MATLAB Codes and IPIX Radar Sea Clutter Data for Anisotropy-Adaptive Total Bregman Divergence for K-Means Clustering on SPD Matrices

MATLAB Codes (7 files):4.2_Fig1_Table3_Homogeneous_TPR.m – Detection performance under homogeneous background (Fig. 1, Table 3)4.2_Fig2_Table4_Heterogeneous_TPR.m – Detection performance under heterogeneous background (Fig. 2, Table 4)4.3_Fig3_Table5_6_Scale_Overlap.m – Robustness under scale-overlapped scenarios (Fig. 3, Tables 5–6)4.4_Fig4_Weight_Allocation.m – Visualization of adaptive weight allocation (Fig. 4)4.5_Fig5_Table7_Difficulty_Levels.m – Robustness under varying difficulty levels (Fig. 5, Table 7)4.6_Fig6_Table8_Influence_Boxplot.m – Influence function verification (Fig. 6, Table 8)4.7_Table9_IPIX_Clutter.m – Geometric analysis of real sea clutter data (Table 9)2.

IPIX Radar Sea Clutter Data (2 files):Hi.zip – High sea state conditions (range bin 3, VV polarization)Lo.zip – Low sea state conditions (range bin 5, VV polarization)These data were collected by the McMaster IPIX radar during the 1993 Dartmouth measurement campaign and are widely used as a benchmark in sea clutter characterization and radar target detection research.The codes reproduce all numerical experiments on synthetic SPD data and real-world sea clutter analysis.