基于多状态卡尔曼滤波的双目视觉导航设计  

Design of Binocular Vision Navigation Based on Multi-State Kalman Filter

作　　者：赵中堂[1] 吴庆涛[1] ZHAO Zhongtang;WU Qingtao(School of Intelligent Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450015, China)

机构地区：[1]郑州航空工业管理学院智能工程学院,郑州450015

出　　处：《兵器装备工程学报》2020年第6期169-173,共5页Journal of Ordnance Equipment Engineering

基　　金：国家自然科学基金项目(U1504609);河南省高等教育教学改革研究与实践一般项目(2017SJGLX400)。

摘　　要：提出了一种改进的多状态约束卡尔曼滤波器(IMSCKF)双目视觉惯性导航算法。该算法在初始阶段采用Sigma滤波器和三焦点张量约束快速完成初始化,产生的状态向量与MSCKF一致,可以实现初始化和后续导航之间的无缝过渡,提高了系统状态估计的精度和鲁棒性。实验结果表明,本文提出的IMSCKF方法位置跟踪误差维持在±1 mm,角度误差维持在±1°,可以提高双目视觉惯性导航的鲁棒性和精度。We proposed an improved multi state constrained Kalman filter(IMSCKF)algorithm for binocular vision inertial navigation.In the initial stage,the algorithm uses sigma filter and three focus tensor constraints to complete the initialization quickly.The generated state vector is consistent with MSCKF,which can realize the seamless transition between initialization and subsequent navigation,and improve the accuracy and robustness of system state estimation.The experimental results show that the IMSCKF method proposed in this paper can maintain the position tracking error in±1 mm range and the angular error in±1°,which can improve the robustness and accuracy of binocular vision inertial navigation.

关 键 词：轨迹跟踪 多状态约束卡尔曼滤波器 三焦点张量 sigma滤波器 

分 类 号：TJ02[兵器科学与技术—兵器发射理论与技术]