Research And Realization Of Kalman Filter On LBL Underwater Acoustic Positioning System

The Long Baseline Underwater Acoustic Positioning System can realize the underwater vehicle high-precision positioning and autonomous navigation in local waters by using acoustic positioning technology. The system makes use of the travel time between the underwater vehicle and transponders to calculate the underwater vehicle's position.However, the travel time cannot be measured precisely because of the complex nature of the underwater channel and the limitation of the system. There are three kinds of error in travel time: high-level error, low-lever error and invalid measurement which may reduce the system positioning accuracy. Kalman filter is a common data processing technology to achieve optimal estimation with linear minimum variance criteria. Kalman filter can process the travel time which has error effectively, reject the high-level error, predict invalid measurement and improve the system positioning accuracy.According to the characteristics of the Long Baseline Underwater Acoustic Positioning System, this dissertation put forward a positioning algorithm with feedback Kalman filter and designed and realized the display and control software of the system.For the Long Baseline Underwater Acoustic Positioning System, this dissertation firstly studied how to model the state equation and measurement equation and how to select the proper initial value and parameter. Then, a positioning algorithm with feedback Kalman filter was put forward. The algorithm used the travel time and position to modify each other,it improved the system positioning accuracy and stability.The display and control software was based on LabWindows/CVI software development platform, making use of multithread programming technology and modular design method. The main functions of the software are as followings: provide a friendly man-machine interfece; real-time control, and harmonize the whole system work; complete the communication between the software and external devices by serial ports; achieve the positioning algorithm with feedback Kalman filter; real-time display the positioning information, save and replay the positioning data. This dissertation describes each functional module realization method in detail. Through software test, the display and control software can run stably and reliably.