A high-performance approach to minimizing interactions between inbound and outbound signals in helmet

NASA is developing a new generation of audio system for astronauts. The idea is to use directional speakers and microphone arrays. However, since the helmet environment is very reverberant, the inbound signals in the directional speaker may still enter the outbound path (microphone array), resulting in an annoying positive feedback loop. To improve the communication quality between astronauts, it is necessary to develop a digital filtering system to minimize the interactions between inbound and outbound signals. In this paper, we will present the following results. First, we set up experiments under three scenarios: office, bowl, and helmet. Experiments were then performed. Second, 3 adaptive filters known as normalized least mean square (NLMS), affine projection (AP), and recursive least square (RLS) were applied to the experimental data. We also developed a new frequency domain adaptive filter called FDAFSS (frequency domain adaptive filter (FDAF) with spectral subtraction (SS)), which is a combination of FDAF and SS. FDAFSS was compared with LMS, AP, RLS, FDAF, and SS filters and FDAFSS yielded better performance in terms of perceptual speech quality (PESQ). Moreover, FDAFSS is fast and can yield uniform convergence across different frequency bands.