Ultra-broadband microwave frequency down-conversion based on optical frequency comb.

Based on optical frequency comb (OFC), a photonic-assisted ultra-broadband microwave signal down-converting method is proposed. In the proposed scheme, microwave signal at 2~20GHz can be down-converted to 0~1GHz intermediate frequency (IF) signals by an OFC of 2GHz frequency space at different order of comb lines. By slightly switching the frequency space of OFC, the frequency of the signal to be measured can be retrieved through the frequency shift of the down-converted IF signal. The validity of this proposed unknown signal detection method is verified by the experiments. The proposed method is proven to be flexible, low-cost and easily implemented, which requires only a low-frequency tunable microwave source while provides ultra-broadband down-converting frequency range.

Multi-resolution subspace-based optimization method for solving three-dimensional inverse scattering problems.

An innovative methodology is proposed to solve quantitative three-dimensional microwave imaging problems formulated within the contrast source framework. The introduced technique is based on the combination of an efficient iterative multiscaling strategy aimed at mitigating local minimum issue arising in inverse scattering problems, and a local search algorithm based on the subspace-based optimization method (SOM) devoted to effectively retrieving both the "deterministic" and the "ambiguous" parts of the unknown contrast currents. To achieve this goal, a nested iteration process is adopted in which the outer loop iteratively refines the region of interest (ROI) where the scatterers are detected, while the inner loop retrieves the dielectric properties of the scatterers within the ROIs. Selected numerical examples are also given to show the validity and robustness of the proposed algorithm in comparison with state-of-the-art techniques.

Application of T-matrix method in solving mixed boundary separable obstacle problem.

The practical problem of imaging scatterers enclosed by separable obstacles with mixed boundary is addressed. Both the unknown scatterers and the known obstacle media can be mixture of dielectric and perfect electric conducting (PEC) materials. The scattering phenomenon of such problem is well modeled by T-matrix method. By usage of separable prior information, the obstacle media are treated as known scatterers rather than part of the background. The number of unknowns is thus reduced greatly. After recovering the profiles of scatterers by T-matrix method, a criterion is further provided to classify the PEC and dielectric scatterers. Various numerical examples are presented to show the effectiveness and good performance of the method.

Electromagnetic imaging of separable obstacle problem.

The practical problem of imaging scatterers that are separable from the known obstacles is addressed. Using such a priori information, the obstacle is regarded as a known scatterer rather than part of the background and can be excluded from the retrieving process by reformulating the cost function. As a result, the proposed method transforms the problem into an inverse scattering problem with homogeneous background, and avoids the computationally intensive calculation of Green's function for inhomogeneous background (bases of the physical model of the problem). Meanwhile, the factors that influence the imaging quality for such kind of problem are also analyzed. Various difficult numerical examples are presented to show the good performance of our method. In addition, a data set of scattering experiments from the Institut Fresnel is tested to verify the validity of our method.