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应用先进传感器与演算法於低成本运动追踪

消耗积分:0 | 格式:rar | 大小:0.28 MB | 2017-06-08

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  应用先进传感器与演算法於低成本运动追踪

  高性能的运动跟踪技术已经从深奥的军事,航空电子设备,海洋和工业应用到消费应用范围扩大。尽管如此,将高性能的运动跟踪到消费市场,往往迫使设计师调和冲突的目标,特别是相对于成本,功耗和计算资源。

  然而,由于MEMS设计和制造工艺的进步,新一代的惯性测量单元(IMU)是帮助设计人员提供更高的性能水平,用更少的妥协。

  本文将概述的设计问题和权衡之前引入一个新的六轴IMU承诺卸载计算密集型操作从主机处理器。它也将讨论新的计算分区策略,帮助设计师实现更高水平的运动跟踪精度显着降低系统的功率电平。最后,新的最优估计算法和开发工具包,将允许开发人员建立更高效的传感器融合解决方案将被讨论。

  应用先进传感器与演算法於低成本运动追踪

  The sensor performance tradeoffs

  As is typical, consumer devices must be optimized for low cost. Traditionally, designers of consumer systems using MEMS motion sensing have opted to stream accelerometer and gyroscope samples from the IMU to the applications processor (AP) or sensor hub controller, before performing further processing on the data.

  However, precision motion tracking requires significant computational resources to perform sensor fusion with currently available 6 and 9-axis IMUs. In these applications, designers must support sampling rates of at least several hundred hertz or more. Designers have struggled to deliver that high level of performance at low cost, without overloading the system processor and undermining the user experience.

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