Linear arrays are popularly used for passive surface wave imaging due to their high efficiency and convenience, especially in urban applications. The unknown characteristics such as azimuth of noise sources, however, make it challenging to extract accurate phase-velocity dispersion information by employing a 1-D linear array. To solve this problem, we proposed an alternative passive surface wave method to capture the dominant azimuth of noise sources and retrieve the phase-velocity dispersion curve by polarization analysis with multicomponent ambient noise records. We verified the proposed method using synthetic data sets under various source distributions. According to the calculated dominant azimuth, it is deduced that noise sources are mainly classified as either inline or offline distribution. For inline noise source distribution, we are able to directly obtain the unbiased phase-velocity measurements; for offline noise source distribution, we should correct the velocity overestimation due to azimuthal effects using the proposed method. Results from two field examples show that the distributions of noise sources are predominantly offline. We eliminated the velocity bias caused by offline source distribution and picked phase velocities following higher amplitude peaks along the trend. After the azimuthal correction, the picked phase-velocity dispersion curves in dispersion images generated from passive source data match well with those from active source data, demonstrating the practicability of the proposed technique.

线性阵列由于其高效率和便利性而广泛用于无源表面波成像，特别是在城市应用中。然而，噪声源方位角等未知特征使得利用一维线性阵列提取准确的相速度色散信息变得具有挑战性。为了解决这个问题，我们提出了一种替代的无源表面波方法来捕获噪声源的主要方位角，并通过多分量环境噪声记录的偏振分析来检索相速度色散曲线。我们使用各种源分布下的合成数据集验证了所提出的方法。根据计算出的主方位角，推断噪声源主要分为在线分布和离线分布。对于在线噪声源分布，我们能够直接获得无偏相速度测量；对于离线噪声源分布，我们应该使用所提出的方法纠正由于方位角效应而导致的速度高估。两个现场示例的结果表明，噪声源的分布主要是离线的。我们消除了由离线源分布引起的速度偏差，并沿趋势选择了跟随更高振幅峰值的相速度。经过方位角校正后，从被动源数据生成的色散图像中拾取的相速度色散曲线与主动源数据的相速度色散曲线吻合得很好，证明了该技术的实用性。