
Global Positioning System
- Language
Extended Kalman Filter (EKF) is a technique used in non-linear applications and dynamic systems identification (e.g. tracking marine vessels and ships) that require state and parameter estimation. This paper studies Kalman Filter (KF) based techniques for tracking ships using Global Positioning System (GPS) data. The present work proposes to exploit information from GPS sensors in order to track a ship in real-time. The absence and presence problem of a ship is handled by a applying KF theory to analyze GPS coordinates and compare current marine vessel routes to previously recorded ones. To study tracking performance, the system was implemented in C++ and simulation results demonstrate the feasibility and high accuracy of the proposed tracking method.