Global geophysical networks provide powerful databases to infer globally coherent signals, and array processing techniques are useful for inferring them. In this study, we comprehensively analyze seven spherical harmonic-based array processing techniques: spherical harmonic stacking (SHS) as well as its gridded form (SHS_GT) and grid-interval weighted forms (SHS_GK1, SHS_GK2); matrix SHS (MSHS); multi-station experiment (MSE); and optimal sequence estimation (OSE). We first use more specific synthetic tests to evaluate the pros and cons of these techniques, and estimate bias in solutions caused by the station distributions. These methods are applied to four global observation networks, the Global Geodynamics Project (GGP) Network, the Global Seismographic Network (GSN), the Global Geomagnetic (GGM) Network and the Global GNSS Network. For the first time, we restored a much cleaner sequence for one singlet of the ₀S₂ mode based on the GGP network, and restored similar result for one singlet of the ₃S₁ mode based on the GSN network. We further isolate different Y_lm-related tidal signals from the GGM network for the first time. Moreover, based on global GNSS observations, we estimate the Love number h₂₁ = 0.6243(±7e−4) − 0.01(±6e−3)i at the Chandler Wobble (CW) frequency with OSE/MSHS (The accuracy of the estimate is an order of magnitude higher than the previous results), and further obtain the corresponding lower-mantle anelasticity (f_r(ω) = −29.5 ± 0.9, f_i(ω) = 12.0 ± 7.2). Our findings confirm that OSE and MSHS methods can more accurately obtain the complex amplitude of any Y_lm-related signal, which is not possible with other methods (and we do obtain more precise results than previous studies upon using them); besides, we also confirm that OSE and MSHS methods can greatly reduce the interference of other signals to the target signals. Hence, we believe the results obtained from the OSE/MSHS will helpful for obtaining reasonable geophysical explanations.

全球地球物理网络提供了强大的数据库来推断全球相干信号，阵列处理技术可用于推断它们。在本研究中，我们综合分析了七种基于球谐函数的阵列处理技术：球谐叠加（SHS）及其网格形式（SHS_GT）和网格间隔加权形式（SHS_GK1、SHS_GK2）；矩阵 SHS (MSHS); 多站实验（MSE）；和最优序列估计（OSE）。我们首先使用更具体的综合测试来评估这些技术的优缺点，并估计由站点分布引起的解决方案的偏差。这些方法应用于四个全球观测网络，即全球地球动力学项目（GGP）网络、全球地震网络（GSN）、全球地磁（GGM）网络和全球GNSS网络。₀ S ₂模式基于GGP 网络，对基于GSN 网络的₃ S ₁模式中的一个单线态恢复了类似的结果。我们首次进一步从 GGM 网络中分离出不同的Y _lm相关潮汐信号。此外，基于全球导航卫星系统的观察，我们估计洛夫数ħ ₂₁  = 0.6243（±7E-4） - 0.01（±6E-3）我在与OSE / MSHS（所述估计的精度Chandler摆动（CW）频率是比之前的结果高一个数量级），并进一步得到相应的下地幔非弹性（f _r ( ω ) = −29.5 ± 0.9, f _i( ω ) = 12.0 ± 7.2)。我们的研究结果证实，OSE 和 MSHS 方法可以更准确地获得任何Y _lm相关信号的复振幅，这是其他方法无法实现的（并且我们确实获得了比以前使用它们的研究更精确的结果）；此外，我们还确认OSE和MSHS方法可以大大减少其他信号对目标信号的干扰。因此，我们相信从 OSE/MSHS 获得的结果将有助于获得合理的地球物理解释。