Electrical audio signal processing systems and devices – Acoustical noise or sound cancellation – Counterwave generation control path
Reexamination Certificate
1998-08-18
2001-08-14
Mei, Xu (Department: 2644)
Electrical audio signal processing systems and devices
Acoustical noise or sound cancellation
Counterwave generation control path
Reexamination Certificate
active
06275592
ABSTRACT:
BACKGROUND
1. Field of the Invention
The object of the invention is a method defined in the preamble of claim
1
, an arrangement defined in the preamble of claim
5
for attenuating noise in a space by generating antinoise, and a mobile station defined in the preamble of claim
10
.
2. Description of the Prior Art
Noise absorbing and isolating materials are generally used for noise attenuation. In some rooms the material required for the attenuation occupies too much space or is otherwise difficult to locate. This has been the reason to develop active noise attenuation systems where the system measures the noise and supplies antinoise into the same room. The object is to use the antinoise to attenuate the noise caused by the noise source. In an ideal case the interference of the noise and the antinoise is zero.
There are known active adaptive noise attenuation systems which from a noise reference generate an antinoise signal to be supplied to a speaker. The operation of the system is adapted on the basis of the residual noise, so that the residual noise will be as low as possible. The residual noise is measured with an error microphone included in the system. The noise reference describes the unattenuated noise caused by the noise source, which is measured with a second microphone, or which is generated from the error signal obtained from the error microphone. Alternatively the noise reference is obtained with another transducer, such as an acceleration transducer which provides information about the noise source. Then the noise caused by the noise source is deduced from its movements.
The Filtered-X LMS (Least Mean Square) algorithm is the algorithm most commonly used in adaptive noise attenuation systems. The attenuation arrangement realised with the aid of this algorithm is shown in FIG.
1
. With the LMS algorithm the object is to minimise the power of the residual noise. The estimating filter
1
contains the estimate C′ of the acoustic response C of the space where the noise occurs. The acoustic response C of a space means that effect, which the space has on the sound supplied to the space. The signal r processed by the estimate filter
1
is supplied to the first input of the calculating unit
2
. The residual noise signal e is supplied to the second input of the calculating unit. The calculating unit contains the LMS algorithm. The calculating unit
2
calculates a control signal, which controls the adaptive filter
3
, whereby the calculation is based on the signals supplied to it and on predetermined constant values. The noise reference x is supplied to the input of the adaptive filter
3
. The calculating unit
2
and the adaptive filter
3
form together a digital unit
6
, which in the inputs and the outputs has A/D converters and D/A converters, respectively. The adaptive filter
3
is a digital filter, such as a FIR filter (Finite Impulse Response), whose coefficients are suitably modified by the calculating unit
2
. The adaptive filter
3
provides a speaker signal ka, which changes in the space
4
according to the acoustic response C and which is added
5
to the noise occurring in the space. This results in the error signal or the residual noise e, which is supplied to the second input of the calculating unit
2
.
When said algorithm is used the adaptive FIR filter supplies at its output
y[n]=w
0
[n]X[n] +w
1
[n]X[n−
1
] +w
2
[n]x[n−2]+ (1)
where x[n] is the input signal or the noise reference at the moment n, and the filter coefficients w
k
are updated according to the formula
w
k
[n+
1
]=w
k
[n]−
2
&mgr;e[n]r[n−k]
(2)
where n is the sampling moment of the digital filter, &mgr; is a constant step length, e is the error signal, and r is the filtered reference signal x, which is filtered by the electroacoustic response estimating filter. In the formulas k is a finite number series from zero to the positive limit. A more comprehensive description of adaptive signal processing is presented in Widrow B., Stearns S. D., Adaptive Signal Processing, Prentice-Hall, 1985.
A problem of the known adaptive noise attenuation systems is that there is a substantial amount of residual noise which can be heard, and that the power required for the sound pressure which is needed to generate the antinoise is high compared to the attenuation result.
SUMMARY OF THE INVENTION
The object of the invention is to obviate said disadvantages.
The method according to the invention is characterised in what is presented in claim
1
. The adaptive noise attenuation system according to the invention is characterised in what is presented in claim
5
. The mobile station according to the invention is characterised in what is presented in claim
10
. Preferred embodiments of the invention are presented in the dependent claims.
An object of the invention is a method for attenuating noise in a space by generating antinoise. According to an advantageous embodiment of the invention the method comprises the steps to:
determine the noise reference,
determine the weighting function,
determine the estimate function of the electroacoustic response of the space,
process the noise reference with the weighting function and with the estimate function of the electroacoustic response in order to generate a first signal,
measure the residual noise, which is formed as a result of the interaction between the noise prevailing in the space and the antinoise supplied into the space,
process the residual noise with the weighting function in order to generate a second signal,
filter the noise reference adaptively and supply the obtained speaker signal into the space, whereby the adaptive filtering is controlled based on the first signal and the second signal so that the second signal or the weighted residual noise is minimised, and the adaptively filtered signal is supplied as antinoise into the space.
The estimate function of the electroacoustic response is determined so that a test signal, such as 1/f-noise or white noise, is supplied to the D/A converter of the equipment, at the same time the signal obtained from the A/D converter connected to the error microphone is stored, the transfer function or the impulse response between the test signal and the measured signal is estimated, preferably by using an LMS algorithm, whereby the estimate filter C′ is realised as a digital FIR filter using filter coefficients which are obtained directly from the estimation. The coefficients of the FIR filter directly provide its impulse response. The use of the LMS algorithm is presented in the book: Widrow B., Stearns S. D., Adaptive Signal Processing, Prentice-Hall, 1985.
In a preferred embodiment of the invention the noise reference is generated so that the antinoise signal of the space's electroacoustic response is subtracted from the residual noise signal, when the antinoise signal is processed with the estimate function.
In an embodiment of the method for adaptive filtering of the noise reference the coefficients w
k
of the adaptive filter function are determined by the formula:
w
k
[n+
1
]=w
k
[n
]−2
&mgr;e
H
[n]r
H
[n−k]
(3)
where n is the sampling moment of the digital filter, &mgr; is a constant step length, e
H
is a second signal or the residual noise signal weighted with the weighting function, and r
H
is a first signal or the filtered reference signal x, which is filtered by the weighting function and the electroacoustic response estimate function. In one embodiment of the invention said weighting function, or the corresponding weighting filter, is a function which takes into account the frequency sensitivity of the human hearing, whereby it generates a maximum total attenuation of the noise at a frequency of substantially 1000 Hz.
An object of the invention is also a noise attenuation arrangement. According to an advanta
Mei Xu
Nokia Mobile Phones Ltd.
Perman & Green LLP
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