Projects per year
Abstract
This Ph.D. thesis includes fundamental considerations about topologies, algorithms, implementations,
methods etc., that can enter in the next generation of active control (AC) systems.
Specifically, a new variant of feedforward control referred to as confined feedforward active control
(CFFAC) is proposed. This topology is constituted from a set of reference sensors that are
positioned on a surface that completely confines the desired zones of quite. A set of performance
sensors monitors the achieved noise reduction. This CFFAC topology in turn is embedded in a
multipleinput and multipleoutput (MIMO) system that facilitates both feedforward and feedback
control. The general system is then referred to as hybrid MIMO confinedfeedforward feedback
(HMIMOCFFFB) active noise reduction (ANR) system. The investigation of a multichannel
ANR system with hybrid feedforward and feedback topologies is motivated by requirements of
high ANR attenuation in extreme noise environments as typically experienced onboard airborne
military platforms. Noise recordings acquired on such platforms reveal very high sound pressure
levels often exceeding 140 dB re. 20 μPa. Moreover, these noise signals exhibit large temporal
as well as spatial variations. Inherent limitations are related to the use of standalone feedback
AC implementation commonly applied in modern ANR headset. In such systems the antinoise
signal is notoriously behind the primary disturbance in time. Accordingly, in demanding military
applications requirements on more advanced and effective ANR system designs prevail.
The achievable ANR performance in a feedforward system (FFS) is to a large extent determined
by the degree of coherence between the set of reference sensors and the set of error sensors (or
performance sensors). Accordingly, this thesis includes a number of coherence analysis that are
based on diffuse sound field measurements in a reverberant chamber and measurements conducted
onboard a CH47D Chinook helicopter. From these coherence analysis it can be concluded
that the CFFAC system with 10 reference sensors applied to pilot helmets potentially provides
approximately 25 dB noise reduction at 100 Hz decreasing to approximately 10 dB attenuation
at 900 Hz. Moreover, there is no apparent sign of saturation of the noise reduction with an
increasing number of reference sensors. Accordingly, by using more reference sensors the spatial
sampling rate is increased which in turn most likely also will lead to an increased ANR bandwidth.
The hybrid system is also constituted from a continuoustime feedback system (FBS) and a
discretetime FBS. The continuoustime FBS is primarily responsible for additional broadband
noise reduction, whereas the discretetime FBS primarily is responsible for the attenuation of
periodic signals.
Owing to the requirement on causal operation of a physical AC system time delays will also to a
large extent determine the achievable performance in FFS design and in particular in FBS design.
A quantity referred to as the spatiallyweightedaveraged acquisition lead time is introduced to
represent the averaged timeadvance obtained by each reference sensor relative to each performance
sensor involved in the proposed CFFAC system. A problem exist when one attempts to
model a physical spatially distributed system with no obvious input and output channel definition
by a finite lumpedelements multichannel system. Usually, no unique transfer function
x
exist as the system is not pointwise excited, but excited over an area as in the case of diffuse
sound field illumination.
A new method for acoustical signal processing that is referred to as jointchannel residual spectral
analysis (JCRSA) is developed. The JCRSA method is used for the extraction of joint signal
information from different observation positions in space. The idea is to separate each spectrum
in a coherent spectrum and a residual spectrum. The contents of the coherent spectrum can be
obtained from a linear superposition of the other signals, whereas the residual spectrum bears
information that is unique to each specific channel. In a specific example a system consisting of
10 reference sensors flushmounted on a Gentex HGU55/P helmet that in turn is mounted on a
head and torso simulator (HATS), is exposed to diffuse sound field illumination. By applying the
JCRSA method the spatiallyweightedaveraged acquisition lead times provided by the reference
sensors relative to the performance sensors are estimated to be as much as 800900μs.
The thesis also includes a detailed description of a new idea for a computational efficient implementation
of a multichannel system in which the adaptive filters for adaptive control as well as
the adaptive filters used for plant modeling are allowing to take different lengths.
A new and more general variant of the affine projection algorithm has been developed. This
adaptive filter algorithm that is denoted by multiplechannelαγΠaffine projection algorithm
includes parameters for both weightdriven and controleffortdriven leakage, adaptive tapweight
regularization as well as numerical regularization. A simplification of this algorithm leads to the
MCαγΠNLMS algorithm that is an extended variant of the NLMS algorithm.
Offline simultaneous system identification capabilities of a complex system involving a total 4
secondary paths, 20 feedback paths and 4 controlperformance paths is demonstrated. Different
adaptive filters and parameterizations hereof are examined.
A novel and general multirate adaptive filter for adaptive AC has been developed. Specifically,
a system involving 3 different sampling rates has been implemented and the results hereof are
presented. In this multirate system conversion take place at highly oversampled rates in order to
reduce the delays in the secondary paths. The nonadaptive control is performed at a somewhat
lower rate. Hereby, a compromise between delays related to the generation of the antinoise
signal and the computational load involved is ensured. Finally, the adaptive control that might
be computational intensive takes place at an even slower sampling rate hereby relaxing the
requirements on a high bandwidth. It is demonstrated that computational savings as high as
40% can be achieved in a 192, 24, 3 kHz triplerate system as compared with a 24 kHz singlerate
system without sacrificing the ANR performance.
It is common engineering practice to apply an assumption of Gaussian distributed signals. However,
many phenomena encountered in daily life fall into a generalization of the normal distribution
that is referred to as αstable distributions. Noise sources encountered in the domain of
AC are sometimes best fitted to the family of αstable distributions. This thesis includes a brief
technical introduction to the stable distributions and description of the adaptive filter that can
be used for AC.
Large parts of the HMIMOCFFFB system including the developed methods and algorithms have
been implemented in a realtime environment (RTE) that includes a signal processor. Test on the
helmet system will continue and a dedicated reference test unit (RTU) for AC is currently being
designed.
Original language  English 

Number of pages  911 

ISBN (Print)  9788791184857 
Publication status  Published  Nov 2008 
Fingerprint
Dive into the research topics of 'Foundations of Active Control  Active Noise Reduction Helmets'. Together they form a unique fingerprint.Projects
 1 Finished

Active Noise Concellation Headset
Elmkjær, T. H. L., Jacobsen, F., Laugesen, S., Rafaely, B., Sjøstrøm, S. O. & Jensen, S. H.
01/09/2001 → 24/11/2008
Project: PhD