A Novel Technique for Localizing the Scatterer in Inverse Profiling of Two Dimensional Circularly Symmetric Dielectric Scatterers Using Degree of Symmetry and Neural Networks
A novel technique for localizing the scatterer in microwave imaging of two-dimensional circularly symmetric dielectric scatterers using degree of symmetry and neural networks is presented. The degree of symmetry for a transmitter position is computed as a function of the difference between the first half and the spatially reflected second half of the measured scattered field vector. A Probabilistic Neural Network (PNN) classifier is trained with the degree of symmetry vectors for the different object configurations. It classifies the degree of symmetry vector of the unknown circularly symmetric scatterer presented to it into one of the classes that indicate the radius and location of the centre of the scatterer. Thus the scatterer is localized in the imaging domain. This not only reduces the degrees of freedom in the inversion for the unknown object, thereby aiding the global convergence of the solution,but also results in a reduction in computation time. The technique has been tested on synthetic data and the results are promising.
Vinu Thomas C.Gopakumar Jaimon Yohannan Anil Lonappan G.Bindu A.V.Praveen Kumar V.Hamsakutty K.T.Mathew
Cochin University of Science and Technology,India
国际会议
Progress in Electromagnetics Research Symposium 2005(2005年电磁学研究新进展学术研讨会)(PIERS 2005)
杭州
英文
115-119
2005-08-22（万方平台首次上网日期，不代表论文的发表时间）