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- 实验方案
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Fast Microwave Through Wall Imaging Method With Inhomogeneous Background Based on Levenberg-Marquardt Algorithm
摘要： In this paper, a fast solution for microwave through wall imaging (TWI) with nonlinear inversion is proposed to reconstruct the unknown targets embedded in an inhomogeneous background medium. We treat inhomogeneous background, the wall around bounded in a finite domain as a known scatterer, which has the advantage of avoiding the time-consuming calculation of inhomogeneous background Green’s function. Under this scheme, a new approach under the framework of difference integral equation model, i.e., difference Lippmann–Schwinger integral equation, with modified enhanced Levenberg–Marquardt algorithm is proposed. In particular, we used a hybrid regularized technique, i.e., generalized cross-validation and truncated singular value decomposition, to stabilize the inversion. It is shown that the proposed method runs fast and is stable in presence of noise. Also, it is able to alleviate the nonlinearity and reconstruct unknown scatterers of high contrast with respect to the background. Both the numerical and experimental TWI tests validate the efficiency of the proposed inversion method.
关键词： microwave imaging,Generalized cross-validation (GCV) regularization,inhomogeneous background,inverse scattering problems (ISPs),Levenberg–Marquardt (LM) method
更新于2025-09-10 09:29:36
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An enhanced Dynamic Modeling of PV Module Using Levenberg- Marquardt Algorithm
摘要： An improved dynamic modeling of PV cell/modules based on automatic parameters extraction is proposed in this paper. For the sake of clarity, three models are compared in this study including, Single Diode (SDM), Double Diode (DDM) and the empirical model developed by Sandia National Laboratory (SANDIA). The use of nominal parameters or the values given by manufacturer in both SDM and DDM diode saturation current I0 and photo-generation current Iph equations can engender a significant error depending on the operating conditions and the consumed lifetime. Hence, these values can be handled as model parameters, and can be adjusted using automatic parameters extraction algorithms. Moreover, parameters based on static extraction methods (with fixed irradiation and temperature) namely, Rs, Rsh and n do not give satisfactory results under variable irradiation and temperature, which involve the use of a dynamic adjustment method to improve these parameters. In this way, static parameters extraction using genetic algorithm (GA) is proposed as a first stage for both SDM and DDM. After that, a dynamic parameters extraction based on the Levenberg-Marquardt algorithm (LMA) has been employed in the purpose to adjust some nominal parameters provided by the literature and the manufacturer, and those given by the static method. The idea consists of considering the PV module and the MPPT as a single system with dynamic inputs (irradiation and temperature) and output (Impp, Vmpp and Pmpp) to minimize the error between the measured and the simulated outputs. The validity of the proposed approach is compared with dynamic LMA models, nominal parameters based models, and the models based on static GA extracted parameters under of different weather conditions and out-door measurements. The improved models show promising results in terms of agreement with real data.
关键词： Photovoltaic module,Genetic Algorithm (GA),Dynamic Parameters Extraction,Static Parameters Extraction,Levenberg- Marquardt (LM)
更新于2025-09-04 15:30:14