Identification Approach of Arriving Wave Model Based on Likelihood Ratio Test With Different Sensor Noise Levels
Identification Approach of Arriving Wave Model Based on Likelihood Ratio Test With Different Sensor Noise Levels
复制标题
不同传感器噪声水平下基于似然比检验的到达波模型识别方法
DOI：
10.1029/2022rs007427
复制
发表时间：
2022
期刊：
影响因子：
1.6
通讯作者：
Kasahara Yoshiya
中科院分区：
文献类型：
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作者：
Tanaka Yuji;Ota Mamoru;Kasahara Yoshiya
由传播特性决定的k矢量方向对于理解空间等离子体的整体特征至关重要。在各种等离子体波测向中，确定到达波模型是获得快速准确结果的一个重要因素。如果我们能确定观测数据是否包含明显的自然波，我们可以通过排除纯噪声数据来减少测向分析的计算时间。传统的识别到达波模型的方法假定所有电磁场传感器具有相同的噪声级。然而，科学卫星上的电磁场传感器在长期运行过程中，会由于传感器的退化而产生噪声水平的变化。因此，即使在所有电磁场传感器的噪声级不相等的情况下，也应识别出到达的波模型。我们提出通过引入包含噪声级比信息的噪声积分核来鲁棒识别到达波模型。我们提出的方法将谱矩阵分为三种情况：噪声模型、单平面波模型和多波模型。该方法包括似然比检验和基于统计观点的识别结果。通过蒙特卡罗仿真，验证了该方法在不同传感器噪声水平下也能准确地推导出到达波模型。
K-vector direction determined by propagation characteristics is crucial for understanding the global features of space plasma. Identifying the arriving wave model is a major factor in obtaining fast and accurate results in the direction finding of various plasma waves. If we can determine whether the observation data contain a significant natural wave or not, we can reduce the computational time for direction finding analysis by excluding noise-only data. The conventional approach for identifying the arriving wave model assumes that all electromagnetic field sensors have same noise levels. However, the noise levels of electromagnetic field sensors on board scientific satellites can change owing to sensor degradation during long-term instrument operation. Thus, the arriving wave model should be identified even when the noise levels of all electromagnetic field sensors are not equal. We proposed robustly identifying the arriving wave model by introducing a noise integration kernel that includes information about noise level ratios. Our proposed approach classifies a spectral matrix into three cases: noise model, single plane wave model, and multiple waves model. The proposed approach comprises the likelihood ratio test, and the identification result based on a statistical viewpoint. We conducted Monte Carlo simulations, and it was verified that the proposed approach can correctly derive the arriving wave model with high accuracy even with different sensor noise levels.