针对磁准静态假设下应用表面积分方程提取宽带电阻电感（RL）参数场景，传统自适应交叉近似（ACA）直接压缩线性系统阻抗矩阵时，矩阵秩随频率升高而增大、压缩效率显著下降的问题，提出一种基于质心基函数变换的ACA实现方法。该方法将矢量电流基函数的方向自由度分离到三个稀疏映射矩阵中，使稠密核心矩阵仅描述面网格之间的标量耦合，并对该核心矩阵实施ACA压缩；同时结合混合面网格、回路电流分析和宽带等效表面阻抗模型构建RL提取方程。数值结果表明，所提方法的远场块秩与压缩率在磁准静态宽频范围内保持稳定。双导体算例中，矩阵填充和压缩时间的最高加速比分别约为6倍和80倍；FCBGA与FCCSP算例的矩阵生成时间分别由89 s降至13 s、由304 s降至25 s，峰值内存分别降低20.8%和31.3%，R、L参数的相对偏差分别不超过4.6%和1.73%。数值仿真结果验证了该方法在复杂封装宽带RL参数提取中的精度与效率。

To address the frequency-dependent rank growth and the resulting loss of compression efficiency when adaptive cross approximation (ACA) is directly applied to the loop-impedance matrix in broadband magneto-quasi-static resistance and inductance (RL) extraction, a basis-transformation-based ACA scheme is proposed. The directional degrees of freedom of vector current basis functions are isolated into three sparse mapping matrices, leaving a dense core matrix that contains only scalar couplings between panels. ACA is then applied exclusively to this core matrix. The formulation is combined with mixed surface meshes, loop-current analysis, and a broadband equivalent surface-impedance model. Numerical results show that the rank and compression ratio of far-field blocks remain nearly frequency independent. For the two-conductor example, the maximum speedups of matrix filling and compression are approximately 6 and 80, respectively. For the FCBGA and FCCSP examples, matrix-generation time is reduced from 89 s to 13 s and from 304 s to 25 s, while peak memory is reduced by 20.8% and 31.3%. The maximum reported deviations of the extracted R and L parameters are 4.6% and 1.73%, respectively.