Research on Inversion Algorithm of Interferometric Microwave Radiometer Based on PSO-LM-BP Model

Abstract

In order to improve the temperature measurement accuracy of microwave radiometer, the inversion algorithm of interferometric microwave radiometer is improved. In the paper propose an improved PSO-LM algorithm based on BP network, which combines Particle Swarm optimization(PSO) and Levenberg-Marquardt(LM). By analyzing the influencing factors of the temperature measurement process of microwave radiometer, the influences of radiometer output voltage, transmission line temperature, aluminum tube temperature and antenna temperature on the temperature measurement results are considered in the inversion algorithm. In order to confirm the effectiveness and superiority of PSO-LM optimized BP network in water temperature inversion experiment, this paper selects PSO algorithm, LM algorithm and PSO-LM algorithm to optimize BP network for comparative experiment and cross-validation. The experimental results show that using PSO-LM algorithm to optimize BP network inversion has higher accuracy and faster convergence rate than traditional PSO algorithm, and is more stable than LM algorithm. PSO-LM-BP algorithm can improve the temperature measurement accuracy of microwave radiometer to $0.207^{\circ}C$, which makes the temperature measurement accuracy of microwave radiometer significantly improved, and has certain practical value and social significance.