Accuracy improvement of the S-parameter adjoint sensitivity analysis for shape parameters

Zhu, Xiaying; Nikolova, Natalia K.

doi:10.1109/mwsym.2009.5165750

Cited by 2 publications

(2 citation statements)

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“…More importantly, when numerical field solutions are used, the adjoint-based sensitivity estimates are accurate, i.e. they are of the same order of accuracy as the response estimates and do not suffer from catastrophic cancellation [37]. Note that the adjoint-variable sensitivity formula is exact when the derivatives of the system matrices with respect to the system parameters are known analytically.…”

Section: Introductionmentioning

confidence: 99%

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Near-field detection at microwave frequencies based on self-adjoint response sensitivity analysis

2010

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A new detection method is proposed for the localization of electrically small scatterers in a known background medium. The method requires the knowledge of the electric field distribution inside the known background medium where no scatterers are present. It is based on a self-adjoint response sensitivity computation which can be performed in real time. Using the E-field distribution in the background medium, it provides three-dimensional maps of the Fréchet derivative within the imaged volume. The peaks and dips in these maps identify the locations where the permittivity and conductivity of the measured medium differ from those in the background medium. The background medium can be heterogeneous. In a homogeneous-medium example, the performance of the detection algorithm is studied in terms of the number of transmission/reception points, the dielectric contrast of the scatterer compared to the background medium, and the size of the scatterer. Its resolution is also addressed. The detection of a small scatterer in a heterogeneous background is demonstrated.

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Section: Introductionmentioning

confidence: 99%

“…In imaging, the number of parameters may be on the order of thousands. Another prohibitive constraint is due to the limited accuracy of the simulated responses, which causes catastrophic cancellations in the finite-difference estimates of the response derivatives [36][37][38].…”

Section: Introductionmentioning

confidence: 99%