One enduring challenge for controlling high frequency sound in local active noise control (ANC) systems is to obtain the acoustic signal at the specific location to be controlled. In some applications such as in ANC headrest systems, it is not practical to install error microphones in a person’s ears to provide the user a quiet or optimally acoustically controlled environment. Many virtual error sensing approaches have been proposed to estimate the acoustic signal remotely with the current state-of-the-art method using an array of four microphones and a head tracking system to yield sound reduction up to 1 kHz for a single sound source. In the work reported in this paper, a novel approach of incorporating remote acoustic sensing using a laser Doppler vibrometer into an ANC headrest system is investigated. In this “virtual ANC headphone” system, a lightweight retro-reflective membrane pick-up is mounted in each synthetic ear of a head and torso simulator to determine the sound in the ear in real-time with minimal invasiveness. The membrane design and the effects of its location on the system performance are explored, the noise spectra in the ears without and with ANC for a variety of relevant primary sound fields are reported, and the performance of the system during head movements is demonstrated. The test results show that at least 10 dB sound attenuation can be realised in the ears over an extended frequency range (from 500 Hz to 6 kHz) under a complex sound field and for several common types of synthesised environmental noise, even in the presence of head motion.

Microphones have been extensively studied for many decades and their related theories are well-established. However, the physical presence of the sensor itself limits its practicality in many sound field control applications. Laser Doppler vibrometers (LDVs) are commonly used for the remote measurement of surface vibration that are related to the sound field without the introduction of any such physical intervention. This paper investigates the performance and challenges of using a piece of retro-reflective film directly as an acoustic membrane pick-up with an LDV to sense its vibration to form a remote acoustic sensing apparatus. Due to the special properties of the retro-reflective material, the LDV beam can be projected to the target over a wide range of incident angles. Thus, the location of the LDV relative to the pick-up is not severely restricted. This is favourable in many acoustic sensing and control applications. Theoretical analysis and systematic experiments were conducted on the membrane to characterise its performance. One design has been selected for sensing sound pressure level above 20 dB and within the 200 Hz to 4 kHz frequency range. Two example applications—remote speech signal sensing/recording and an active noise control headrest—are presented to demonstrate the benefits of such a remote acoustic sensing apparatus with the retro-reflective material. Particularly, a significant 22.4 dB noise reduction ranging from 300 Hz to 6 kHz has been achieved using the demonstrated active control system. These results demonstrate the potential for such a solution with several key advantages in many applications over traditional microphones, primarily due to its minimal invasiveness.

Active noise control (ANC) systems are commonly designed to achieve maximal sound reduction regardless of the incident direction of the sound. When desired sound is present, the state-of-the-art methods add a separate system to reconstruct it. This can result in distortion and latency. In this work, we propose a multi-channel ANC system that only reduces sound from undesired directions, and the system truly preserves the desired sound instead of reproducing it. The proposed algorithm imposes a spatial constraint on the hybrid ANC cost function to achieve spatial selectivity. Based on a six-channel microphone array on a pair of augmented eyeglasses, results show that the system minimized only noise coming from undesired directions. The control performance could be maintained even when the array was heavily perturbed. The proposed algorithm was also compared with the existing methods in the literature. Not only did the proposed system provide better noise reduction, but it also required much less effort. The binaural localization cues did not need to be reconstructed since the system preserved the physical sound wave from the desired source.

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