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Comparison of quantized state estimators with different transmitted information forms

机译:具有不同传输信息形式的量化状态估计器的比较

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Bandwidth limitation is an unavoidable constraint when data is transmitted from local sensor to the estimation center in networked systems. As a result, quantization strategy is often used to deal with this constraint during the design of networked state estimators. In this paper, we compare the performance of three quantized estimators with different transmitted data forms, such as the original measurement, the innovation and the local estimation. Firstly, adaptive bit quantization is introduced to deal with the bandwidth limitation constraint. Secondly, three quantized state estimators are introduced. Actually, they adopt the same quantizing strategy. Intervals and common variance upper approximation method are also used. Thirdly, we compare estimation accuracies of the three quantized estimators by using their estimation error co-variances. Finally, a simple simulation is demonstrated to validate the conclusion in our comparison. The results show that these three quantized filters have very similar estimation accuracy.
机译:当数据从本地传感器传输到网络系统中的估计中心时,带宽限制是不可避免的约束。结果,在网络状态估计器的设计过程中,经常使用量化策略来处理此约束。在本文中,我们比较了三种量化估计器在不同传输数据形式下的性能,例如原始度量,创新和局部估计。首先,引入自适应比特量化来处理带宽限制约束。其次,介绍了三种量化状态估计器。实际上,它们采用相同的量化策略。还使用时间间隔和公共方差上限近似方法。第三,我们通过使用三个量化估计量的估计误差协方差来比较它们的估计准确性。最后,在我们的比较中,演示了一个简单的仿真来验证结论。结果表明,这三个量化滤波器具有非常相似的估计精度。

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