Subspace Optimization Based Nonlinear Inverse Scattering Method For Scatters Reconstruction

With the development of era, a growing number of microwave imaging technology has been applied in various fields, it accounts for the proportion of more and more in our daily life and in the military field. Traditional microwave imaging algorithm can’t meet the demand of People’s Daily. Therefore, it is of great significance to the defense of the information age and highly developed society that carry out research related to the microwave imaging. Microwave imaging studies is one of the world frontier subject. With the microwave imaging technology, its main function is to imaging to the target, how to improve the effect of microwave imaging is the one of the important research. This paper mainly studied the microwave imaging algorithm, and how to improve this algorithm. It has positive significance to the development of microwave imaging.Electromagnetic field inverse imaging problem is to solve the problem of nonlinear integral equation, the equation for ill- equation, when solving this equation by directly with high computational cost and instability. Therefore, how it is an important research content that how to optimize the nonlinear integral equation in solving electromagnetic inverse scattering problem. According to the processing of the nonlinear integral equation in a different way, Microwave imaging algorithm can be divided into two categories: linear imaging algorithm, nonlinear imaging algorithm. This paper mainly studies the second born approximation of the linear algorithm and subspace optimization method of nonlinear algorithm, and through the experimental analysis compare the second born approximation and the subspace optimization method.In view of the second Born approximation, based on the first Born approximation derive the second order Born approximation, and make it linearization, and then using inexact Newton algorithm for target imaging. Consider how to optimize the iterative algorithm and how to reduce the computational cost, In the case of multiple transmit antennas and receive antennas, consider how to merge the imaging effect, and compare the imaging effect in TM and TE waves.For subspace optimization method(SOM), in this article, improve the objective function is used in the target imaging. 2-D Green’s function use the Hankel function of second kind and zeroth-order, and the expression of related parameters is deduced. Calculated the deterministic current by choosing appropriate cut-off point, and through iterative optimization calculate the ambiguous part of the induced current. Finally, calculate the total electric field within the target grid, and then work out the relative permittivity of the target.In this paper, the experimental data from Marseille Fresnel institute. Experimental results show that the use of the second order Born approximation for target imaging is better than first-order Born approximation. It can be concluded that the location, size, and dielectric constant of the object. In addition, Multi-objective imaging also has a good result. For using SOM to target imaging, it not only can be a more accurate reflection of the target position and size than the second order Born approximation, but also can better calculate the target of the dielectric constant,but it cost the high computational. As a result, the SOM of the nonlinear imaging algorithm showed higher accuracy for the target imaging.