Research And Implementation Of Error Calibration And Temperature-induced-error Compensation Technique For The FOG IMU

In stapdown inertial navigation system (SINS) based on fiber optic gyroscope (FOG), the error of FOG Inertial Measurement Unit (IMU) has an important effect on the precision of navigation system. After analyzing the IMU error model, the error parameters can be calculated by the error compensation algorithm, and the performance of navigation system can be greatly improved by error compensation in the process of navigation solution.On the basis of studying the FOG national military standard (NMS), the classification, meaning and test method of FOG's major performance index is generalized. Besides, the actual FOG's performance test is done in detail, and the test can provide not only theoretical basis but also lots of test data for error calibration and temperature-induced-error compensation technique for FOG IMU.For the reason that the expandability of the conventional algorithm was weak, and also the redundant calibration data can't be made full use of, a calibration algorithm called multi-position fusion algorithm (MPFA) is brought forward; For the bias of FOG can't be identified by the conventional method of angular velocity calibration, and the output of FOG is effected by temperature fluctuation, a new calibration algorithm called adaptive recursive least square (ARLS) is brought forward. Meanwhile, combining the calibration algorithms above with development technology of computer software, a set of calibration software for FOG SINS is developed by VC.For the purpose of reducing the temperature-induced drift and improving the precision of FOG, the technique of compensating the FOG's temperature drift is studied by the static temperature test. On the one hand, the temperature error compensation based on polynomial approximation method is studied, and the model of the temperature-induced drift for FOG is established; On the other hand, on the basis of improving the conventional algorithm of BP neural network, the improved algorithm is used for identifying the temperature-induced drift of FOG. And the validity of the above temperature error compensation algorithm is demonstrated by the temperature test.Finally, by static and rotary tests of the actual FOG SINS, it is approved that the technique of error calibration and temperature-induced-error compensation for FOG IMU, can effectively improve the precision of the navigation system, and has important value in engineering application.