基于微惯性器件的头部运动综合测量方法研究

摘要

针对运动平台上头部姿态测量问题,提出一种可以获得更快测量速度、更高测量精度的综合测量方法.通过卡尔曼滤波将分别由视觉测量和微惯性测量得到的头部姿态数据进行数据融合.利用视觉测量对微惯性测量进行校正,综合了视觉测量方法误差不随时间变化与微惯性测量方法测量速度快、测量范围大的优点,抑制了惯性测量随时间累积产生的无约束发散误差,克服了视觉测量方法范围受限、容易受到干扰的缺点,并经过试验分析与仿真,得到了验证.%Aiming at head posture measurement on the moving platform, an integrated measurement method with faster measuring speed and higher accuracy is put forward.The head posture data obtained respectively by Vision Measurement (VM) and Inertial Measurement (IM) are fused by using the Kalman filter, and the data from the inertial pose measurement is revised by using the vision pose measurement.Therefore, the advantages of VM that the error is not changed with time, and of IM of fast measuring speed and large measuring scope are integrated; while the disadvantage of IM of unlimited and distributed error is restrained, and the shortcomings of VM such as limited measurement range, easily being disturbed, etc., are overcome.Experimental analysis and simulation results have proved the validity of the method.