Development of an integrated navigation algorithm based on IMU, depth, DVL sensors and earth magnetic field map

Inertial navigation system has drift error in underwater applications. Use of DVL with Kalman filter for position and attitude correction is common. Using velocity data decreases drift error in position estimation but this error exists and increases linearity with time. In this article the navigation system consists of inertial measurement unit (IMU) and a Doppler velocity log (DVL) along with depth sensor. With use of magnetic field measurement and earth magnetic field map a new measurement is generated. Discrete extended Kalman filter with indirect feedback is used for tightly coupled integrated navigation algorithm. This algorithm is based on inertial navigation error dynamics. This paper demonstrates the effectiveness of algorithm through simulation. The procedure of simulation is done by sensor data generation. Arbitrary trajectory with specific kinematic characteristic (linear and angular velocity and acceleration) is generated. Sensor data by adding noise and bias to kinematic characteristic of trajectory is produced. Simulation results reveal that the new algorithm with use of magnetic data and earth magnetic field map decreases the drift error with comparison to conventional INS-DVL integrated navigation algorithm.