Implementation and Performance Comparison of Indirect Kalman Filtering Approaches for AUV Integrated Navigation System using Low Cost IMU

Strapdown Inertial Navigation System (SINS) estimates position, velocity, and attitude of vehicle using the signals measured by accelerometer and gyroscope and is basedon dead-reckoning principle. Due to different imperfections in measurements, and the consecutive integration of theacceleration signals, estimation error increases with time and itis acceptable only for short times in the low cost SINS. In order to reduce the error, auxiliary sensors together with inertial sensors are utilized and to combine the data estimated by SINS with the signals measured by auxiliary sensors, data fusionmethods based on direct and indirect Kalman filtering is used. The feedforward and feedback structures are two commonapproaches of the indirect filtering. In this paper, an underwater integrated navigation system has been designed using indirect filtering approaches due to lower computationalload and higher reliability with respect to the direct approach. The auxiliary sensors used consist of DVL, Gyrocompass, anddepthmeter. The performance of the designed system has been studied using real measurements. The experimental results showed that the root mean square error in the estimated position for feedforward structure is reduced from 3.2 to 0.2 percent of the travelled distance when using feedback structure

کلیدواژه ها:

Strapdown inertial Navigation System ، Integrated navigation system ، Indirect Filtering approaches ، Feedforward and Feedback Kalman filter