Improved wavelet threshold denoising method for magnetic field signals of magnetic targets

Abstract The presence of complex electromagnetic noise significantly impacts the accuracy of magnetic targets signal detection, necessitating the development of an effective denoising method to enhance detection precision. Nevertheless, traditional denoising methods faces problems such as difficulty in selecting wavelet basis, difficulty in specifying the decomposition level, and unreasonable selection of thresholds. This study introduces improved wavelet threshold denoising based on peak-to-sum ratio and composite evaluation index T, named as (PSR-T-IWTD). PSR-T-IWTD integrates the improved wavelet basis selection method, improved wavelet decomposition level selection method, improved threshold selection method, and improved threshold function design method. Calculate the composite evaluation index T and select the wavelet basis with the smallest T as the optimal wavelet basis. The optimal number of decomposition level is determined by the PSR of the wavelet detail coefficients. An improved threshold selection method and threshold function are introduced to further enhance the performance of wavelet threshold denoising (WTD). Finally, the magnetic field denoising test of the ship model was designed and compared with Butterworth low-pass filter (BLPF), optimal wavelet selection wavelet adaptive threshold denoising (OWSWATD) and improved WTD based on T (T-IWTD) to verify the effectiveness of PSR-T-IWTD. The test results show that PSR-T-IWTD has lower computational complexity. Meanwhile, PSR-T-IWTD improves the signal-to-noise ratio by 10.2%, 6.8% and 8.3% compared to BLPF, OWSWATD and T-IWTD, respectively.