The inertial measurement unit (IMU) biases, DVL lever arm and installation misalignment angles between IMU and doppler velocity log (DVL) have a great influence on in-motion initial alignment for DVL-aided low-cost strap-down inertial navigation system (SINS). A new Kalman filter-based initial alignment method is proposed in this paper. To weaken the effects of IMU biases, DVL lever arm and installation misalignment angles between IMU and DVL, a closed-loop scheme is presented to simultaneous estimate and compensate these parameter errors and the body attitude matrix based on a linear state-space model, which improves the accuracy of vector observations. The constant matrix from initial body frame to initial navigation frame can be determined based on the vector observations by Davenport's q-method. Simulation results illustrate that, for the DVL-aided low-cost SINS, the alignment performance of the proposed initial alignment method is better than that of the compared initial alignment methods.

中文翻译：

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DVL辅助低成本SINS的基于卡尔曼滤波器的运动初始对准的新方法

惯性测量单元（IMU）偏置，DVL杠杆臂以及IMU和多普勒速度测井（DVL）之间的安装失准角对DVL辅助的低成本捷联惯性导航系统（SINS）的运动初始对准有很大影响）。提出了一种新的基于卡尔曼滤波的初始对准方法。为了减弱IMU偏置，DVL杠杆臂以及IMU和DVL之间的安装失准角的影响，提出了一种闭环方案，以基于线性状态空间模型同时估计和补偿这些参数误差和身体姿势矩阵，该方法提高矢量观测的准确性。可以根据Davenport的q方法的矢量观测值确定从初始车身框架到初始导航框架的常数矩阵。仿真结果表明，