Algorithms For BD/MIMU Integrated Navigation Systems

Methods and application technology for BD/MIMU integrated navigation have been an attractive research with the developments of Beidou satellites navigation system in China and inertial navigation technology and our army in urgent need of technology for guided munitions. This thesis proposes a BD/MIMU integrated navigation system using the concept of software based receiver technique, studies on tightly and deeply integrated frames and related optimization technologies. Some major theoretic problems and related key technologies are researched. The main contributions include the following aspects:1. Considering the motion dependence of SINS performance, performance matching between software based receiver and SINS is analysed in theory. BD-2/SINS integration frame is established based on software based receiver. The principle of SINS aided satellites signal acquisition is presented and the influences factors are summarized detail by detail. The equations of performances between BD-2 receivers and SINS are induced using SINS velocity errors equations. Performance analysis of SINS aided acquisition based on motion dependence of SINS is evaluated in the high dynamic situation. Simulation experiments illustrate that aided acquisition method with SINS composed of 100 deg/h bias drift MEMS gyros and 1 mg bias drift MEMS accelerometers can enhance the sensitivity of probability of detection up to 4.2 dB-Hz compared with unaided acquisition.2. A BD-2/MIMU tight integration algorithm based on software based receivers is proposed. The minimal GDOP value in theory which is a token of GNSS satellites distribution conditions is proved and GDOP comparison of BD-2 and GPS is analysed. A MIMU-aided rapid satellite selection algorithm in application to high dynamic conditions is proposed and its validity is proved by experimental results. The optimal loop bandwidth of MIMU-aided PLL was designed in the tightly integrated navigation algorithm based on a 3rd order PLL with 3 Hz loop bandwidth. In order to overcome the outages of satellites signals, an ANFIS aided KF tightly integrated algorithm is provided and experiments illustrate that the new algorithm can improve the performance of integrated system effectively and enhance the position accuracy even with 100 s outages of satellites signals.3. A BD-2/MIMU deep integration algorithm based on software based receivers is presented. The principle of seimparametric regression model and penalized lest square method are introduced, and the choices of regular matrix and smoothing factor are discussed. Based on temperature compensation model of MEMS gyro, a seimparametric regression model of systemic errors compensation during the process of start-up is proposed to improve the performance of MEMS gyro accuracy. A gyro de-noising algorithm based on extended Recursive Least Square with AR(2) model are used to compensate gyro random drifts and related experiments prove the feasibility and effectiveness of new algorithms. Deep integration is discussed and filters are designed using cascading filtering technology. Vector-tracking structure is adopted and a seimparametric regression model for the pre-processing function of baseband signals is also researched to improve the performance of signals pre-processing.4. A BD-2/MIMU integrated navigation system based on software based recerivers is set up. Test methods are designed with real high dynamic flight data grounded on conditions of our lab and BD signals simulator. Satellites signals acquisition tests are carried out and signals can acquisited successfully using 5 ms pre-detection integration time. Tighly integrated method and deeply integrated method are applied to this BD-2/MIMU navigation system. The test results show that two methods are feasible and the positioning accuracy is better than 6 m and velocity accuracy is better than 0.15 m/s, the horizontal attitude accuracy is better than 0.4 degrees and the yaw accuracy is better than 0.5 degrees.5. A BD-1/SINS integrated navigation system is presented. A back-propagation neural network aided KF algorithm is proposed in order to overcome the time delay of BD-1 positioning. The algorithm has been verified on real data collected in land vehicle tests and is compared with other approaches, especially with the outages of satellites signals. The results demonstrate that the new algorithm improves the horizontal positioning accuracy with better than 50 m.