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Optimal Design Based on Closed-Loop Fusion for Velocity Bandwidth Expansion of Optical Target Tracking System

机译:基于闭环融合的光学目标跟踪系统速度带宽扩展优化设计

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摘要

Micro-electro-mechanical system (MEMS) gyro is one of the extensively used inertia sensors in the field of optical target tracking (OTT). However, velocity closed-loop bandwidth of the OTT system is limited due to the resonance and measurement range issues of MEMS gyro. In this paper, the generalized sensor fusion framework, named the closed-loop fusion (CLF), is analyzed, and the optimal design principle of filter is proposed in detail in order to improve measurement of the bandwidth of MEMS gyro by integrating information of MEMS accelerometers. The fusion error optimization problem, which is the core issue of fusion design, can be solved better through the feedback compensation law of CLF framework and fusion filter optimal design. Differently from conventional methods, the fusion filter of CLF can be simply and accurately designed, and the determination of superposition of fusion information can also be effectively avoided. To show the validity of the proposed method, both sensor fusion simulations and closed-loop experiments of optical target tracking system have yielded excellent results.
机译:微机电系统(MEMS)陀螺仪是光学目标跟踪(OTT)领域中广泛使用的惯性传感器之一。然而,由于MEMS陀螺仪的共振和测量范围问题,OTT系统的速度闭环带宽受到限制。本文分析了通用传感器融合框架,即闭环融合(CLF),并详细提出了滤波器的最佳设计原理,以通过集成MEMS信息来改善对MEMS陀螺仪带宽的测量。加速度计。融合误差优化问题是融合设计的核心问题,可以通过CLF框架的反馈补偿律和融合滤波器的优化设计更好地解决。与传统方法不同,可以简单,准确地设计CLF的融合滤波器,并且还可以有效地避免确定融合信息的重叠。为了证明该方法的有效性,传感器融合仿真和光学目标跟踪系统的闭环实验均取得了优异的效果。

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