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Optimal input design for multi UAVs formation anomaly detection

机译:多维无人机形成异常检测的最佳输入设计

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摘要

As the input signal must be informative enough, so that the resulting dataset is enough informative to excite the identification experiment for multi UAV5 formation anomaly detection. Based on our previous work on multi UAV5 formation anomaly detection, the optimal input signals are designed for two identification strategies, i.e. least squares estimation and improved sparse estimation. Using the variance of the asymptotic distribution corresponding to the unknown parameters, the common trace operation is chosen to construct one numerical optimization problem, whose solution is corresponded to the optimal power spectral. After giving the detailed minimization process, we see that the power spectral corresponding to the optimal input signal is a constant. In addition, for the sake of completeness, one dynamic programming technique in multi UAVs formation anomaly detection is added to complete our early research. Finally, one numerical example illustrates the effectiveness of our proposed theories. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.
机译:由于输入信号必须足够提供信息,因此所得到的数据集足够提供信息来激发多UAV5形成异常检测的识别实验。基于我们之前的多UAV5形成异常检测的工作,最佳输入信号被设计用于两个识别策略,即最小二乘估计和改进的稀疏估计。使用对应于未知参数的渐近分布的方差,选择公共跟踪操作来构建一个数值优化问题,其解决方案对应于最佳功率谱。在提供详细的最小化过程之后,我们看到对应于最佳输入信号的功率谱是恒定的。此外,为了完整性,添加了一个多无人机地层形成异常检测中的动态编程技术以完成我们的早期研究。最后,一个数值示例说明了我们所提出的理论的有效性。 (c)2019 ISA。 elsevier有限公司出版。保留所有权利。

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