Abstract
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.
Highlights
With the development of edge computing and interest of things technologies, electronic devices are being widely used in various applications
When the multiple coherent interference sources are detected, the confusion could occur due to coherent noise that is caused by interference phenomenons and the interference intensity of the diffraction wave may be stronger than the intensity of the electromagnetic interference sources (EMIS)
Coherent noise was improved by 13 dB for a maximum value of maximum sidelobe level (MSL), and the dynamic range of the system increased by 76 dB after the proposed method was applied; this proved that a higher MSL
Summary
With the development of edge computing and interest of things technologies, electronic devices are being widely used in various applications. A spectrum analyzer or other qualified measurement equipment is used to detect electromagnetic interference sources (EMIS) It is very time-consuming to use these methods, which require a series of complex and direct measurements on the device surface at different times. A new method was proposed by Jing Dong [4] using a sparse analysis model that contains a data fidelity term and two regularizes to remove the multiplicative noise. These methods are iterative and do not allow one to predict the convergence process at all and are not applicable to real-time measurements. It can realize real-time processing on terminal equipment
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
