Key Technology Research On Integrated Navigation For Underwater Applications

The development of the underwater equipment is inseparable from precise navigation systems. Doppler Velocity Log (DVL)/Inertial Navigation System (INS) integrated navigation is a frequently used navigation method in uncharted water. By in-depth studying the navigation technology to improve the responsibility, concealment, and anti-jamming capability of the navigation system, the capability of the underwater equipment could be further improved.In order to improve the response capability and suitability of the underwater equipment, we hope the time of the initial alignment and coordinate calibration processes could be as short as possible. So the first two parts are aimed on how to speed up these two processes. In order to improve the concealment of the underwater equipment, the next part proposes an integrated navigation method for the condition that the information of the aided sensors is sparse. And the last part aims on an inertial measurement unit (IMU) rotation technology to improve attitude sensing for the condition that no aiding sensors are available. The research is listed as follows.1) In the initial alignment part, owing to the in-motion condition and the lack of the GPS, a DVL aided in-motion alignment algorithm is proposed. The velocity update equation and its integral form in the body frame are studied, and the attitude coarse alignment becomes an optimization-based attitude determination problem between the body frame velocity and the integral form of gravity. The body frame velocity and the Earth frame position are separate treated, and the position alignment problem turns into an equation solving problem. No back tracking is needed. So the algorithm can be used in a real-time navigation system. The experiment results show that the alignment process could be finished in 300 s. After the alignment, the heading accuracy is better than 1 deg and the final position error could achieve 1.5% of the voyage distance.2) In the coordinate calibration part, by separately treating the body frame and the navigation frame attitude update, the algorithm does not require continuous attitude information. The algorithm could be simultaneously carried out during the INS attitude alignment stage. And the attitude information is only needed when the calibration is finished. So the calibration does not require additional time.3) The sparse velocity aided integrated navigation is studied in the third part. A continuous prediction process is used to obtain more accurate information in the nonlinear state equation. And the Unscented Kalman Filter (UKF) turns into a multi prediction one correction form. The new algorithm uses only 1/30 of the DVL’s information but the accuracy is still better than 1.2% of the voyage distance. So it can improve the concealment of the underwater equipment without losing position accuracy.4) MEMS inertial sensors based attitude sensor, which has the feature of anti-magnetic interference, is studied in the fourth part. A dual-axis rotation structure with a proper rotary scheme according to the design principles is applied in the system to compensate for the attitude and heading drift caused by the large gyroscope biases. An optimization algorithm is applied to compensate for the installation angle error between the body frame and the rotation table’s frame. Experimental results show that the attitude error is smaller than 3 deg under large magnetic interference environment.