Transient Electromagnetic Weak Signal Extraction Method Based on Multi-Scale Combined Difference Product Morphological Filtering

Abstract

To solve the problem of poor recognition effect of transient signal in low Signal-to-Noise ratio(SNR) and strong interference electromagnetic environment, a morphological filtering method based on the multi-scale combined difference product (MCDPMF) was proposed. This paper concentrates on the issues of sudden changes in transient electronic signal, such as impulses and edges. Firstly, it provides a difference product morphological filter. Moreover, the extended and multi-origin morphological Structural Elements (SEs) is constructed, combining with the multi-structural layers a (a indicates the structural layers of the MCDPMF), the transient electromagnetic weak signal is multi-scale filtered. They are used to optimize the number of the structure layers a adaptively based on the amplitude characteristic ratio of the positive and negative polarity of the filtered signal(HML value), combining the kurtosis-SNR(k x − SN R) ratio characteristic coefficient. MCDPMF is proposed to enhance the filtering results and suppress the noise frequency points. Meanwhile, it can extract the structure components and identify the features of the transient electromagnetic weak signal. It can be shown from simulation and experimental results that the proposed method is superior to EMD, AVG, OCCO, and other methods in subjective evaluation and objective indicators.

Extracting weak electromagnetic signals based on RMPSO-SPBSR in virtual anechoic chamber

“…This article employs both visual observations of output signals in the time and frequency domains and numerical analysis of dimensionless statistical characteristics [33] (Kurtosis, Skewness, Peakfactor, Impulsefactor, Mean squared error) to evaluate the performance of the system. The time and frequency domain images provide a visual representation of the output signal, permitting a qualitative assessment.…”