Rongbing Li

Optimization method of MEMS IMU/LADAR integrated navigation system based on Compressed-EKF

Micro-electromechanical Systems (MEMS) IMU/ LADAR integrated navigation is a new-type autonomous navigation and environment detection method. It has a broad application prospect in the indoor environment. In MEMS IMU/LADAR integrated navigation system, the MEMS inertial sensors are used to measure vehicle movement. The LADAR is used to detect environmental features, and their outputs are fused by a digital filter, to provide precise position and environment mapping information for small rotorcraft. However, with the increasing amounts of observed landmarks, the computation complexity of traditional Extended Kalman Filter (EKF) increase excessively, making it unable to meet the realtime navigation requirement for small rotorcraft. In addition, the existing LADAR is generally planar scanning radar. When the aircrafts attitudes change, there is no guarantee that detecting plane maintains in a horizontal plane. This makes detecting information couple attitude angle measurement errors, and would bring great errors to the integrated navigation results. According to the problems mentioned above, the paper proposes the LADARs attitude angle coupling error compensation algorithm. The navigation filter is designed based on Compressed-EKF(CEKF) algorithm. And the experimental prototype is designed for MEMS IMU/LADAR integrated navigation system, to verify CEKF algorithm in indoor environment. The tests show that the proposed algorithm can effectively improve the LADARs precision and decrease the calculation amount of filtering algorithm. The research has significant reference value for small rotorcrafts simultaneous location and mapping (SLAM) technology in the structured indoor environment.

The Acceleration Sensitive Coefficient Calibration of the Crystal Oscillator Based on the GPS Carrier Control Principle

In acceleration and vibration environment, to weaken frequency instability influence of the crystal oscillator on GPS carrier loop and rectify frequency compensation, researchers usually adopt the solution of crystal oscillator frequency acceleration compensation. The vital basis of compensating frequency errors is how to obtain accurately corresponding sensitive parameters of crystal oscillator. In the traditional calibration approach of acceleration sensitivity coefficient, indispensably using precise frequency reference and measurement equipment makes the calibration process expensive and complex, that fails to be widely applied in GPS navigation system. Combined a precise frequency reference of GPS satellites with the carrier tracking loop principle, the paper analyzes the acceleration frequency errors transmission mechanism of crystal oscillator in the carrier tracking loop, and designs an adaptive weighted EKF to handle frequency bias observed values synchronously in multiple tracking loops, which reduces frequency bias estimating noise and separates frequency offset and frequency drift rate, from the receiver’s frequency bias observation in the crystal oscillator. And on this basis, acceleration sensitivity coefficients of crystal oscillator calibrate on the super tight combination navigation board by 2g flipping calibration method. The experiments show that the method is able to effectively calibrate acceleration sensitivity coefficients of crystal oscillator, which is the solution base of compensating crystal oscillator acceleration frequency errors on related GPS technology research.

SINS/GPS/CNS information fusion system based on improved Huber filter with classified adaptive factors for high-speed UAVs

For High-speed UAV, the measurement noise of GPS and star sensor show non-Gaussian characteristics in high-dynamic and high speed flight. In order to improve the system performance in the above situation, this paper presents an INS/GPS/CNS integrated navigation system and builds the asynchronous measurement model. The system measurement noise feature has also been analyzed according to a perturbed Gaussian mode. Furthermore, this paper designs an integrated navigation algorithm based on improved Huber filter with classified adaptive factors (CAHF), which could improve the precision of position, velocity and attitude in the condition of perturbed measurement noise. Simulation cases involving both CAHF and Kalman Filter are provided to validate the advantage of CAHF.

Research on multi-sensor information fusion system application for UAVS with long range and high altitude

Multi-sensors combination is an effective means to improve the accuracy and fault tolerance of the navigation system for UAVs with long range and high altitude. Based on analyses of attitude determination using STAR sensor, this paper presents a SINS/STAR/GPS information fusion navigation system. To solve the problem of the incoordinate interval characteristics of multi-sensors, an asynchronous centralized Kalman Filter (AKF) is designed., and the filter period is divided to time update period and measurement update period. An extrapolation method is designed to deal with GPS information. Moreover, a new model is designed to solve the problem of attitude combination in process of vertical mobility. Simulation results indicate that filtering accuracy is improved by 50% with the Kalman Filter, and the method is of important value in engineering application

Calculation method for air data based on information from inertial navigation system and wind field

Aiming at air data measuring under high altitude, high mobility and high velocity for aerospace vehicles, a calculation method for air data based on information from inertial navigation system and wind field is proposed. This algorithm provides indirect measurements of air data without requiring extra hardware. On the base of the turbulence model (Dryden model), time domain model of turbulence is established from temporal spectrum. Exploiting the wind speed from the weather forecast, the mathematic relationship between INS, wind field and air data (including true air speed, angle of sideslip, and angle of attack) is established. Real-time estimation of air data is achieved using EKF. The simulation results show that, this method not only has high precision, favorable stability and robustness, but also improves the measurement range and reliability of air data system, which can effectively be used to measure the angle of attack, the angle of sideslip and true airspeed within full flight envelope.