94 GHz Asymmetric Antenna Radar for Speech Signal Detection and Enhancement via Variational Mode Decomposition and Improved Threshold Strategy

Abstract

To further improve the detection distance and sensitivity of bio-radar, a 94 GHz asymmetric antenna radar sensor is employed to detect speech signal. However, the radar speech is often mixed with various noise, which will seriously affect the quality and intelligibility of the speech signal. Therefore, a novel method based on variational mode decomposition (VMD) and improved threshold strategy (ITS) is proposed in this paper for improving the quality and intelligibility of the radar speech. VMD is a novel adaptive decomposition method, which overcomes the problem of mode aliasing and end effect in empirical mode decomposition (EMD). ITS can overcome the limitation of traditional wavelet threshold and achieve the best compromise between speech intelligibility and noise reduction. Firstly, EMD is applied to determine the number of decomposition level, and then radar speech is decomposed into several limited bandwidth intrinsic mode functions by VMD. Secondly, ITS is employed to remove noise from useful modes which are determined by Pearson correlation coefficient (PCC). The performance of the proposed method is evaluated by perceptual evaluation of speech quality (PESQ), short-time objective intelligibility (STOI) and composite measures (CMs). The experimental results show that the radar sensor can detect long distance speech signal and the proposed method can effectively improve the quality and intelligibility of the radar speech signal. Due to the good performance, the proposed method will provide a promising alternative for various applications related to radar speech and traditional microphone speech signal enhancement.