2017 25th European Signal Processing Conference (EUSIPCO) 2017
DOI: 10.23919/eusipco.2017.8081276
|View full text |Cite
|
Sign up to set email alerts
|

Time-domain Kalman filter for active noise cancellation headphones

Abstract: 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-th… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
27
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
5
2
1

Relationship

1
7

Authors

Journals

citations
Cited by 26 publications
(27 citation statements)
references
References 9 publications
(10 reference statements)
0
27
0
Order By: Relevance
“…The acoustic loads coupled with the headphone and acoustic effects constitute the main signal processing challenges of ANC algorithms. 36 Compromises may be necessary related to the size of the loudspeaker, the energy consumption, and the capacity of the ANC system. Advanced technology, such as a deep learning model for ANC, to expand the capacity of the ANC function to achieve real-time implementation of ANC headphones in audiometric tasks will be a focus of future work.…”
Section: Discussionmentioning
confidence: 99%
“…The acoustic loads coupled with the headphone and acoustic effects constitute the main signal processing challenges of ANC algorithms. 36 Compromises may be necessary related to the size of the loudspeaker, the energy consumption, and the capacity of the ANC system. Advanced technology, such as a deep learning model for ANC, to expand the capacity of the ANC function to achieve real-time implementation of ANC headphones in audiometric tasks will be a focus of future work.…”
Section: Discussionmentioning
confidence: 99%
“…For example, if the background noise is louder than the acoustic source, it is difficult for the system to localize the acoustic source without a sophisticated noise filtering method. We are currently improving the accuracy of ball position estimation by integrating an active noise cancellation [21] and a room sound wave reflect-aware scheme [22] in the existing system.…”
Section: Discussionmentioning
confidence: 99%
“…Improper choice of Q and R may influence the performance of the filter method. Many estimation methods have been proposed to determine Q and R in the filter process (e.g., Akhlaghi et al 2017;Basso et al 2017;Ding et al 2007;Liebich et al 2017;Saho and Masugi 2015). With the use of adaptive filtering approach, we estimate Q and R , and it can be expressed as (Akhlaghi et al 2017) where ε(k) = Y (k) − HX(k|k) is the difference between the observed value and estimated one.…”
Section: Adaptive Kalman Filtermentioning
confidence: 99%