2058 IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 19, NO. 7, SEPTEMBER 2011
Improving Performance of Hybrid Active
Noise Control Systems for Uncorrelated
Narrowband Disturbances
Muhammad Tahir Akhtar, Member, IEEE, and Wataru Mitsuhashi
Abstract—In filtered-x LMS (FxLMS) single-channel feedfor-
ward active noise control (ANC) systems, a reference signal is
available that is correlated with the primary disturbance at the
error microphone. In some practical situations, there may also be
a disturbance uncorrelated with the primary disturbance at the
error microphone, for which a correlated reference signal is not
available. This disturbance, being uncorrelated with the primary
noise, cannot be controlled by the standard FxLMS algorithm, and
increases the residual noise. In this paper we propose an improved
hybrid ANC system that can simultaneously control both the
correlated and uncorrelated noise signals. The proposed method
comprises three adaptive filters: 1) the FxLMS-based ANC filter to
cancel the primary noise; 2) a separate FxLMS-based ANC filter
to cancel the uncorrelated disturbance; and 3) an LMS-based sup-
porting adaptive filter to generate appropriate signals for the two
ANC filters. Computer simulations demonstrate that the proposed
method can effectively mitigate the correlated and uncorrelated
primary disturbances. This improved performance is achieved at
only a small increase in computational complexity.
Index Terms—Active noise control (ANC), filtered-x least mean
square (FxLMS) algorithm, hybrid ANC, uncorrelated distur-
bance.
I. INTRODUCTION
A
CTIVE noise control (ANC) is based on the principle of
destructive interference between acoustic or vibrational
waves. Essentially, the primary noise is canceled near the error
microphone by generating and combining an antiphase can-
celing noise [1]. Feedforward control is widely used in ANC
systems when an independent reference signal is available
and is well correlated with the primary noise. As shown in
Fig. 1, a single-channel feedforward ANC system comprises
one reference sensor to pick up the reference noise
correlated with the primary disturbance , one canceling
Manuscript received July 01, 2010; revised October 23, 2010 and January 04,
2011; accepted January 21, 2011. Date of publication February 07, 2011; date
of current version July 20, 2011. The associate editor coordinating the review
of this manuscript and approving it for publication was Dr. Jingdong Chen.
M. T. Akhtar is with The Center for Frontier Science and Engineering
(CFSE), University of Electro-Communications, Tokyo 182-8585, Japan, and
also with The Center for Research and Development of Educational Technology
(CRADLE), Tokyo Institute of Technology, Tokyo 152-0033, Japan (e-mail:
akhtar@ice.uec.ac.jp; akhtar@ieee.org).
W. Mitsuhashi is with the Department of Information and Communication
Engineering, University of Electro-Communications, Tokyo 182-8585, Japan
(e-mail: mit@ice.uec.ac.jp).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TASL.2011.2112349
Fig. 1. Block diagram of single-channel feedforward ANC system in the pres-
ence of an uncorrelated disturbance.
loudspeaker to propagate the canceling signal generated
by ANC filter through the secondary path , and one
error microphone to pick up the residual noise . The most
famous adaptation algorithm for ANC systems is the filtered-x
least mean square (FxLMS) algorithm [2], which is a modified
version of the LMS algorithm [3]. The FxLMS algorithm is
a popular ANC algorithm due to its robust performance, low
computational complexity, and ease of implementation [2]. In
the FxLMS algorithm, the reference signal is filtered
through a model of the secondary path and hence the
name filtered-x algorithm. The secondary path model may
be estimated a priori using offline modeling technique [2] and
kept fixed, or it may also be adapted online during operation
of the ANC system [4]–[9]. In this paper, we assume that the
secondary path has been exactly identified as .
The FxLMS algorithm is widely used in ANC systems. How-
ever, the performance the FxLMS algorithm in steady state will
be degraded due to the presence of an uncorrelated disturbance
at the error microphone, shown as in Fig. 1. This situ-
ation arises in many real-world applications. For example, in
electronic mufflers for automobiles [10], an uncorrelated dis-
turbance, such as the noise generated by other passing-by auto-
mobiles, will affect the stability and performance of the ANC
system. In another example for industrial installations, neigh-
boring machinery near the error microphone may generate an
uncorrelated disturbance. For other related examples, the reader
is referred to [11], [12].
In [11], an adaptive algorithm consisting of two intercon-
nected adaptive notch filters is proposed to reduce the uncorre-
lated disturbance problem. However, this algorithm is effective
only for narrowband, single-frequency ANC systems. In [12],
this algorithm has been generalized to multifrequency narrow-
band feedforward ANC systems using a single high-order adap-
tive filter, and an ANC system using cascading filters is pro-
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