IAE-adaptive Kalman filter for INS/GPS integrated navigation system

1 .INTRODUCTIONInertial navigation system(INS) and Global posi-tioning system ( GPS) are two major navigationsystems now widely usedfor marine applications a-round the world. Considering both systems pos-sess complementary working characteristics , abooming attention is focused on finding effectivemethods to combine the two different systems toconstituteintegrated navigation system with higheraccuracy and better performance .Information likeGPS position and velocity are often chosen as…     

Robust fault detection filter and its application in MEMS-based INS/GPS

Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems,it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose,this paper proposes a robust fault-detection filter for linear discrete time-varying systems.The algorithm uses H∞ estimator to minimize the worst possible amplification from disturbances to estimate errors,and H_ index to maximize the minimum effect of faults on the residual output of the filter.This approach is applied to the MEMS-based INS/GPS.And simulation results show that the new algorithm can reduce the effect of unknown disturbances and has a high sensitivity to faults.     

GPS/VISNAV integrated relative navigation and attitude determination system for ultra-close spacecraft formation flying

For the improvement of accuracy and better faulttolerant performance, a global position system (GPS)/vision navigation (VISNAV) integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying. Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design. Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.     

Novel approach to GPS/SINS integration for IMU alignment

Strapdown inertial navigation system(SINS) requires an initialization process that establishes the relationship between the body frame and the local geographic reference.This process,called alignment,is generally used to estimate the initial attitude angles.This is possible because an accurate determination of the inertial measurement unit(IMU) motion is available based on the measurement obtained from global position system(GPS).But the update frequency of GPS is much lower than SINS.Due to the non-synchronous data streams from GPS and SINS,the initial attitude angles may not be computed accurately enough.In addition,the estimated initial attitude angles may have relatively large uncertainties that can affect the accuracy of other navigation parameters.This paper presents an effective approach of matching the velocities which are provided by GPS and SINS.In this approach,a digital high-pass filter,which implements a pre-filtering scheme of the measured signal,is used to filter the Schuler cycle of discrete velocity difference between the SINS and GPS.Simulation results show that this approach improves the accuracy greatly and makes the convergence time satisfy the required accuracy.     

Analysis of unmanned aerial vehicle navigation and height control system based on GPS

According to the characteristic of global positioning system (GPS) reflection signals, a GPS delay mapping receiver system scheme is put forward, which not only satisfies the unmanned aerial vehicle (UAV) guidance localization but also realizes height measurement. A code delay algorithm is put forward, which processes the direct and land reflected signal and outputs the navigation data and specular point. The GPS terrain reflected echo signal mathematical equation is inferred. The reflecting signal area, when the GPS signal passes the land, is analyzed. The height survey model reflected land surface characteristic is established. A simulation system which carries guidance localization of the UAV and the height measuring control through the GPS direct signal and the land reflected signal is designed, taken the GPS satellite as the illumination source, the receiver is put on the UAV. Then the UAV guidance signal, the GPS reflection signal and receiver’s parallel processing are realized. The parallel processing reduces UAV’s payload and raises system’s operating efficiency. The simulation results confirms the validity of the model and also provides the basis for the UAV’s optimization design.     

基于神经网络的高超声速飞行器惯导系统精度提高方法

针对目前惯性系统误差补偿模型对静态误差和动态误差处理能力不足的问题,为适应高超声速飞行器长航时、高精度的惯性导航要求,基于神经网络提出一种加速度计拟合模型。在高超声速飞行器飞行前期有准确的卫星导航信息时,收集导航信息和加速度计脉冲信息,利用神经网络强大的非线性拟合能力,在飞行过程中进行在线训练,得到精确的惯性系统模型。仿真结果表明,在存在逐次通电误差和不考虑二次项误差系数的误差补偿模型方法位置导航偏差在数公里和数百米量级的情况下,相同时间内所提方法的位置导航偏差仅为数十米量级,有效提高了高超声速飞行器的导航精度。