一种车辆模型辅助的MEMS-SINS导航方法

发布时间：2018-04-15 19:20

  本文选题：MEMS-SINS + ABS轮速传感器　； 参考：《中国惯性技术学报》2017年02期

【摘要】：针对城市环境中GNSS因遮挡导致MEMS-SINS精度快速降低的问题,在车辆运动学约束的基础上,结合四通道ABS轮速传感器和方向盘转角信息,提出一种新的适用于陆地车辆的MEMS-SINS导航方法。该方法通过分析车辆转弯和运动约束特性,构建角速度和加速度观测量,从而实现基于模型辅助的MEMS误差在线补偿;其次,ABS轮速信息与非完整约束条件结合可额外增加三维车体速度观测量,进一步维持卫星失效时组合滤波器的量测更新。跑车实验表明,在GNSS信号频繁丢失甚至长时间无法定位时,低精度MEMS惯性器件引起的快速误差积累得到有效抑制,与经典车体约束结合里程计算法相比,航向精度提高约70%,位置、速度精度也有相应的提高,验证了算法的有效性。
[Abstract]:In order to solve the problem of fast reduction of MEMS-SINS precision caused by GNSS occlusion in urban environment, a new MEMS-SINS navigation method suitable for land vehicles is proposed based on the kinematics constraints of vehicle and the information of four-channel ABS wheel speed sensor and steering wheel rotation angle.Based on the analysis of vehicle turning and motion constraint characteristics, the angular velocity and acceleration measurements are constructed, and the on-line compensation of MEMS error based on model is realized.Secondly, the combination of ABS wheel speed information and nonholonomic constraints can increase the three-dimensional vehicle body velocity observation, and further maintain the measurement update of the combined filter when the satellite fails.Sports car experiments show that the fast error accumulation caused by low precision MEMS inertial devices is effectively suppressed when the GNSS signal is lost frequently or even can not be located for a long time, which is compared with the classical car body constraint combined with mileage calculation method.The accuracy of heading is improved by about 70, and the accuracy of position and velocity is improved accordingly, which verifies the validity of the algorithm.
【作者单位】： 北京理工大学自动化学院;
【基金】：国家自然科学基金面上项目(61173076,61473042);国家自然科学基金重大研究计划培育项目(91120003)
【分类号】：U463.67;U495
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本文编号：1755439