Adaptive beamforming for noise reduction

The invention provides an adaptive noise cancelling apparatus which operates to overcome a problem encountered in conventional noise cancelling circuitry when the signal-to-noise ratio at the sensor array is high--to wit, that the target signal is degraded, leading to poorer intelligibility. An apparatus constructed in accord with the invention selectively inhibits the adaptive filter from changing its filter values in these instances and, thereby, prevents it from generating a noise-approximating signal that will degrade the target component of the output signal.

BACKGROUND OF THE INVENTION 
This invention relates to adaptive signal processing and, more 
particularly, to adaptive noise cancelling apparatus. The invention has 
application in systems where it is desired to reduce interference from 
noise sources that are spatially separate from a target source, e.g., in 
hearing aids, automatic speech recognition systems, telephony and 
microphone systems. 
Adaptive signal processing systems are characterized by the capability to 
adjust their response in the face of changing, or time-variant, inputs. 
These systems are well suited to perform filtering tasks based on 
automatic "training" in which they continuously monitor their own 
previously-generated output signals to replace or remove specified 
components in presently-received input signals. While adaptive systems 
have broad applicability in areas such as prediction, modeling and 
equalization, of particular interest here is their application in 
interference cancelling, i.e., the removal of unwanted noise from input 
signals. 
The prior art offers a variety of noise cancelling circuits. Among these 
are adaptive beamforming systems, which use spaced arrays of sensors, 
e.g., microphones, to reduce interference. A simple system, known as the 
Howells-Appelbaum sidelobe cancler, for example, employs two 
omnidirectional sensors for receiving input signals generated by target 
and interference sources. The system filters one of the input signals, the 
"reference," through an adaptive element and subtracts it from the other, 
the "primary." The output signal resulting from this subtraction is fed 
back to the adaptive element which adjusts the filter to minimize the 
difference between the filtered reference and primary signals. As the 
filter converges, the signal-to-noise ratio of the output improves--at 
least when interference dominates the input. See, for example, Widrow et 
al, Adaptive Signal Processing, Prentice Hall (1985), at pp. 302, et seq. 
More complex beamforming systems proposed by Frost, and by Griffiths and 
Jim, among others, provide improved output signal-to-noise ratios under 
conditions where the input noise component is not dominant. See, Widrow et 
al, supra, and Griffiths, et al, "An Alternative Approach to Linearly 
Constrained Adaptive Beamforming," IEEE Transactions on Antennas and 
Propagation, vol. AP-30 (January 1982), at pp. 27, et seq. 
Unfortunately, even these systems lose their effectiveness when the input 
becomes dominated by the target itself, or when a target-free sample of 
noise is not available. Here, the prior art adaptive systems degrade the 
target signal, producing an output with a lower signal-to-noise ratio than 
the input. This deficiency becomes of real concern where such beamforming 
circuits are incorporated into hearing aids and other applications where a 
target-free reference signal is unavailable and the system must operate at 
high, as well as low, signal-to-noise ratios. 
In view of the foregoing, an object of this invention is to provide an 
improved adaptive beamforming system. 
More particularly, an object of this invention is to provide an adaptive 
beamforming system which operates effectively over all ranges of input 
signal-to-noise ratios. 
A further object of this invention is to provide an improved hearing aid 
which processes incoming signals using adaptive beamforming techniques and 
which continues to operate effectively even when there is relatively 
little interference in the input signals. 
SUMMARY OF THE INVENTION 
The aforementioned objects are attained by the invention, which provides, 
in one aspect, an adaptive noise cancelling apparatus which operates to 
overcome the problem encountered in conventional noise cancelling 
circuitry when the signal-to-noise ratio at the sensor array is high--to 
wit, that the target signal is degraded, leading to poorer 
intelligibility. In these instances, rather than allowing the adaptive 
filter to converge on filter values that degrade the target component of 
the output signal, a system constructed in accord with invention 
selectively inhibits adaptation, thereby preserving the target signal. To 
do this, the system takes advantage of momentary low signal-to-noise 
ratios, which are characteristic of human speech, for example, to converge 
to a desired filter response. 
In another aspect, the invention provides an adaptive noise cancelling 
apparatus including an array of spatially disposed sensors, each arranged 
to receive an input signal having target and noise signal components, and 
an element coupled to the array for combining one or more of those input 
signals to form a primary signal. Another generator element is also 
coupled to the array to process the input signals to generate one or more 
reference signals representing only noise components of the input signals. 
An adaptive filter produces a noise-approximating signal as a function of 
reference signals received over time and feeds that noise-approximating 
signal to an output element, which subtracts it from the primary to 
produce an output approximating the target signal. 
A feedback path, including an adaptation controller, is coupled between the 
output elemebnt and the adaptive filter. The controller generates an 
adaptation signal as a function of the output signal and an SNR signal, 
which the controller generates from the input signals. More particularly, 
the controller is coupled with the sensor array for processing one or more 
of the input signals to generate the SNR signal as representative of the 
relative strength, over a short time, of the target signal to the noise 
signal. In one aspect, this SNR signal represents a cross-correlation 
between input signals received by two or more of the sensors. 
The adaptative filter is coupled with the adaptation controller to receive 
the adaptation signal and to selectively modify the noise-approximating 
signal to minimize a difference between it and the primary signal. By 
providing that modified noise-approximating signal to the output element, 
the latter is able to generate an output signal more closely matching the 
target signal. 
In one embodiment, the invention can provide an adaptive noise canceler of 
the type described above in which the adaptation controller includes a 
threshold detection element which generates a zero-valued adaptation 
signal if the SNR signal is in a first selected range, and for generating 
an adaptation signal which is equivalent to the output signal if the SNR 
signal is in a second selected range. In another embodiment, the 
adaptation controller can include a sliding scale element which generates 
an adaptation signal that varies with the SNR signal. 
The adaptive noise cancelers of the present invention can further include 
filters within the adaptation controller for providing selected linear 
filterings of at least certain ones of the received input signals. 
According to another aspect of the invention, those filterings can be 
selected in accord with a range of expected delays in noise signal 
components received by selected ones of said sensor elements. 
These and other aspects of the invention are evident in the drawings and in 
the detailed description which follows.

DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENT 
FIG. 1 depicts a two-microphone adaptive noise cancelling system 10 
constructed in accord with the invention. The illustrated system 10 
includes a receiving array 12, sampling elements 13a, 13b, a primary 
signal generator 14, a reference signal generator 16, an adaptive filter 
18, an output element 20, and an adaptation controller 22. 
Receiving array 12 includes two sensors, e.g., microphones, 12a, 12b, 
spaced apart by a distance x and arranged to receive input signals having 
signal components from a target source 26 and noise sources 28a, 28b. In 
the illustrated embodiment, delays 24a, 24b are connected with the sensors 
12a, 12b to steer the array 12, i.e., to delay input signals 
differentially to insure that target signal components received in the 
"look" direction y are in phase. 
Sampling elements 13a, 13b sample the input-representative signals 
generated by array 12 and pass the sampled inputs on to other elements of 
the illustrated system. The sampling elements 13a, 13b are discussed in 
further detail below. 
Primary signal generator 14 receives input signals from the sampling 
elements 13a, 13b over conductor lines 30a, 30b and generates a primary 
signal representative of a selected combination of those input signals. In 
a preferred embodiment, generator 14 comprises a summation element 32 for 
adding the input signals, as well as a filter element 34, which may 
include a delay to simulate non-causal impulse responses of the adaptive 
filter. The primary signal is transmitted from the generator 14 to the 
output element over conductor line 35. 
The reference signal generator 16 also receives input signals from the 
samplers 13a, 13b over conductor lines 30a, 30b to produce a reference 
signal representing components of the noise signal. The illustrated 
generator 16 produces that reference signal by subtracting input signals 
received by one sensor 12b from those received by the other 12a. Output 
from the reference signal generator 16 is transmitted to the adaptive 
filter 18 over conductor line 36, as indicated in the drawing. 
The adaptive filter 18 generates a signal which approxmates the value of 
the noise signal. This approximation is based on the noise component 
signals received from the reference signal generator 16 over a selected 
period of time. For this purpose, the illustrated filter 18 includes a 
tapped delay line 38 having a plurality of "taps," or stores, which retain 
values of reference signals generated during the past L timing intervals, 
where L is referred to as the length of the adaptive filter. The tapped 
delay line 38 also includes a set of weighting elements 40a, 40b, . . . , 
40c which store mathematical weights associated with each of the L taps. A 
linear combiner 42 is coupled to the taps and to the weighting elements 
for generating the noise-approximating signal as a sum of the 
multiplicative products of each of the stored reference signals and the 
associated weights. That noise-approximating signal is transmitted to the 
output element 20 over line 46. 
Output element 20 generates an output signal, representing the signal 
generated by the target 26, by subtracting the primary signal, received 
over conductor line 35, from the noise-approximating signal, received over 
line 46. In a preferred hearing-aid embodiment, that output signal can be 
passed over line 47 to a digital-to-analog converter, a low-pass filter 
48, an amplifier 50, and a speaker 52 to provide an audible signal 
suitable for the hearing-aid user. The output signal is also routed over 
line 47 to the adaptation controller 22. 
The adaptation controller 22 processes input signals received over lines 
30a, 30b to generate an SNR signal representing a relative strength of the 
target signal to the noise signal. In the illustrated system, the SNR 
signal is produced by first passing each of the sampled input signals 
through fixed linear filters 54a, 54b, selected according to the range of 
expected delays in the noise signal components received by the sensors 
12a, 12b. 
The outputs of filters 54a, 54b are then passed to an element 56 which, in 
accord with a preferred embodiment, generates the SNR signal from a 
running cross-correlation of the filtered input signals. Through the 
element 56 can produce the SNR signal by multiplying the values 
represented by the filtered input signals, preferably, it simply estimates 
the cross-correlation by multiplying the polarity of those inputs. 
In the illustrated embodiment, the SNR sgnal is passed to a threshold 
detection element 58 which generates an adaptation signal having a value 
of zero if the SNR signal is in a first selected range and having a value 
equal to that of the output signal (received over line 47) if the SNR 
signal is in a second selected range. Where the SNR signal represents an 
estimate of the input signal cross-correlation--as opposed to another 
estimate of target signal strength to noise signal strength--a zero-valued 
adaptation signal is generated in response to a cross-correlation signal 
having a value above a preselected threshold, and an output 
signal-equivalent adaptation signal otherwise. 
In another preferred embodiment, the adaptation element 22 can include a 
sliding scale element which generates an adaptation signal having a value 
which varies, e.g., monotonically, with the SNR signal. 
The adaptation signal generated by the adaptation controller 22 is 
transmitted to modification element 44 over conductor line 60. Element 44 
adjusts the weight-representative signals in response to that adaptation 
signal to minimize a difference between the noise-approximating signal and 
the primary signal. 
A fuller appreciation of the operation of the adaptive noise canceler 10 
may be understood as follows. The sensor array 12 receives input signals 
generated by the target source 26 and the noise source 28. As a result of 
the positioning of the sensors, and/or the delays effected by the steering 
elements 24a, 24b, the array 12 produces input-representative signals 
having target signal components which are nearly in phase and noise signal 
components which are substantially out of phase. 
Generator 14 combines the input signals to produce a primary signal, having 
both target and noise components, which is a sum of the input signals. 
Simultaneously, generator 16 subtracts the input signals from one another 
to produce a reference signal having predominantly noise components. The 
reference signal is fed into the adaptive filter 18 which produces a 
noise-approximating signal based on a weighted sum of current and past 
values of the reference signal. 
Subtracting this noise-approximating signal from the primary signal, output 
element 20 produces an output signal approximating the target signal. 
To improve the quality of the output signal, the adaptive filter 18 
continuously monitors the adaptation signal, generated by controller 22, 
to determine if the weighting values require adjustment. In this regard, 
it will be appreciated that the power of the output signal falls to a 
minimum when that signal contains only target signal components. 
To prevent degradation of the target signal when it dominates the 
beamformer input, the illustrated adaptation controller 22 reduces the 
adaptation signal to zero when it determines that the cross-correlation of 
the input signal is high. The filter 18 interprets that zero-valued signal 
as an indication that the input target-to-noise ratio is high and, 
accordingly, freezes the current weight values. Where, on the other hand, 
the cross-correlation is low, the controller 22 generates an adaptation 
signal equal in value to the output signal, so that the filter 18 can 
further adjust the weights, if necessary, to minimize the power output. 
In this light, it is clear that the filters 54a, 54b function to pass those 
frequencies of the input signals which are most likely to indicate the 
presence of noise, i.e., those which will experience the greatest 
decorrelation given the particular spacing of the sensors 12a, 12b. 
A further understanding of the operation of a preferred embodiment of the 
beamforming system 10 may be attained by reference to FIG. 2 and to the 
chart below, which together present in mathematical from the values of 
signals generated by the system components. The circuit of FIG. 2 is 
similar to that of FIG. 1 and, accordingly, uses like element 
designations. 
In FIG. 2, the value of signals transmitted between components are denoted 
adjacent the conductor lines connecting those components. A more complete 
expression of those values is given in Table 1, below. Thus, for example, 
input signals passed from the sensor array 12 to the primary signal 
generator 14 and the reference signal generator 16 are denoted m.sub.1 [n] 
and m.sub.2 [n]. Upon processing by summation element 32 of the primary 
signal generator 14, the input signals are combined to form the primary 
signal, s[n], which Table 1 indicates as having a value equal to one-half 
the sum of the sensor signals, i.e., (m.sub.1 [n][m.sub.2 [n])/2. The 
remaining signal values shown in the drawing can be interpreted in a like 
manner. 
TABLE 1 
______________________________________ 
Signal Value/Description 
______________________________________ 
d[n] 1/2 .times. (m.sub.1 [n] - m.sub.2 [n]) 
f.sub.j [n] 
the sum of (m.sub.j [n - i] .times. g.sub.i), for i = to N - 1, 
and 
for j = 1, 2 
m.sub.1 [n] 
input-representative signal from sensor 12a 
m.sub.2 [n] 
input-representative signal from sensor 12b 
r[n] 0.99 .times. r[n - 1] + 0.01 .times. f[n], where 
f[n] = +1, if f.sub.1 [n] .times. f.sub.2 [n] &gt; 0, and 
f[n] = -1, if f.sub.1 [n] .times. f.sub.2 [n] &lt; 0 
v[n] the sum of (d[n - k] .times. w.sub.k [n]), 
for k = 0 to (L - 1) 
s[n] 1/2 .times. (m.sub.1 [n] + m.sub.2 [ n]) 
t[n] 0, if r[n] &gt; threshold constant, and 
y[n], if r[n] &lt; threshold constant 
y[n] s[n - (L - 1)/2] - v[n], for odd values of L 
______________________________________ 
In Table 1 and FIG. 2, bracket notation is used to denote the value of each 
signal at specific time intervals. Thus m.sub.1 [n], m.sub.2 [n] and y[n] 
represent input and beamformer output sgnal values, respectively, at 
timing interval n, where n is an integer. It will be noted that the signal 
output by element 34 also includes a time component; however, unlike that 
of the other system elements, the element 34 output is delayed (L-1)/2 
timing intervals, a time period equal to roughly half the length of the 
adaptive filter 16. Those skilled in the art will appreciate that such a 
delay simulates a non-causal impulse response; that is, it permits the 
adaptive filter 18 to employ values of the reference signal d[n] received 
both before and after the primary signal. 
Consistent with the above notation, the modification element 44 (FIG. 1) 
adjusts the weights used in the adaptive filter 18 in accord with an 
unconstrained least squares algorithm and based upon a power value q[n] 
equal to 0.9941.times.p[n-1]+0.0059.times.p[n], where p[n] is equal to 
(y[n]).sup.2 +(d[n]).sup.2 ; a weight-delta value D[n] equal to 
2.times.A.times.(t[n])/(L.times.(q[n])); and weight update values W.sub.k 
[n+1] equal to W.sub.k [n]+(D[n]).times.(d[n-k]), where W.sub.k represents 
a weight associated with a kth tap in delay line 38 and where k is an 
integer between 0 and (L-1). 
A preferred beamforming system 10 intended for use in a hearing aid, 
assuming a sampling frequency of 10 kHz, has an adaptive filter length, L, 
between 5 and 500 samples, with a preferred value of 169; a correlation 
filter length, N, between 5 and 500, with a preferred value of 100; an 
adaptation constant, A, between 0.005 and 0.5, with a preferred value of 
0.05; and a threshold constant between -0.5 and +0.5, with a preferred 
value of 0.0. 
In a preferred embodiment, the beamforming system 10 is implemented using 
two Motorola DSP56000ADS signal processing boards: one for performing the 
functions of the primary signal generator 14, the reference signal 
generator 16, the adaptive filter 18 and the output element 20; and the 
other, for performing the functions of the adaptation element 22. 
The aforementioned system 10 employs a digital-to-analog converter 51 
interposed between the output element 20 and low-pass filter 48. The 
system also employs sampling elements 13a, 13b of the type depicted in 
FIG. 3 for converting incoming target and noise signals to digital form. 
Referring to FIG. 3, samplers 13a, 13b include, respectively, amplifiers 
64a, 64b, low-pass filters 66a, 66b and analog-to-digital converters 68a, 
68b. Each samplers 13a, 13b is coupled to a microphone 12a, 12b (FIG. 1) 
and preamplifier (not shown) of the array 12 (FIG. 1). Amplified 
input-representative signals, generated by amplifiers 64a, 64;I b, are 
filtered through low-pass filters 66a, 66b, selected to pass target and 
noise signal frequencies less than one-half the sampling frequency. 
Filtered input signals from both illustrated channels are sampled by 
analog-to-digital converters 68a, 68b, which are driven by external clock 
70. The digital outputs of the converters 68a, 68b are passed, via lines 
30a, 30b, respectively, to the primary signal-generator 14, reference 
signal-generator 16, and adaptation controller 22 for processing in the 
manner described above. 
In a preferred embodiment intended for use in conjunction with a hearing 
aid, the low-pass filters 66a, 66b are selected to pass frequencies below 
4.5 kHz, and the sampling rate of the A/D converters 68a, 68b is set at 10 
kHz. 
The above teachings can be applied, more generally, to an (M-1) sensor 
beamforming system constructed and operated in accord with the invention, 
where M is an integer greater than or equal to two. One such system is 
depicted in FIG. 4. The illustrated system 80 includes a receiving array 
82, a primary signal generator 84, (M-1) beamforming sections 86.sub.1, 
86.sub.2, . . . 86.sub.M-1, and output element 88. Each beamforming 
section includes a reference signal generator 92.sub.1, 92.sub.2, . . . 
92.sub.M-1, an adaptive filter (which can include a modification element, 
now shown) 94.sub.1, 94.sub.2, . . . 94.sub.M-1, and a adaptation 
controller 96.sub.1, 96.sub.2, . . . 96.sub.M-1. These elements are 
constructed and operated in accord with the teachings of similarly-named 
elements shown in FIGS. 1 and 2, described above. 
Particularly, receiving array 82 includes a plurality of sensors 82.sub.1, 
82.sub.2, . . . 82.sub.M-1, 82.sub.M, each having a corresponding steering 
delay 90.sub.1, 90.sub.2, 90.sub.3, . . . 90.sub.M-1, 90.sub.M. As 
illustrated, the outputs of the array 82 are passed to the primary signal 
generator 84. Likewise, the outputs of pairs of those sensors are passed 
to the reference signal generators 92.sub.1, 92.sub.2, . . . 92.sub.M-1 
and to the adaptation controllers 96.sub.1, 96.sub.2, . . . 96.sub.M-1. 
As above, the reference signal generators and adaptation controllers pass 
their output--representative, respectively, of reference and adaptation 
signals corresponding to associated pairs of the sensors--to corresponding 
adaptive filters (and modification element) 94.sub.1, 94.sub.2, . . . 
94.sub.M-1. These adaptive filters produce noise-component approximating 
signals which approximate the noise signal components received from the 
associated sensor pairs based on a time-wise sample of those components. 
The output of the filters 94.sub.1, 94.sub.2, . . . 94.sub.M-1 are routed 
to the output element 88, which subtracts them from the primary signal, 
thereby producing an output signal matching the target signal. 
The foregoing describes improved adaptive beamforming systems which can be 
constructed using a plurality of sensors to reduce interference from noise 
sources that are spatially separate from a target source. These improved 
systems operate effectively over all ranges of input signal-to-noise 
ratios and, unlike prior art systems, do not suffer target signal 
degradation when input signal-to-noise ratios are high. 
Those skilled in the art will appreciate that the illustrated embodiments 
described above are exemplary only, and that modifications, additions and 
deletions can made thereto without falling outside the scope or spirit of 
this invention: for example, that at least portions of the systems 
described above can be constructed to process analog, as well as digital, 
signals; that the SNR signals can be generated as a function of the input 
received from one, as well as many, sensors; that the adaptation 
controller can employ a combination of threshold and sliding scale 
elements; and that the adaptive filter can employ any of a number of known 
weight-modification algorithms, in addition to the unconstrained least 
squares algorithm.