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

机译:基于PSO-LM-BP模型的干涉微波辐射计倒反转算法研究

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摘要

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.
机译:为了提高微波辐射计的温度测量精度,改善了干涉式微波辐射计的反转算法。本文提出了一种基于BP网络的改进的PSO-LM算法,其结合了粒子群优化(PSO)和Levenberg-Marquardt(LM)。通过分析微波辐射计的温度测量过程的影响因素,以反演算法考虑了辐射计输出电压,传输线温度,铝管温度和天线温度对温度测量结果的影响。为了确认PSO-LM优化的BP网络在水温反演实验中的有效性和优越性,本文选择PSO算法,LM算法和PSO-LM算法优化BP网络进行比较实验和交叉验证。实验结果表明,使用PSO-LM算法优化BP网络反演具有比传统PSO算法更高的收敛速度,比LM算法更稳定。 PSO-LM-BP算法可以将微波辐射计的温度测量精度提高到0.207 ^ { rIC} C $,这使得微波辐射计的温度测量精度显着提高,具有一定的实用价值和社会意义。

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