The wideband electromagnetic imaging system using a parabolic reflector is a device for detecting and locating electromagnetic interference sources (EMIS). When multiple coherent interference sources are detected, the confusion will occur due to the coherent noise that is caused by interference phenomenons. Previous works have removed the coherent noise by using iterative techniques, but they face a limitation in removing noise in that the coherent noise pattern changes with frequency in a wideband. In this paper, an adaptive homomorphic filtering is proposed to overcome the limitations of conventional methods from 1 GHz–6 GHz. The coherent noise existing in the several electromagnetic images is studied, and it is confirmed that the variation of the coherent noise pattern is related to the position, the number, and the frequency of EMIS. Then, by analyzing the probability density of coherent noise intensity, an adaptive Gaussian filter is carefully designed to remove coherent noise. The filter parameters are selected by the minimum description length criterion (MDL) to apply to compute directly the local amount of Gaussian smoothing at each pixel of each image. The results of the experiments and simulations demonstrate that the proposed method can significantly improve the quality of electromagnetic images in terms of maximum sidelobe level (MSL) by 15 dB and dynamic range (DR) of the system over 20 dB, compared with conventional narrowband denoising methods.
Coherent Noise Suppression Using Adaptive Homomorphic Filtering for Wideband Electromagnetic Imaging System
