An Improved QPSO Material Calibration Algorithm for Ray-Tracing at Terahertz Band

In real scenarios, the electromagnetic parameters of materials play a critical role in determining the accuracy of ray-tracing (RT) simulations. Due to the incomplete terahertz (THz) frequency material libraries for RT simulations, accurate material calibration is essential for improving simulation precision at THz frequencies. In order to fill this gap, an improved quantum-behaved particle swarm optimization (QPSO) algorithm, referred to as the OSQPSO algorithm, is proposed to calibrate the material parameters for THz bands. The algorithm incorporates opposition-based learning (OBL) and simulated annealing (SA) algorithms in the initialization and particle updating processes of the QPSO algorithm, thereby increasing particle diversity and enhancing global search capability. The modified QPSO algorithm calibration performance is validated in an outdoor canyon scenario at 140 and 220 GHz, demonstrating superior calibration accuracy while maintaining a similar convergence rate compared to traditional swarm optimization algorithms.