利用隐藏对称性实现对物体的定位、识别与传感。
Target localization, identification and sensing using latent symmetries
- 通过分析散射体阵列对称性被破坏程度来探测入侵物。
- 在有测量噪声时，神经网络比字典法表现更优。
- 首次在三维开放系统中成功应用隐藏对称性传感。
我们证明，设计具有隐藏对称性的散射体阵列可作为传感器使用。以电容矩阵为三维耦合的典型模型，研究入侵散射体如何破坏这些隐藏对称性。通过分析各对称性被破坏的程度，可识别入侵物半径并定位其位置。虽然可用字典法实现，但在存在测量噪声时，贝叶斯推断或多层感知机（MLP）表现更佳。据我们所知，这是首次成功将隐藏对称性应用于传感问题，也是首次在无法用稀疏图近似的三维开放系统中观测到此类对称性。
原文摘要 · Abstract (English)
We show that an array of scatterers which has been designed to have latent ("hidden") symmetries can be used as a sensor. We use the capacitance matrix as a canonical model for three-dimensional hybridisation and study how the introduction of an "intruder'' scatterer breaks the latent symmetries. By analysing the degree to which each symmetry is broken, we identify the radius of the intruder and localize its position. This can be achieved using a dictionary-based approach, however Bayesian inference or an artificial neural network (multi-layer perceptron) perform better in the presence of measurement noise. To our knowledge, this is the first time latent symmetries have been exploited successfully for sensing problems. It is also the first time latent symmetries have been observed in a three-dimensional open system that cannot be approximated by a sparse graph.
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