摘要
建立了利用车辆内部传感器取代惯性敏感器获得航向、速度信息的车辆航位推算 (DR)系统的系统方程和观测方程 ,并采用描述机动载体运动的当前统计模型 ,给出了基于自适应卡尔曼滤波的车载无陀螺DR系统的导航算法 .在导航算法中 ,对原始测量数据进行组合运算获得线性形式的观测方程 ,避免了目前常用导航算法由于观测方程线性化引起的模型误差 ,算法稳定性较好 ,且计算量小 .现场跑车试验表明 。
Using internal sensors of vehicle instead of inertia sensor to get orientation/velocity information, the system/observation equations of vehicular dead reckoning (DR) navigation system are established. The current statistics model is introduced to describe the maneuvering vehicle kinematics, and then the navigation algorithm based on adaptive Kalman filter for DR system without gyroscope is proposed. By operating measured data synthetically, linear observation equation is obtained for the navigation algorithm. This approach avoids model error due to linearizing nonlinear observation equation in the conventional algorithm, so that the stability of navigation algorithm is improved and computation expenses are reduced. Field running experiments show that satisfactory accuracy can be obtained by the proposed navigation model and algorithm for the vehicular DR system without gyroscope.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2001年第12期1284-1287,共4页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目 (6 9775 0 12)