Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units

The strapdown fiber optic gyrocompass (strapdown FOGC) system for ships primarily works on external horizontal damping and undamping statuses. When there are large sea condition changes, the system will switch frequently between the external horizontal damping status and the undamping status. This means that the system is always in an adjustment status and influences the dynamic accuracy of the system. Aiming at the limitations of the conventional damping method, a new design idea is proposed, where the adaptive control method is used to design the horizontal damping network of the strapdown FOGC system. According to the size of acceleration, the parameters of the damping network are changed to make the system error caused by the ship’s maneuvering to a minimum. Furthermore, the jump in damping coefficient was transformed into gradual change to make a smooth system status switch. The adaptive damping network was applied for strapdown FOGC under the static and dynamic condition, and its performance was compared with the conventional damping, and undamping means. Experimental results showed that the adaptive damping network was effective in improving the dynamic performance of the strapdown FOGC.

Section: Resultsmentioning

confidence: 99%

Section: Design Of the Adaptive Damping Networkmentioning

confidence: 99%

An Adaptive Damping Network Designed for Strapdown Fiber Optic Gyrocompass System for Ships

Sun

Liu

et al. 2017

“…Gao et al [ 27 ] and Liu et al [ 31 ] proposed methods to compensate the size effect and the lever arm effect, respectively. As for the turntable rotation strategy, the 6-position [ 22 ], 9-position [ 24 , 32 ], 18-position [ 18 , 34 ], and 24-position [ 35 ] methods have been proposed. In existing works, calibration methods are rarely designed for the space-stable INSs.…”

Section: Introductionmentioning

confidence: 99%

A Three-Stage Accelerometer Self-Calibration Technique for Space-Stable Inertial Navigation Systems

Han

et al. 2018

As a specific force sensor, the tri-axis accelerometer is one of the core instruments in an inertial navigation system (INS). During navigation, its measurement error directly induces constant or alternating navigation errors of the same order of magnitude. Moreover, it also affects the estimation accuracy of gyro drift coefficients during the initial alignment and calibration, which will indirectly result in navigation errors accumulating over time. Calibration can effectively improve measurement accuracy of the accelerometer. Device-level calibration can identify all of the parameters in the error model, and the system-level calibration can accurately estimate part of these parameters. Combining the advantages of both the methods and making full use of the precise angulation of the space-stabilized platform, this paper proposes a three-stage accelerometer self-calibration technique that can be implemented directly in the space-stable INS. The device-level calibration is divided into two steps considering the large amount of parameters. The first step is coarse calibration, which identifies parameters except for the nonlinear terms, and the second step is fine calibration, which not only identifies the nonlinear parameters, but also improves the accuracy of the parameters identified in the first step. The follow-on system-level calibration is carried out on part of the parameters using specific force error and attitude error to further improve the calibration accuracy. Simulation result shows that by using the proposed three-stage calibration technique in the space-stable INS, the estimation accuracy of accelerometer error can reach 1×10−6 normalg order of magnitude. Experiment results show that after the three-stage calibration, the accuracy of latitude, longitude, and attitude angles has increased by over 45% and the accuracy of velocity has increased by over 22% during navigation.

“…In order to improve navigation accuracy, the error parameters of an INS should be accurately calibrated before its official use. The commonly used laboratory calibration methods are the multi-position method and its various improved methods [ 6 , 7 , 8 ]. However, when an INS works in a real dynamic environment, particularly for aircraft or other high maneuverability carriers, there always exist enormous differences between the real work and laboratory test environments.…”

Section: Introductionmentioning

confidence: 99%

High-Accuracy Decoupling Estimation of the Systematic Coordinate Errors of an INS and Intensified High Dynamic Star Tracker Based on the Constrained Least Squares Method

Jiang

Zhang

2017

Navigation accuracy is one of the key performance indicators of an inertial navigation system (INS). Requirements for an accuracy assessment of an INS in a real work environment are exceedingly urgent because of enormous differences between real work and laboratory test environments. An attitude accuracy assessment of an INS based on the intensified high dynamic star tracker (IHDST) is particularly suitable for a real complex dynamic environment. However, the coupled systematic coordinate errors of an INS and the IHDST severely decrease the attitude assessment accuracy of an INS. Given that, a high-accuracy decoupling estimation method of the above systematic coordinate errors based on the constrained least squares (CLS) method is proposed in this paper. The reference frame of the IHDST is firstly converted to be consistent with that of the INS because their reference frames are completely different. Thereafter, the decoupling estimation model of the systematic coordinate errors is established and the CLS-based optimization method is utilized to estimate errors accurately. After compensating for error, the attitude accuracy of an INS can be assessed based on IHDST accurately. Both simulated experiments and real flight experiments of aircraft are conducted, and the experimental results demonstrate that the proposed method is effective and shows excellent performance for the attitude accuracy assessment of an INS in a real work environment.