基于注意力机制的电磁时间序列异常检测方法

Anomaly detection method of electromagnetic time series based on attention mechanism

摘要:

实现电磁数据的异常检测和模式发现，对电磁目标异常行为的判断与提前预警具有重要价值。不同类型的电磁数据通常以时间序列的形式存在，且具有正常数据与异常数据不均衡等特点。为应对上述挑战，提出一种基于时空联合注意力机制的时间序列异常检测方法。基于电磁数据的时间与空间特征，结合通道与空间注意力机制，增强对时序数据异常部分的特征表示。实验结果表明，提出的检测算法能够有效应对数据不均衡的难点，具有较强的鲁棒性。

Abstract:

The realization of abnormal detection and pattern discovery of electromagnetic data is of great value to the judgment and early warning of abnormal behaviors of electromagnetic targets. Different types of electromagnetic data usually exist in the form of time series, with the characteristic of imbalance between normal data and abnormal data. To address these issues，a time series anomaly detection method is proposed based on the spatial-temporal joint attention mechanism. The channel attention mechanism and spatial attention mechanism are combined to enhance the feature representation of the abnormal part of time series data. Experimental results show that the proposed detection algorithm can effectively deal with the difficulty of data imbalance and has strong robustness.