40 years of sensor fusion for orientation tracking via magnetic and inertial measurement units: Methods, lessons learned, and future challenges

Mooring alignment for marine SINS using the digital filter

Proceeding from actual needs of AINS initial alignment technology, this paper is specific to rigidity carrier ship, and it deduces the model equations of Airborne Inertial Navigation System's velocity and acceleration (ecificforce) with the effect of arm-lever vector. It employs the method that establishes large initial misalignment angle transfer alignment model of AINS, which is other than traditional velocity and attitude matching algorithm. Basing on nonlinear deterministic particle filtering, it simulates the performance of the model with experimental data, and comparatively studies inhering lever-arm vector error's influence on AINS misalignment attitude angle estimation error and its alignment accuracy. With different initial lever-arm vectors it researches its effects on misalignment attitude angle's estimation error and the accuracy of transfer alignment. The simulation results verify the model's validity and its superior alignment accuracy in transfer alignment of AINS. It is of great theory and application value in design of AINS.

The Impact of Arm-Lever Effect Error Based Large Initial Misalignment Transfer Alignment Technology Study

Aiming at transfer alignment of gimbaled inertial navigation systems (INS) on a moving base, we propose an attitude matching alignment model to align the attitude of the slave platform. This method is achieved by applying an unscented Kalman filter to estimate the fixed misalignment angle, and the misalignment angle can be obtained only with attitude maneuvers, which are very easy for the ship to implement. Firstly, the frame dynamics equations are introduced. Then, frame angular error differential equations, which include the ship-body flexure and other alignment errors, are set up via the frame angle information from the master and the slave INS platform. With these frameworks, the nonlinear attitude matching alignment model is designed based on unscented Kalman filter technology. The simulation results show that the proposed method can obtain an alignment to an accuracy of 1.50 and alignment time of 50 sections.

Novel Transfer Alignment of Shipborne Gimbaled Inertial Navigation Systems

The monocular visual odometer is widely used in the navigation of robots and vehicles, but it has defects of the unknown scale of the estimated trajectory. In this paper, we presented a position and attitude estimation method, integrating the visual odometer and Global Position System (GPS), where the GPS positioning results were taken as a reference to minimize the trajectory estimation error of visual odometer and derive the attitude of the vehicle. Hardware-in-the-loop simulations were carried out; the experimental results showed that the positioning error of the proposed method was less than 1 m, and the accuracy and robustness of the attitude estimation results were better than those of the state-of-art vision-based attitude estimation methods.

https://www.mdpi.com/1424-8220/20/7/2121/pdf

Position and Attitude Estimation Method Integrating Visual Odometer and GPS.

This paper proposes an approach to update the attitude and velocity synchronously utilizing the fourth order Runge-Kutta in the strapdown inertial navigation system. The synchro-updating algorithm is designed for the condition, in which the outputs of gyroscope are the angular rate and the outputs of accelerometer are the specific force acceleration. The synchro-updating algorithm is based on the quaternion. Under the improved classical coning motion and the generalized vibrational motion respectively, this paper analyzes and compares the attitude error and velocity error of the above algorithm with other algorithms'. The simulation results show that the synchro-updating algorithm is more effective than the others for the angular rate outputs and the specific force outputs.

Study of strapdown inertial navigation integration algorithms

Transfer alignment provides a rapid and effective way how to align and calibrate an inertial navigation system (INS) using the accurate information of other INS. However, in the previous literatures, it is found that not every transfer alignment algorithm is efficient in any environments. In this paper, the conventional velocity matching algorithm and the rapid velocity and attitude matching algorithm are compared in several typical environments by observability analysis. It is explained in theory, in this paper, why the velocity matching algorithm could estimate azimuth misalignment under constant velocity maneuver, but the velocity and attitude matching algorithm could not. At the same time, this paper analyzes the influence of sway and acceleration maneuvers to improve the observability of the two transfer alignment algorithms. Since GPS can provide the velocity and attitude information of vehicle, the accurate information used in transfer alignment can be replaced by the corresponding information from GPS in order to reduce the cost. However, the errors of velocity and attitude provided by GPS are larger than by accurate INS. So the estimation errors caused by external sensor errors must be considered if using GPS as the external sensor. At the end of this paper, the estimation errors of azimuth angle of the two algorithms due to the unobservable states and the errors of external sensor are deduced using the control- theoretic approach and proved by simulation, respectively.

http://ieeexplore.ieee.org/iel5/10978/34615/01650680.pdf

Wei Gao

Papers

Study of strapdown inertial navigation integration algorithms

Comparison of INS Transfer Alignments through Observability Analysis