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Abstract-Noise pollution has a large negative influence on the health of humans, especially in case of long-term exposure. Various passive hearing protection approaches are available. However, they often lack good protection against low frequency noise. For these applications, the principle of Active Noise Cancellation (ANC) offers a promising supplement. It relies on anti-phase compensation of the noise signal. Within the area of ANC, only few publications deal with the Kalman filter approach. The state-of-the-art in literature is briefly reviewed. The algorithm presented in this contribution is inspired by the time-domain Kalman filter. The Kalman filter has the favorable property of fast convergence as well as good tracking properties. Especially the tracking of time-varying noise conditions is often a drawback of least-mean-square (LMS) and recursive-least-square (RLS) approaches. The proposed algorithm uses the Kalman equations which are extended by online model parameter estimation based on observable signals. This results in faster convergence and higher robustness against dynamically changing noise conditions. The performance of the algorithm is evaluated by means of convergence, tracking and stability with measured acoustic paths from a real-time system.

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The evolving field of ear-mounted hearing devices manifests in more people wearing headphones, hearing aids or hearables in daily life. One of their purposes is to reduce the increasing burden of ambient noise. Their passive attenuation of noise can be supplemented by using Active Noise Cancellation (ANC). It uses acoustic anti-phase compensation. The occurring ambient noises in daily life can have a highly time-variant nature, e.g. with varying direction of arrival. In this contribution, we investigate the direction-dependency of ANC systems based on acoustic device-specific head related transfer functions (DHRTF). The DHRTF were measured with a fast measurement system for HRTF. We focus on in-ear headphones as the acoustic front-end. The headphones comprise two microphones; an outer microphone for ambient sounds and an inner microphone, which faces the eardrum. The transfer function between these two microphones is called the primary path. For the ANC system, we investigate optimal time-invariant feedforward filtering that depends on the primary path. Therefore, changes in the primary path due to varying directions of arrival may degrade the performance. The DHRTF measurements reveal differences in magnitude and phase of the primary path. Evaluations show that the attenuation performance depends on the direction of arrival.