Fast and accurate relative attitude measurement is of great significance to aerospace and military equipment. The traditional inertial relative attitude measurement method uses the angular velocity output of two inertial devices to perform independent attitude integral calculation, which is inconvenient to introduce external observation, thus limiting the application scope of relative attitude measurement. An angular velocity differential relative attitude measurement method based on dual inertial devices is proposed, which uses two angular velocity outputs and the relative rotation matrix at the current moment to obtain the relative angular velocity at the current moment, and integrates to obtain the relative attitude of the measured object and the carrier. After 450s of relative attitude measurement experiments, the deviation between the method in this paper and the traditional method is 0.060°（1σ, pitch axis） and 0.015°（1σ, heading axis）, which is one order of magnitude smaller than the average inertial measurement error 0.510°（1σ, pitch axis） and 0.372°（1σ, heading axis）, and it can be considered that the attitude measurement accuracy of this method is equivalent to that of the traditional method. Compared with the traditional method, the angular velocity differential relative attitude measurement method proposed in this paper can be connected to the Kalman filter, which has higher precision in observed measurements, and is more suitable for engineering applications such as spacecraft space docking and helmet sights.
To improve the positioning accuracy and reliability of multi-sensor navigation system under urban canyon scenarios, a resilient interactive fusion method based on sensor-independent-update is proposed. The trust priority of navigation sensors is introduced into the information fusion in the form of transition probability matrix defined by Markov chain.The overall estimation is determined by the weighted sum of average from every filter estimate. This weight of every model is dynamic updated by the prior transition information and posterior model likelihood. The multi-sensor integration is implemented in state estimation domain enhanced by interactive information fusion rather than in measurement domain implemented in traditional filter method. The kinematic vehicle experiment in urban canyon environment verifies the superiority of the proposed method. The dynamic weights have the natural function of fault detection and exclusion without additional operations which is insensitive to sensor measurement noise and outliers. The effect of dynamic sensor selection is achieved in this processing.The same independent structure is also applied to adopt new available sensor to realize plug-and-play navigation. The proposed resilient navigation method shows better accuracy and reliability compared to classical Kalman filters.
Hemispherical resonant gyroscope（HRG） is a new type of Coriolis gyroscope with broad prospects for development. Due to the damping mismatch caused by the manufacturing process and assembly errors, the gyroscope has a lock-in effect when the rate input is small. Aiming at this problem, based on the dynamic model and signal processing model of the HRG, a method of virtual rotation to overcome the lock-in effect is proposed in this paper. Firstly, the lock-in effect of the HRG is analyzed. Secondly, the basic principle of virtual rotation method is introduced. Finally, the effectiveness of virtual rotation method on the lock-in effect is verified. The simulation results show that the pattern angle can track the rate input in real time which effectively overcomes the lock-in problem of the HRG after applying virtual rotation.
Aiming at the problem of poor positioning accuracy caused by satellite rejection for firefighters in the underground mine, tunnel, indoor and other rescue environments, a firefighter positioning method based on multiple sensors zero velocity update（ZUPT） is designed in this paper. This method is based on ZUPT of strapdown inertial navigation system（SINS）, magnetometer and altimeter as supplements for positioning, inertial sensor, magnetometer and altimeter are fixed to the shoes. According to the characteristic that the speed is basically zero when the sole of the firefighter fully contacts the ground in walking process, the navigation information output by SINS is corrected through Kalman filtering, which can realize the firefighter’s autonomous positioning in the beacon-free environment. The offline data is collected through semi-physical simulation experiments and the positioning results are calculated to verify the effectiveness of the algorithm, its error ratio does not exceed 1%D.
With the continuous improvement of the velocity and maneuverability of highly dynamic aircraft, the control system is faced with problems such as high nonlinearity, strong coupling, fast time variation, and uncertainty. In order to improve the control accuracy and stability of the high dynamic aircraft overload control system, the autopilot design scheme based on angular acceleration feedback is proposed, and the active disturbance rejection control（ADRC） system and its stability analysis method are designed. Firstly, the PI two-loop autopilot control system scheme based on angular velocity and angular acceleration feedback is designed. Secondly, the ADRC overload control method is designed based on angular acceleration feedback, and the frequency domain analysis of the system stability is performed. Finally, simulation experiments are carried out, and the results show that the performance of the control system with angular acceleration feedback is significantly better than that with angular velocity feedback for the traditional overload control with PI correction. Compared with the traditional overload control system with PI correction, the ADRC system can achieve better control effect, and significantly improves the stability and robustness of the system.
