A hybrid navigation system of underwater vehicles using fuzzy inferrence algorithm

J. Ocean Eng. Technol. 1997;11(3):170-179.

Korea Institute of Machinery and Materials,Korea Institute of Machinery and Materials,Samsung Iieavy Industry

퍼지추론을 이용한 무인잠수정의 하이브리드 항법 시스템

이판묵,이종무,정성욱

Keywords: Sensor Fusion, AHFRS, Attitude, Heading and Flow Reference System, SSBL, Super Short Baseline, Failure Detection, Fuzzy Inference Logic

핵심용어: 센서 퓨전, 오류감지, 퍼지추론

Abstract

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.