A Depth-Adaptive Filtering Method for Effective GPR Tree Roots Detection in Tropical Area

This study presents a technique for processing Step-frequency continuous wave (SFCW) ground penetrating radar (GPR) data to detect tree roots. SFCW GPR is portable and enables precise control of energy levels, balancing depth resolution trade-offs. However, the high-frequency components transmission band suffers from poor capability generates noise that interferes with root detection. The proposed time-frequency filtering uses short-time Fourier transform (STFT) track changes in frequency spectrum density over time. To obtain filter window, weighted linear regression (WLR) method used. By adopting conversion variant chirp Z-Transform (CZT), window filters out samples are not interest when doing frequency-to-time domain conversion. depth-adaptive can self-adjust different scenarios, making it independent soil information effectively determines subsurface successfully validated using actual sites tropical area moisture two-dimensional (2D) map systems highly improved compared existing methods.