Self-Calibration of Accelerometer Arrays
Self-Calibration of Accelerometer Arrays
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DOI：
10.1109/tim.2016.2549758
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发表时间：
2016-08-01
影响因子：
5.6
通讯作者：
Manoli, Yiannos
中科院分区：
文献类型：
--
作者：
Schopp, Patrick;Graf, Hagen;Manoli, Yiannos
无陀螺仪惯性测量单元仅采用加速度计来以其线加速度和角加速度以及其角速度的形式捕获物体的运动。为此，多个换能器被固定在身体的不同位置，它们一起形成加速度计阵列。为了准确地估计运动，传感器的姿态，即，它们的位置和方向必须精确地知道。不幸的是，这些参数通常很难评估。当前最先进的校准方法能够基于一组运动数据和对应的加速度测量来重建几何传感器配置。然而，要在传感器阵列上施加参考运动并以必要的精度捕获该运动，需要复杂的实验室设备。在本文中，我们提出了一种方法来估计传感器的姿态只使用自己的测量，而不依赖于参考运动数据。它是基于一个迭代的图形优化，认为传感器的姿势和运动作为目标变量。最初，这会产生无穷多个解。我们减少的解决方案，只有一个全球最优的明确建模所使用的三轴加速度传感器三元组，并进一步考虑到时间依赖性的加速度样本。我们比较我们的方法，传统的校准使用参考数据的估计精度。此外，我们分析了我们的方法的收敛性能，通过评估其公差的初始位姿偏差。对于这两个，我们使用合成和实验数据记录在一个3-D旋转表。
A gyroscope-free inertial measurement unit employs solely accelerometers to capture the motion of a body in the form of its linear and angular acceleration as well as its angular velocity. For that, multiple transducers are fixed at distinct locations of the body that together form an accelerometer array. To accurately estimate the motion, the poses of the sensors, i.e., their positions and orientations, must be known precisely. Unfortunately, these parameters are typically hard to assess. Current state-of-the-art calibration methods are able to reconstruct the geometrical sensor configuration based on a set of motion data and corresponding acceleration measurements. However, to impose a reference motion on the sensor array and to capture that motion with the necessary accuracy requires sophisticated laboratory equipment. In this paper, we present a method to estimate the transducer poses using only their own measurements without depending on reference motion data. It is based on an iterative graph optimization that considers both the sensor poses and the motion as target variables. Initially, this results in infinitely many solutions. We reduce the solutions to only one global optimum by explicitly modeling the used triple-axis accelerometers as sensor triads and furthermore taking the temporal dependence of the acceleration samples into account. We compare our method to the conventional calibration using reference data in terms of its estimation accuracy. Furthermore, we analyze the convergence properties of our method by evaluating its tolerance to initial pose deviations. For both, we use synthetic and experimental data recorded on a 3-D rotation table.