车载GNSS失锁下基于BPNN的微陀螺误差估计及定位方法研究

Research on error estimation of micro-gyroscope and location method based on BPNN for vehicle during GNSS outages

针对在全球导航卫星系统(global navigation satellite system,GNSS)失锁阶段将微陀螺惯性系统作为备用定位系统时,由于微陀螺误差引起的定位误差发散问题,提出了基于后向传播神经网络(back propagation neural network,BPNN)的微陀螺误差估计及定位算法。在GNSS有效阶段为车辆提供定位信息,同时对微陀螺误差进行估计,并利用后向传播神经网络BPNN建立微陀螺误差预测模型,为GNSS失锁阶段车辆定位做准备;在GNSS失锁阶段,利用已建立好的微陀螺误差预测模型估计微陀螺误差,对微陀螺输出信息进行补偿,以抑制由陀螺误差引起的定位误差。最后利用仿真与试验验证了此方法的正确性与有效性。

In the global navigation satellite system(GNSS)outages phase,the micro-gyroscope inertial system is used as a standby positioning system.In order to solve the problem of positioning divergence error caused by micro-gyroscope error,the error estimation of the micro-gyroscope and location method based on back propagation neural network(BPNN)is proposed in this paper.In the GNSS effective phase,it provides positioning information for vehicles and estimates the micro-gyroscope error.A prediction model of micro-gyroscope error that is prepared for vehicle positioning in the GNSS outages phase is established by the BPNN.In the GNSS outages phase,the micro-gyroscope error prediction model is used to estimate the micro-gyroscope error and compensate the output information of the micro-gyroscope to suppress the positioning error caused by the gyroscope error.Finally,the correctness and effectiveness of this method is verified by simulation and experiment.