Radar Data Processing and Applications: Probabilistic Data Association Filter (PDAF) Source Code

Please provide the source code for the Probabilistic Data Association Filter (PDAF) algorithm from "Radar Data Processing and Applications." This algorithm is fundamental to radar data processing and target tracking systems, utilizing probabilistic approaches to associate measurements with tracks while handling cluttered environments. The PDAF implementation typically includes: - Measurement validation and gate formation using chi-square tests - Probability calculation for each measurement-track association - Kalman filter updates with weighted measurement combinations - Clutter density estimation and false alarm management This critical algorithm enables robust multi-target tracking in radar applications by resolving measurement ambiguities. Access to the source code would facilitate deeper understanding of the mathematical implementation, including covariance management and probability normalization routines. The code structure likely showcases matrix operations for state prediction, innovation calculations, and gain computations typical of tracking filters. Thank you for your assistance in providing this important resource for radar engineering development!