Adaptive array control device, method and program, and adaptive array processing device, method and program

[Object] By enabling accurate coefficient update, a high-quality array processing output which is less influenced by frequency characteristics and incoming directions of input signals control can be acquired, irrespective of the frequency characteristics and incoming direction of the input signals. [Achieving Means] Identification information of a target signal and interference by amplitude is corrected according to identification information of the target signal and the interference by phase, and with use of the correction result, identification of the target signal and the interference is performed. More specifically, an identification information generation section according to phase, a correction signal generation section, and a correction section are provided.

This applications is based upon and claims the benefit of priority from Japanese patent applications No. 2006-117289, filed on Apr. 20, 2006, the disclosure of which is incorporated herein in its entirety by reference.

TECHNICAL FIELD

The present invention relates to an adaptive array control device, a method and their program, and an adaptive array processing device, a method, and their program. In particular, the present invention relates to an adaptive array control device, method and program for receiving signals with directivity using a plurality of sensors, and an adaptive array processing device, method, and its program.

In the field of audio signal acquisition, sonars, and wireless communications, a speech enhancement device by means of an adaptive microphone array and a wireless transceiver by means of an adaptive antenna array have been known, for example. Such a device is capable of enhancing and receiving only a particular signal from a plurality of signal sources, which is an application of an adaptive array technique. As sensors, microphones, ultrasonic sensors, sonar receivers, and radio wave antennas may be used.

Here, a case of using microphones as sensors will be described.

Hereinafter, in order to simplify the description, a case where microphones are arranged on a line at equal interval will be considered. Further, it assumes that a target audio source is sufficiently distant from the line on which the microphones are arranged, and that the direction of the target audio source is orthogonal to the line.

A microphone array filters signals input to a plurality of microphones, and then adds them to form a spatial filter. With this spatial filter, only a signal incoming from a predefined direction, or a switch target signal, is enhanced, and signals other than the target signal are attenuated. An adaptive microphone array is an array of microphones having a function of adaptively varying the spatial filter characteristics. As a configuration of an adaptive microphone array, a “generalized sidelobe canceller” disclosed in Non-Patent Document 1, the configuration disclosed in Non-Patent Document 2, the configuration disclosed in Non-Patent Document 3, the “frost beamformer” disclosed in Non-Patent Document 4, and the configuration disclosed in Non-Patent Document 5, have been known, for example.

A generalized sidelobe canceller, which is a basic adaptive array processing device disclosed in Non-Patent Document 1, includes a fixed beamformer, a blocking matrix circuit, and a multi-input canceller. The blocking matrix circuit includes an adaptive blocking matrix circuit including adaptive filters. The fixed beamformer processes a plurality of sensor signals and enhances a target signal. The blocking matrix circuit suppresses the target signal included in the plurality of sensor signals, and relatively enhances interferences.

The adaptive blocking matrix circuit subtracts a pseudo target signal generated by the adaptive filters from the plurality of the sensor signals with the fixed beamformer output being used as a reference signal, and supplies to a multi-input canceller. The adaptive filter coefficient of the adaptive blocking matrix circuit is to be updated so as to minimize an output of the adaptive blocking matrix circuit with use of the fixed beamformer output and an output of the adaptive blocking matrix circuit.

The multi-input canceller subtracts a pseudo interference generated by the adaptive filters from the fixed beamformer output with an output of the blocking matrix circuit being used as a reference signal. In the signal obtained by the subtraction processing, the target signal is enhanced and the interference is suppressed, which becomes an array display output. Through the subtraction processing, correlation of the output signal with respect to the interference is eliminated. The adaptive filter coefficient of the multi-input canceller is updated to minimize the multi-input canceller output using the blocking matrix circuit output and the multi-input canceller output.

As the fixed beamformer, a delay-and-sum beamformer which delays respective sensor signals and adds them, a filter-and-sum beamformer which filters and adds them, may be used. Those fixed beamformers are described in Non-Patent Document 6 in detail.

The delay-and-sum beamformer delays a plurality of sensor signals for only the unique number of samples of each signal, and after multiplying a unique coefficient by each signal, calculates the sum and outputs it. The delay time of each signal is set such that after each sensor signal is delayed, the phases of the target signal included therein will become the same. Consequently, the target signal included in the output of the delay-and-sum beamformer is enhanced.

On the other hand, for the interference incoming from a direction different from that of the target signal, as the phases are different from each other in the respective delayed signals, the interferences are offset each other by addition and attenuated. As such, in the output of the delay-and-sum beamformer, the target signal is enhanced and the interferences are attenuated. The filter-and-sum beamformer has a configuration such that delaying and constant multiplying with respect to sensor signals in the delay-and-sum beamformer are replaced with filters. Those filters can be made such that effects of delaying and constant multiplying in the delay-and-sum beamformer differ with respect to respective frequencies. As such, the target signal enhancing effect is more enhanced compared to that of the delay-and-sum beamformer with respect to signals in which spectrum is not flat.

The adaptive blocking matrix circuit and the multi-input canceller include a plurality of adaptive filters. As such adaptive filters, structures of FIR filters, IIR filters, and lattice filters may be used. Further, as a coefficient update algorithm of those adaptive filters, NLMS algorithm (learning identification method or normalized LMS algorithm), RLS algorithm (sequential minimum square method), a projection algorithm, a gradient method, an LS algorithm (minimum square method), a block adaptive algorithm, and adaptive algorithm of transform region may be used. Further, when performing coefficient updating, a tap coefficient constraint adaptive algorithm applying constraint to a coefficient value to be newly calculated, a leak adaptive algorithm, and a tap norm constraint adaptive algorithm applying constraint to a coefficient value norm may be used. As those coefficient update algorithms with constraint are described in Non-Patent Document 7 in detail, the description is omitted.

In the coefficient update of the adaptive blocking matrix circuit, the enhanced interference becomes an unnecessary signal for coefficient update, and in the coefficient update of the multi-input canceller, the enhanced target signal becomes an unnecessary signal for coefficient update, both of which disturb coefficient update. As such, in either case, the adaptive filter coefficient is disturbed, so that uncomfortable breathing noises are caused in the output signal of the array processing device. In order to prevent the noises, it is necessary to make the coefficient update step size small. However, a small step size causes a delay of the speed with which the characteristics of the adaptive blocking matrix circuit follows the movement of the target signal, so that the quality of the adaptive array device output which is the final output is deteriorated. In order to solve this problem, adaptive mode control devices are disclosed in Non-Patent Documents 8 and 9.

In the method disclosed in Non-Patent Document 8, presence of the interference is detected using correlation between signals obtained from adjacent sensors. By halting coefficient update when the interference is detected, a fine output of the adaptive array device can be obtained. In this method, as it is developed to be applied for hearing aid, microphone intervals are wide, and the signal band is restricted from about 600 Hz to 1,200 Hz in order to prevent spatial aliasing. In an application of using normal audio signals, as the audio power may sometimes also be present outside this frequency range, presence of interferences cannot be detected accurately. Further, as it is configured to control coefficient update of only multi-input canceller while assuming a fixed blocking matrix circuit, it cannot be directly applied to the adaptive blocking matrix circuit.

In the method disclosed in Non-Patent Document 9, presence of interference is detected using a power ratio of the target signal to the interference (SIR). The power estimation of the target signal is performed using a fixed beamformer output. The power estimation of the interference is performed using an output of the adaptive blocking matrix circuit. The ratio of these estimation values (that is, estimation values of SIR) is compared with a threshold. If SIR is larger than the threshold, as the target signal is prevailing in the input signal and effects of the target signal are small, coefficient update will be performed in the adaptive blocking matrix circuit. In contrast, as the target signal interrupts coefficient update of the multi-input canceller, coefficient update of the multi-input canceller is halted. If SIR is smaller than the threshold, the coefficient update is halted in the adaptive blocking matrix circuit, and coefficient update is performed in the multi-input canceller.

In this method, the adaptive blocking matrix circuit does not exhibit sufficient performance until the adaptive filter coefficient included in the adaptive blocking matrix circuit is converged, so that estimation of the interference power becomes inaccurate. As such, particularly in the initial timing of operation, errors may be easily caused in the coefficient update control of the adaptive blocking matrix circuit and the multi-input canceller, leading to deterioration in the output audio of the array processing device. In order to solve this problem, Non-Patent Document 10 discloses an adaptive mode control means having a dedicated fixed blocking matrix circuit.

In the method disclosed in Non-Patent Document 10, power estimation of interference is performed using a dedicated fixed blocking matrix circuit. As such, desired performance can be achieved irrespective of the convergence of the adaptive filter coefficient included in the adaptive blocking matrix circuit, which enables accurate interference power estimation.

FIG. 31shows a configuration in which the adaptive array processing device disclosed in Non-Patent Document 9 is combined with the adaptive mode control device disclosed in Non-Patent Document 10. The adaptive array processing device disclosed in Non-Patent Document 9 includes a fixed beamformer200, an adaptive blocking matrix circuit300, a delay element400, and a multi-input canceller500. Further, the adaptive mode control device includes a blocking matrix circuit310, an SIR estimation section700, and a comparator section800.

The fixed beamformer200processes signals obtained from M pieces of sensors1000to100M−1to thereby enhance a target signal. The adaptive blocking matrix circuit300suppresses the target signal included in the plurality of sensor signals, and relatively enhances interference. This is achieved by generating pseudo target signals by a plurality of adaptive filters with an output of the fixed beamformer200being used as a reference signal, and subtracting them from signals obtained from M pieces of the sensors1000to100M−1. The coefficient of the adaptive filter is updated such that an output of the adaptive blocking matrix circuit300is minimized, by using an output of the fixed beamformer200and an output of the adaptive blocking matrix circuit300.

The delay element400delays an output of the fixed beamformer200by L sample, and supplies it to the multi-input canceller500. The value of L is set such that the phases of the target signal component in the output of the delay element400and the target signal component in the output of the adaptive blocking matrix circuit300become the same. For example, it may be set to the sum of the group delay time of the fixed beamformer200and a time corresponding to about one fourth to a half of the number of taps of the adaptive blocking matrix circuit300.

The multi-input canceller500receives and performs processing on a signal formed by delaying the output signal of the fixed beamformer200and an output signal of the adaptive blocking matrix circuit300to thereby suppress interference, and further enhances the target signal relatively. The multi-input canceller500receives the enhanced interference as a reference signal from the adaptive blocking matrix circuit300, and as a signal correlated to this signal, generates a pseudo interference by adaptive filters. The generated pseudo interference is subtracted from the enhanced target signal which is an output of the delay element400. This output is transmitted to the output terminal600. The adaptive filter coefficient of the multi-input canceller500is updated, using the output of the adaptive blocking matrix circuit300and the output signal transmitted to the output terminal600, so as to minimize the output signal.

The output of the adaptive blocking matrix circuit300to be used in coefficient update of the adaptive blocking matrix circuit300includes interference and a suppressed target signal. However, as the adaptive blocking matrix circuit300can affect only the target signal component, the interference is output as it is. In other words, the adaptive blocking matrix circuit300can minimize only the target signal component, and the interference component included in this output disturbs coefficient update. With the disturbing, the adaptive filter coefficient included in the adaptive blocking matrix circuit300is disordered, so that the signal transmitted to the multi-input canceller500becomes unstable. As a result, the output of the multi-input canceller500, that is, the output of the entire adaptive array device, is disturbed, causing uncomfortable breathing noises. In order to prevent the noises, SIR is estimated using the plurality of sensor signals, and the coefficient update of the adaptive blocking matrix circuit300is controlled using the estimated value.

Similarly, the target signal enhanced in the coefficient update of the multi-input canceller500becomes an unnecessary signal for coefficient update, disturbing the coefficient update. With the disturbing, the adaptive filter coefficient included in the multi-input canceller500is disordered, causing uncomfortable breathing noises in the adaptive array device output. As such, same as the adaptive blocking matrix circuit300, SIR of the plurality of sensor signals is estimated, and coefficient update of the multi-input canceller500is controlled with the estimated value.

The SIR estimation section700performs SIR estimation using the output of the blocking matrix circuit310and the output of the fixed beamformer200. Power estimation of the target signal is performed using the output of the fixed beamformer. Power estimation of the interference is performed using the output of the fixed blocking matrix circuit. The two estimate values are supplied to the SIR estimation section700, and the ratio is calculated to serve as an estimated SIR value. The estimated SIR value is transmitted from the SIR estimation section700to the comparator section800. The comparator section800compares the estimated SIR value with a threshold.

If the estimated SIR value is larger than the threshold, as the target signal is prevailing in the input signal so that effect of the interference is small, a control signal for performing coefficient update in the adaptive blocking matrix circuit is generated, and the signal is supplied to the adaptive blocking matrix circuit300. In contrast, as the target signal disturbs in the coefficient update of the multi-input canceller500, a control signal for halting coefficient update of the multi-input canceller is generated, and the signal is supplied to the multi-input canceller500. If the estimated SIR value is smaller than the threshold, coefficient is halted in the adaptive blocking matrix circuit, and a signal for performing coefficient update in the multi-input canceller is generated and supplied to the adaptive blocking matrix circuit300and the multiple input canceller500, respectively.

The blocking matrix circuit310and the SIR estimation section700configures an identification information generation section810. The SIR is a ratio of the target signal power and the interference power, and calculating the SIR corresponds to generating identification information of the target signal and the interference by amplitude. By comparing the identification information with the threshold, it is identified whether a target signal is prevailing or interference is prevailing. In other words, the identification information generation section810generates identification information by amplitude.

FIG. 32shows an exemplary configuration of the blocking matrix circuit310, which is configured of a subtractor311for calculating the difference between the ithsensor signal Xi(k) and the (i+1)thsensor signal Xi+1(k). Here, k is an indicator showing the time, and i is an integer in a range from 0 to M−2. The output signal z(k) of the blocking matrix circuit310becomes Xi(k)−Xi+1(k). With respect to the target signal incoming from the front, z(k)=0 is established because Xi(k) and Xi+1(k) are equal. With respect to interference incoming from another direction, z(k) is not zero. As such, the blocking matrix circuit310has an advantage of suppressing the target signal.

Non-Patent Document 3: THE TRANSACTIONS OF THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS A, VOL. 79, NO. 9, PP. 1516-1524, September 1996

DISCLOSURE OF THE INVENTION

Problems to be Solved by the Invention

In order to prevent distortion, the maximum interval between sensors, determined by the wavelength and the sound speed, is set. Further, the value of the number of pieces M of sensors also has an upper limit, practically. As such, the frequency characteristics of the fixed blocking matrix circuit which performs power estimation of interference are not flat, and also, selectivity based on directions is not enough. Accordingly, with the conventional art including that shown inFIG. 31, an error may not be avoidable in the power estimation depending on the frequency characteristics and incoming direction of interference, causing performance deterioration due to an inappropriate coefficient updating control of the adaptive array processing device.

It is an object of the present invention to provide an adaptive array processing device, an adaptive array processing method, and their program, which enables an accurate coefficient updating control irrespective of frequency characteristics and incoming directions of input signals to thereby acquire high-quality array processing outputs which are less influenced by frequency characteristics of input signals and directions of a target signal and interference.

Means for Solving the Problems

In order to achieve the above object, an adaptive array control device according to the present invention includes: a first identification information generation section which applies first array processing to signals acquired in a plurality of sensors arranged in an array and calculates a relative ratio between a target signal and interference based on phase information to thereby acquire first identification information; a correction signal generation section which generates a correction signal, using the first identification information, for performing larger correction when target signal power is higher than interference power; a second identification information generation section which calculates a relative ratio between the target signal and the interference based on amplitude information to thereby acquire second identification information; a correction section which corrects the second identification information according to the correction signal to thereby acquire corrected identification information; and a control section which controls speed and accuracy of parameter adjustment in adaptive array processing using the corrected identification information.

In order to achieve the above object, an adaptive array controlling method according to the present invention includes: applying first array processing to signals acquired in a plurality of sensors arranged in an array and calculating a relative ratio between a target signal and interference based on phase information to thereby acquire first identification information; generating a correction signal, using the first identification information, for performing larger correction when target signal power is higher than interference power; calculating a relative ratio between the target signal and the interference based on amplitude information to thereby acquire second identification information; correcting the second identification information according to the correction signal to thereby acquire corrected identification information; and controlling speed and accuracy of parameter adjustment in adaptive array processing using the corrected identification information.

In order to achieve the above object, an adaptive array controlling program causes a computer to perform functions of: applying first array processing to signals acquired in a plurality of sensors arranged in an array and calculating a relative ratio between a target signal and interference based on phase information to thereby acquire first identification information; generating a correction signal, using the first identification information, for performing larger correction when target signal power is higher than interference power; calculating a relative ratio between the target signal and the interference based on amplitude information to thereby acquire second identification information; correcting the second identification information according to the correction signal to thereby acquire corrected identification information; and controlling speed and accuracy of parameter adjustment in adaptive array processing using the corrected identification information.

In order to achieve the object, an adaptive array processing device according to the present invention includes: a sixth array processing section which enhances a target signal with respect to other signals to thereby acquire a sixth array-processed signal; a seventh array processing section which attenuates the target signal with respect to other signals to thereby acquire a seventh array-processed signal; a correlation elimination section which eliminates a signal component correlated to the seventh array-processed signal from the sixth array-processed signal and outputs the sixth array-processed signal; a first identification information generation section which applies first array processing to signals acquired in a plurality of sensors arranged in an array and calculates a relative ratio between the target signal and interference based on phase information to thereby acquire first identification information; a correction signal generation section which generates a correction signal, using the first identification information, for performing larger correction when target signal power is higher than interference power; a second identification information generation section which calculates a relative ratio between the target signal and the interference based on amplitude information to thereby acquire second identification information; a correction section which corrects the second identification information according to the correction signal to thereby acquire corrected identification information; and a control section which controls speed and accuracy of parameter adjustment in adaptive array processing using the corrected identification information.

In order to achieve the above object, an adaptive array processing method according to the present invention includes: enhancing a target signal with respect to other signals to thereby acquire a sixth array-processed signal; attenuating the target signal with respect to other signals to thereby acquire a seventh array-processed signal; when eliminating a signal component correlated to the seventh array-processed signal from the sixth array-processed signal and outputting the sixth array-processed signal, applying first array processing to signals acquired in a plurality of sensors arranged in an array and calculating a relative ratio between the target signal and interference based on phase information to thereby acquire first identification information; generating a correction signal, using the first identification information, for performing larger correction when target signal power is higher than interference power; calculating a relative ratio between the target signal and the interference based on amplitude information to thereby acquire second identification information; correcting the second identification information according to the correction signal to thereby acquire corrected identification information; and controlling speed and accuracy of parameter adjustment in adaptive array processing using the corrected identification information.

In order to achieve the above object, an adaptive array controlling program causes a computer to perform functions of: enhancing a target signal with respect to other signals to thereby acquire a sixth array-processed signal; attenuating the target signal with respect to other signals to thereby acquire a seventh array-processed signal; eliminating a signal component correlated to the seventh array-processed signal from the sixth array-processed signal and outputting the sixth array-processed signal; applying first array processing to signals acquired in a plurality of sensors arranged in an array and calculating a relative ratio between the target signal and interference based on phase information to thereby acquire first identification information; generating a correction signal, using the first identification information, for performing larger correction when target signal power is higher than interference power; calculating a relative ratio between the target signal and the interference based on amplitude information to thereby acquire second identification information; correcting the second identification information according to the correction signal to thereby acquire corrected identification information; and controlling speed and accuracy of parameter adjustment in adaptive array processing using the corrected identification information.

As described above, in an adaptive array control device, a controlling method and their program, and an adaptive array processing device, a controlling method and their program, identification information of a target signal and interference by amplitude is corrected according to identification information of the target signal and the interference by phase, and with use of the correction result, identification of the target signal and the interference is performed. More specifically, the present invention includes an identification information generation section according to phase, a correction signal generation section, and a correction section.

Effects of the Invention

With the configuration described above, in the present invention, as identification information of a target signal and interference by amplitude is corrected according to identification information of the target signal and the interference by phases, it is possible to acquire highly accurate identification information of the target signal and the disturbing in which the identification information by amplitude and the identification information by phase are combined. As such, coefficient updating control of the adaptive array processing device can be performed appropriately, whereby high-quality array processing outputs which are less influenced by the frequency characteristics and incoming directions of input signals can be acquired.

BEST MODE FOR CARRYING OUT THE INVENTION

Hereinafter, exemplary embodiments of the invention will be described according to the drawings.

First Exemplary Embodiment

FIG. 1is a block diagram showing an adaptive array device having an adaptive array control device according to a first exemplary embodiment of the invention. The first exemplary embodiment includes, in the conventional adaptive array control device shown inFIG. 31, in addition to an identification information generation section configured of a blocking matrix circuit310and an SIR calculation section700, an identification information generation section820, a correction signal generation section830, and a correction section840are included. The identification information generation section850configured of the identification information generation section810, the identification information generation section820, the correction signal generation section830, and the correction section840provide the same function as that of the conventional identification information generation section810. Hereinafter, configuration and effects will be described mainly based on the operations of the identification information generation section820, the correction signal generation section830, and the correction section840.

The identification information generation section820generates information regarding identification of a target signal and interference according to phase information of signals obtained from M pieces of sensors1000to100M−1. This information includes not only presence of target signals and interferences but also a relative ratio of both signals. The identification information obtained in the identification information generation section820is transmitted to the correction signal generation section830. With use of the identification information supplied from the identification information generation section820, the correction signal generation section830generates a correction signal for correcting the identification information supplied from the identification information generation section810, and supplies it to the correction section840. The correction section840corrects the identification information supplied from the identification information generation section810using the correction signal supplied from the correction signal generation section830, and transmits the corrected identification information to the control section800.

If the corrected identification information is larger than the threshold, the target signal is prevailing in the input signal, and influence of the interference is low. As such, a control signal for coefficient update is generated and supplied to the adaptive blocking matrix circuit300. In contrast, as coefficient update of the multi-input canceller is disturbed by the target signal, a control signal for halting coefficient update of the multi-input canceller is generated and supplied to the multi-input canceller500. If the corrected identification information is smaller than the threshold, coefficient update coefficient update is halted in the adaptive blocking matrix circuit, and a signal for performing coefficient update is generated in the multi-input canceller, and is supplied to the adaptive blocking matrix circuit300and the multi-input canceller500, respectively. Further, the value of the corrected identification information calculated may be converted to a gain which takes a large value if the target signal is prevailing to the interference and takes a small value if it is not the case, and supplied to the adaptive blocking matrix circuit300and the multi-input canceller500. However, it is assumed that the gain is normalized so as to have a value in a range between 0 and 1.

The adaptive blocking matrix circuit300and the multi-input canceller500can control speed and accuracy of coefficient update by replacing the product of the supplied gain and a coefficient update step size with the coefficient update step size. In the case of using an index which has a large value close to 1 with respect to interference and has small correlation with respect to a target signal instead of normalized mutual-correlation, the same effects can be achieved. Consequently, a coefficient update control can be performed with higher accuracy than the case of using a comparison result with the threshold.

FIG. 2shows an exemplary configuration of the identification information generation section820. The identification information generation section820is configured of leakage blocking matrix circuits330and340, and a correlation section920. Input signals of the leakage blocking matrix circuits330and340are equal to input/output signals of the conventional blocking matrix circuit310. The leakage blocking matrix circuits330and340have symmetric structures, in which gains with respect to a target signal incoming from the front is the same, and have spatial selectivity for attenuating the target signal. On the other hand, a phase different between output signals of the leakage blocking matrix circuits330and340with respect to interference incoming from a direction other than the front becomes a large value near 180 degrees. The output signals of the leakage blocking matrix circuits330and340are supplied to the correlation calculation section920. The correlation calculation section920calculates mutual-correlation between outputs of the leakage blocking matrix circuits330and340, and transmits it to the correction signal generation section830.

As a correlation, a normalized mutual-correlation which is a result of dividing a value obtained by accumulating a product of respective output samples of the leakage blocking matrix circuits330and340with respect to a plurality of past samples, by a product of square root of a result of accumulating respective samples of the outputs of the leakage blocking matrix circuits330and340with respect to a plurality of past sample respectively, for example. A normalized mutual-correlation γ(n) in a sample n, determined as described above, is given by the following expression:

[Expression⁢⁢2]γ⁡(n)≈γ⋒⁡(ρ,ϑ)=∑i=0N-1⁢⁢{G2⁡(i,θ)·cos[φ(i,θ]+ρ·G2⁡(i,0)}∑i=0N-1⁢⁢{G2⁡(i,θ)+ρ·G2⁡(i,0)}(2)
Here, G(i,θ) is a (common) gain of the leakage blocking matrix circuits330and340with respect to the ithfrequency component and a direction θ, φ(i, θ) is a phase difference between output signals of the leakage blocking matrix circuits330and340with respect to the ithfrequency component and a direction θ, and ρ is an actual SIR. G(i,θ) can be calculated from actual configurations of the leakage blocking matrix circuits330and340.

With respect to a target signal incoming from the front, outputs of the leakage blocking matrix circuits330and340are equal, and a normalized mutual-correlation with respect to them has a large value near 1. On the other hand, with respect to interference incoming from a direction other than the front, as outputs of the leakage blocking matrix circuits330and340have a large phase difference, the normalized mutual-correlation becomes small. Accordingly, by transmitting the normalized mutual-correlation calculated by the correlation calculation section920to the control section800, and with use of a relationship with a predetermined threshold, a coefficient update control signal of the adaptive blocking matrix circuit300and the multi-input canceller500can be generated.

Although operation has been described here by means of an example of a normalized mutual-correlation, any index can be used if it has a large value near 1 with respect to a target signal and has small correlation with respect to interference. In contrast, the same effect can be expected even with an index having a large value near 1 with respect to interference and has small correlation with respect to a target signal.

FIG. 3shows an exemplary configuration of the leakage blocking matrix circuit330. InFIG. 3, the blocking matrix circuit330is configured of multipliers3311to331M−2, subtractors3320to332M−2, and an adder333. The multipliers3311to331M−2multiplies giby ith(i is an integer from 1 to M−2) sensor signal xi(k), and outputs the product gixi(k). The subtractor332i(i is an integer from 0 to M−2) calculates a difference zi(k)=xM−1(k)−gixi(k) between the M−1thsensor signal xM−1(k) and an output of the multiplier331i, and transmits to the adder333. Here, i is an integer in a range from 1 to M−2. The subtractor3320calculates a difference z0(k)=xM−1(k)−x0(k) between the M−1thsensor signal xM−1(k) and the 0thsensor signal x0(k), and transmits to the adder333. The adder333adds all of the M−1 pieces of input signals, and outputs the addition result as z3(k). That is, z3(k) is given by the Expression (3).

FIG. 4shows an exemplary configuration of the leakage blocking matrix circuit340. InFIG. 4, the blocking matrix circuit340is configured of multipliers3411to341M−2, subtractors3421to342M−1, and an adder343. The multipliers3411to341M−2multiplies giby ith(i is an integer from 1 to M−2) sensor signal xi(k), and outputs the product gixi(k). The subtractor342i(i is an integer of from 1 to M−1) calculates a difference zi(k)=x0(k)−gixi(k) between the 0thsensor signal x0(k) and an output of the multiplier341i, and transmits to the adder343. Here, i is an integer in a range of M−2 from 1. The subtractor342M−1calculates a difference zM−1(k)=x0(k)−xM−1(k) between the 0thsensor signal x0(k) and the M−1thsensor signal xM−1(k), and transmits to the adder343. The adder343adds all of the M−1 pieces of input signals, and outputs the addition result as z4(k). That is, z4(k) is given by the Expression (4).

Assuming that the signal source is provided at a sufficiently distant, all signals incoming to a sensor can be expressed with reference to any one of the signals. Now, assuming that x0(k) is a reference signal, xi(k) can be expressed by the following expression.
[Expression 5]
xi(k)=z−iDx0(k)  (5)

Here, z−iDis a delay corresponding to an interval between adjacent sensors. By applying the Expressions (5), (3) and (4), the Expressions (6) and (7) are established.

When the gains G3(k) and G4(k) of the leakage blocking matrix circuits330and340from the Expressions (6) and (7), the Expressions (8) and (9) are established.

When applying, to the Expressions (8) and (9), conditions that both of the gains G3(k) and G4(k) of the leakage blocking matrix circuits330and340becomes G(k), the Expression (10) is established.

In order that the Expression (10) is established,
[Expression 11]
gm=gM−1−m(11)
is to be established.

This indicates that multiplier coefficients of the leakage blocking matrix circuits330and340are symmetrical. Further, as multiplying all multiplier coefficients by a constant is equal to multiplying outputs by a constant, the leakage blocking matrix circuits330and340may be configured to multiply x0(k) and xM−1(k) by a constant and then supply to a corresponding subtractor. If a planar wave is assumed, signals incoming from an orthogonal angle with respect to a sensor array are all equal. When applying the Expression (11) after the Expressions (3) and (4), and then applying the Expression (5) where D=0, z3(k)=z4(k). That is, with respect to a signal incoming from the front, outputs of the leakage blocking matrix circuits330and340are equal.

Assuming that gm=gLto all m with respect to the leakage blocking matrix circuits330and304shown inFIGS. 3 and 4, when the number of sensors is M, the gain G(i,θ) included in the Expression (2) is given by the following Expression.

As obvious fromFIGS. 3 and 4, the leakage blocking matrix circuits330and340have symmetrical structures, and satisfy the Expression (11). Particularly, when gi=1 (i is an integer from 1 to M−2), the leakage blocking matrix circuits330and340have the configurations shown inFIGS. 5 and 6, respectively. Due to the symmetric property of the structures, respective output signals z3(k) and z4(k) provide a large phase difference particularly in a low frequency with respect to interference incoming from a direction other than the front. Further, with respect to a target signal incoming from the front, z3(k)=z4(k)=0 is established. Accordingly, to the target signal, the normalized mutual-correlation between z3(k) and z4(k) becomes zero.

Originally, as the normalized mutual-correlation should be zero with respect to interference, the target signal and the interference are not distinguishable in this state. As such, gi≠1 (i is an integer from 1 to M−2) is set. Such a value of gicauses z3(k) and z4(k) to leak the target signal to thereby prevent the normalized mutual-correlation from becoming zero.

The normalized mutual-correlation calculated by the correlation calculation section920using outputs of the leakage blocking matrix circuits330and340configured as described above generates a large difference with respect to the target signal and the interference, which enables to accurately distinguish the target signal and the interference using the normalized mutual-correlation. This means a target signal block where the target signal is prevailing and an interference block where the interference is prevailing can be separated accurately. Further, instead of deciding (hard decision) one of the target signal block and the interference block, it is possible to continuously decide (soft decision) intermediate states between the both.

Based on information of the target signal block and the interference block with high accuracy obtained in this manner, by controlling parameters determining the following property and operation accuracy of adaptive filters such as coefficient update step size and forgetting coefficient, coefficient update of the adaptive array processing device can be controlled appropriately. Consequently, a high quality array processing output less influenced by the frequency characteristics of input signals and directions of the target signal and the interference can be obtained.

FIGS. 7 and 8show second exemplary configurations of the leakage blocking matrix circuits330and340. Compared withFIGS. 3 and 4, the sensor signals xM−3(k) and x2(k) are not used. Corresponding to this, the configuration does not include the multiplier331M−3and a subtractor332M−3, and a multiplier3412and a subtractor3422. In other words, each of the leakage blocking matrix circuits330and340may be configured such that a path corresponding to a pair of sensors having the widest interval has no multiplier, and other paths are symmetrically provided with a coefficient giand a subtractor.

FIGS. 9 and 10show third exemplary configurations of the leakage blocking matrix circuits330and340. Compared withFIGS. 7 and 8, a sensor signal x0(k) is not used. When paying attention to sensor signals x1(k) to xM−1(k), the same configuration as that ofFIGS. 7 and 8is adopted. That is, the leakage blocking matrix circuits330and340may be configured such that one of signals corresponding to a pair of sensors having the widest interval is not used, and a path corresponding to a pair of sensors having a second widest interval do not have a multiplier, and other paths has a symmetric configuration in which coefficient and a subtractor are arranged.

FIGS. 11 and 12show fourth exemplary configurations of the leakage blocking matrix circuits330and340. Compared withFIGS. 9 and 10, a sensor signal xM−1(k) is not used. When paying attention to sensor signals x1(k) to xM−2(k), the same configuration as that ofFIGS. 7 and 8is adopted. That is, the leakage blocking matrix circuits330and340may be configured such that signals corresponding to a pair of sensors having the widest interval are not used, and a path corresponding to the closest pair of sensors interposed between them does not have a multiplier, and other paths has a symmetric configuration in which coefficient and a subtractor are arranged.

FIG. 13shows a fifth exemplary configuration of the leakage blocking matrix circuit330. InFIG. 13, the blocking matrix circuit330is configured of multipliers3311and331i+1, and a subtractor332i(i is an integer from 1 to M−2). The multiplier331imultiplies giby the ithsensor signal xi(k), and outputs the product gixi(k). The multiplier331i+1multiplies gi+1by the i+1thsensor signal xi+1(k), and outputs the product gi+1xi+1(k). The subtractor332icalculates a difference z3(k)=gi+1xi+1(k)−gixi(k) between an output of the multiplier331i+1and an output of the multiplier331i, and outputs it. Note that when the conditions of the Expression (11) are applied, gi+1=giis established. Further, it is needless to say that such coefficients may be arranged after the subtractor332i. The configuration of that case is the same as that shown inFIG. 32.

FIG. 14shows a fifth exemplary configuration of the leakage blocking matrix circuit340. InFIG. 14, the blocking matrix circuit340is configured of multipliers3411and341i+1, and a subtractor342i(i is an integer from 1 to M−2). The multiplier341imultiplies giby the ithsensor signal xi(k), and outputs the product gixi(k). The multiplier341i+1multiplies gi+1by the i+1thsensor signal xi+1(k), and outputs the product gi+1xi+1(k). The subtractor342icalculates a difference z4(k)=gixi(k)−gi+1xi+1(k) between an output of the multiplier341iand an output of the multiplier341i+1, and outputs it. Note that when the conditions of the Expression (11) are applied, gi=gi+1is established. Further, it is needless to say that such coefficients may be arranged after the subtractor342i.

Five exemplary configurations regarding the leakage blocking matrix circuits330and340have been described. In these five exemplary configurations, the number of pairs of sensor signals combined via internal subtractors and corresponding sensor intervals are different. It is configured that outputs of all subtractors are set to have values which are close to zero with respect to a target signal incoming from the front. Outputs of the subtractors will not become zero with respect to interference incoming from a direction other than the target signal. In other words, each of the subtractor outputs functions as a blocking matrix circuit independently. However, each of the subtractor outputs has different frequency response and directivity. This is due to the following two grounds.

First, a relative delay between two sensor signals which are subtractor inputs is given in a form that a product of a distance between sensors and sine of the signal incoming direction is divided by sound velocity. Further, distances between sensors are different in all subtractor outputs. The frequency characteristics and directivity of subtractor outputs become functions of distances between sensors. This means, in turn, subtractor outputs corresponding to different distances between sensors have different frequency characteristics and directivity. This is correct even if subtractors and adders are exchanged. However, the different point is that a gain becomes an inverse number of a gain of a subtractor. In the case of using an adder, a target signal is enhanced. The frequency characteristics and spatial selectivity in that case are disclosed in FIG. 1.1 of Non-Patent Document 11.

In the case of subtractors, it is clearly understood that it is only necessary to take inverse numbers of the characteristics shown in FIG. 1.1 of Non-Patent Document 11 and normalizing them. Referring to FIG. 1.1, if distances between sensors are constant, it is found that the spatial selectivity becomes steeper as the input signal frequency becomes higher. In a low frequency, the beam angle is wide, and the spatial selectivity deteriorates. If applying this to the case of the subtractors, in a low frequency, the sensitivity is low with respect to a target signal incoming from the front direction, and the sensitivity is high with respect to a direction off the front. However, transition from the direction of low sensitivity to the direction of high sensitivity is slow, so sufficient spatial selectivity cannot be achieved. On the other hand, if a sensor interval becomes wider, a relative delay becomes larger, so steep spatial selectivity can be achieved.

According to this principle, in the five exemplary configurations regarding the leakage blocking matrix circuits330and340, a plurality of differences between signals acquired from pairs of sensors having different intervals are calculated, and by adding them, blocking matrix circuits having comprehensively excellent spatial selectivity are acquired. With this configuration, differences between signal pairs obtained from sensors of wide intervals act effectively with respect to low-frequency signals, and differences between signal pairs obtained from sensors of narrow intervals act effectively with respect to high-frequency signals, and excellent spatial selectivity can be realized with respect to wide-band signals. As such, the leakage blocking matrix circuits330and340can suppress the target signal with excellent frequency characteristics and spatial selectivity. In the five exemplary configurations, as different subtractor outputs are used respectively, different spatial selectivity can be realized. Of course, the spatial selectivity is more excellent as the number of types of substrate outputs is larger, and the order is exemplary configuration1,2,3,4, and5.

A common aspect of blocking matrix circuits configuring those pairs is that the structure is symmetry and a gain with respect to the front is equal. This has been shown in Expression (11). As such, outputs are equal with respect to a target signal, and a phase difference between outputs with respect to interference becomes a value close to 180 degrees. Accordingly, the correlation between these blocking matrix circuit outputs is large with respect to a target signal, and is small with respect to interference. As long as these characteristics are held, the blocking matrix circuits configuring these pairs may take any structures. For example, the configuration of the blocking matrix circuits330and340can be the one in which a plurality of blocking matrix circuits corresponding to a plurality of sensor intervals are combined. In this example, null can be formed in the target signal direction by adjusting the filter characteristics in the filter-and-sum beamformer described above. Array processing for forming such null is performed respectively for a plurality of times corresponding to a plurality of sensor intervals, and the results can be combined.

The correction signal generation section830generates a correction signal used in the correction section840using normalized mutual-correlation supplied from the identification information generation section820. As obvious from the Expression (2), the normalized mutual-correlation γ hat becomes a function of ρ which is an actual SIR, and the range is between −1 to +1. In particular, if the normalized mutual-correlation γ hat takes a large value, the target power is extremely larger than the interference power. In that case, the correction signal generation section830generates a large gain K (γ hat). If it is not the case, the correction signal generation section830generates a small gain K (γ hat). Accordingly, the gain K (γ hat) becomes an increase function of γ hat. In other words, the gain is determined such that a larger correction will be performed when the target signal power is larger than the interference power. As an example of such a function, a linear function in a log domain of γ hat may be considered. That is, it is a gain K (γ hat) having a linear relationship with the log of γ hat, which can be expressed as the Expression (13).
[Expression 13]
K()=δ·(−r)  (13)

Here, δ and γTare constants. In order to set these constants, two conditions are required. A first condition is when identification between a target signal and interference is unnecessary, that is, when ρ=0 dB. At this time, as it is required that the Expression (2) is also satisfied, ρ=0 dB can be made in the Expression (2). However, as γ hat also depends on the signal incoming direction θ, it cannot be determined uniquely. An example of changes of γ hat changes with respect to various θ has been shown inFIG. 16. Here, considering that to which θ the gain K is most important, it is easily understood that it is a smaller θ. This is because, with respect to a smaller θ, in array processing in which a target signal is assumed to be incoming from the front, identification between a target signal and interference becomes difficult, and the accuracy of the estimated SIR becomes low. For an SIR of low estimation accuracy, the necessity of correction increases.

Now, in the graph as shown inFIG. 16, if the minimum value of the estimated interference incoming direction is set, the value of γ hat corresponding to θ min which is the direction thereof may be set to be γT. If the steering is non-zero, it is only necessary to correct θmin corresponding to the steering amount to thereby set the value of γT. Determination of δ which is another constant has trade-off. The value of δ is determined while considering the correction level of an SIR estimated in an actual environment for obtaining a value closet to the actual SIR. For example, in the case of using a microphone array consisting of four microphones in a typical room, an appropriate correction was achieved by setting δ to be 70. It should be noted that although an example of using a linear function of γ hat in calculation of K in the correction signal generation section830has been described, it is clearly understood that this may be any function or polynomial.

The gain K acquired by the function designed in this manner is transmitted to the correction section840. The correction section840multiplies the estimation SIR supplied from the identification information generation section810by the gain K supplied from the correction signal generation section830, and transmits the product to the control section800. Although an example of multiplies the correction in the correction section840multiplies the gain K, it is clearly understood that correction defined by simple addition, a more complicated function, polynomial or the like, other than multiplication, can be applied.

FIG. 15shows a second exemplary configuration of the identification information generation section820. The second exemplary configuration of the identification information generation section820is configured such that a filter334is provided between the leakage blocking matrix circuit330and the correlation calculation section920and a filter344is provided between the leakage blocking matrix circuit340and the correlation calculation section920, in the first exemplary configuration shown inFIG. 2. The filters334and344are designed such that a frequency, where the spatial selectivity defined by the blocking matrix circuits330and340, in particular, attenuation characteristics with respect to a direction other than the front becomes flat with respect to a direction, becomes a pass band thereof.

With the filters334and344, the mutual-correlation calculated by the correlation calculation section920with use of output signals of these filters causes a large difference between a target signal and interference, whereby distinction between a target signal and interference using mutual-correlation can be performed accurately. This means a target signal block where a target signal is prevailing and an interference block where interference is prevailing can be separated. Other operations and their effects are the same as those of the first exemplary configuration which have been described usingFIG. 2.

In the above description, a value of a parameter giin the first and second exemplary embodiments of the identification information generation section820has not been discussed. However, it has been described that in order to prevent output signals of the leakage blocking matrix circuits330and340from becoming zero with respect to the target signal, the value must be other than 1. As such, if gi≠1, it is understood that the value of giis preferably around 1 in order to cause a large phase difference. Actually, when calculating a normalized mutual-correlation with an assumption that a signal incoming to the sensor is a white signal, it becomes a function of a phase difference ø of true SIR ρ, a signal incoming direction θ, and output signals of the leakage blocking matrix circuits330and340.

When calculating gains and phases of the leakage blocking matrix circuits330and340with an assumption that the range of signal incoming direction θ is 30 to 90 degrees, the signal band is 500 to 1500 Hz, and the number of sensors is 4, a normalized mutual-correlation γ hat can be plotted with respect to a particular SIR ρ. In the case of the signal incoming direction θ being on the horizontal axis and the normalized mutual-correlation γ hat being plot on the vertical axis with respect to ρ=0 dB and ρ=−∞ dB,FIG. 16is obtained.

As it is preferable that only a single γ hat is determined with respect to θ of wide range, the locus of a γ hat value is preferably near horizon. Further, ranges of γ hats corresponding to ρ=0 dB and ρ=−∞ dB must not overlap each other. This is for obtaining clearly different γ hats for ρ=0 dB in which target signal and interference is combined at the almost same ratio and for ρ=−∞ dB in which the power of interference is overwhelmingly higher with respect to a target signal. When plotting a γ hat with respect to ginear 1 in these conditions, the optimum value of giis 0.92.FIG. 16shows a locus of a γ hat acquired with respect to the optimum value gi=0.92 in the above conditions, provided that the pass band of the filters334and344is set to be 500 to 1,500 Hz in correspondence with the voice.

FIG. 17shows a third exemplary configuration of the identification information generation section820. The third exemplary configuration of the identification information generation section820includes, in the second exemplary configuration, a leakage blocking matrix circuit350and a filter354, and a leakage blocking matrix circuit360and a filter364, in addition to the leakage blocking matrix circuit330and the filter334and the leakage blocking matrix circuit340and the filter344. The leakage blocking matrix circuit360is for providing an effect to a high-range signal with respect to the leakage blocking matrix circuit330acting mainly on a low-range signal by the filter334. As such, the pass band of the filter364is set to be higher than the passband of the filter334and to cover wider frequency bands when the pass bands of the filters334and364are combined.

That is, the processing performed by the leakage blocking matrix circuit330in the first exemplary configuration is to be performed by the leakage blocking matrix circuits330and360for respective frequency bands. An output of the filter364is transmitted to the multiplier365. The multiplier365enhances a high-frequency component so as to almost equal the power of an output of the filter364and the power of an output of the filter334. For example, if a signal band to be input to a sensor is 8 kHz, a coefficient of the multiplier365can be set to be around 3. An output of the multiplier365is transmitted to the adder336, and is added to the output of the filter334. The addition result is supplied to the correlation calculation section920.

Similarly, the leakage blocking matrix circuit350is for providing an effect to a high-range signal with respect to the leakage blocking matrix circuit340mainly acting on a low-range signal by the filter344. As such, the pass band of the filter354is set to be higher than the pass band of the filter344and cover wider frequency bands when the filters344and the354are combined. An output of the filter354is transmitted to the multiplier355. The multiplier355enhances a high frequency component so as to almost equal the power of an output of the filter354and the power of an output of the344. Accordingly, the coefficient of the multiplier355can be the same value as the coefficient of the multiplier365. An output of the multiplier355is transmitted to the adder346, and is added to an output of the filter344. The addition result is supplied to the correlation calculation section920.

With the leakage blocking matrix circuits350and360and the filters354and364, as a signal component of a frequency band, which has not been used when they were not present, can be used, mutual-correlation calculated by the correlation calculation section920causes a large difference between a target signal and an interference, so that distinction between the target signal and the interference using mutual-correlation can be performed accurately. This means a target signal block where a target signal is prevailing and an interference block where interference is prevailing can be distinguished accurately. Other operations and their effects are the same as those of the first exemplary embodiment which have been described usingFIG. 1.

As obvious from the above description, the leakage blocking matrix circuits350and360have symmetric configurations and the same givalue, which is the same as the leakage blocking matrix circuit330and340.FIGS. 18 and 19show examples of a phase difference ø of an output signal caused by the combination of the leakage blocking matrix circuits330and340, and a phase difference ø of an output signal caused by the combination of the leakage blocking matrix circuits350and360, respectively. It is calculated that the number of sensors is 4, and the signal band is 8,000 Hz, and the vertical axis is indicated as cosine (COS ø) of a phase difference ø. From these drawings, it is found that when the signal incoming direction DOA is close to 0, the cosine value is 1 regardless of the frequency. This corresponds to the target signal.

On the other hand, if the signal incoming direction DOA is distant from 0, the cosine value is −1 in only a specific frequency band. This corresponds to interference. The frequency bands where the cosine value becomes −1 are different inFIGS. 18 and 19, and the central frequency is about 1,000 Hz inFIG. 18, and is about 3,000 Hz inFIG. 19. That is, a frequency band where the normalized mutual-correlation becomes −1 with respect to interference is higher inFIG. 19. Accordingly, by processing outputs of the leakage blocking matrix circuits330and340and outputs of the leakage blocking matrix circuits350and360by bandpass filters which pass corresponding frequency bands respectively, a phase difference between a pair of leakage blocking matrix circuit outputs can be calculated as an index which becomes 1 with respect to a target signal and becomes −1 with respect to interference.

In the third exemplary configuration described usingFIG. 17, an input signal to the correlation calculation section920has been calculated using two pairs of leakage blocking matrix circuits. However, it is clearly understood that the number of pairs of leakage blocking matrix may be increased. Next, a method of designing a leakage coefficient giin a leakage blocking matrix circuit in the case that there are a plurality of pairs of leakage blocking matrix circuits will be described.

FIG. 20is a flowchart showing a design procedure of a leakage coefficient giin a leakage blocking matrix circuit. First, a signal band which should be processed by a pair of object leakage blocking matrix circuits and a minimum value θ min of a signal incoming direction (DOA) θ considered as interference are designated (S101). Next, a leakage coefficient giconsidered as appropriate is set (S102). According to these settings, the γ hat when the actual power ratio (SIR) ρ of the target signal to the interference is 0 dB is calculated using the Expression (2) with respect to θ which is larger than θ min and smaller than 90 degrees. The gain G (i, θ) in the Expression (2) can be calculated corresponding to the configuration of the leakage blocking matrix circuit if it is determined. The gain in the case of using the configurations shown inFIGS. 3 and 4becomes the one shown in the Expression (12). Similarly, the γ hat when ρ is ∞ dB is calculated with respect to θ which is larger than θ min and smaller than 90 degrees (S103).

It is checked whether or not the loci cross each other when these ρ are shown as inFIG. 16(S104). When they cross each other, the signal incoming direction (DOA) θ corresponding to a node corresponds to both ρ=0 dB and ∞ dB, so it is impossible to distinguish a state where the power of a target signal and the power of interference is almost equal and a state where the power of a target signal is overwhelmingly higher than the power of interference. As this phenomenon is caused by the value of a leakage coefficient giwhich has been set primarily, the processing so far is again performed using another leakage coefficient gi. If no locus crosses, the leakage coefficient giand data of the γ hat corresponding to ρ=0 dB is stored (S105).

Here, if evaluation is performed with another leakage coefficient gi, the procedure up to this point is repeated from the start (S106). Up to this point, data of γ hat corresponding to at least one leakage coefficient gihave to be obtained. Further, if data of γ hat corresponding to a plurality of leakage coefficients giare obtained up to this point, one value is selected. This selection is performed in the following procedure.

First, it is checked whether there is a leakage coefficient giin which the polarity of γ min hat and the polarity of γ max hat is opposite (S107).

Here, γ min hat and γ max hat are the minimum value and the maximum value of γ hat respectively obtained when changing θ with ρ=0 dB. When such a leakage coefficient giis present, a leakage coefficient giin which the absolute value of the average of γ min hat and γ max hat becomes the minimum is selected (S108). This indicates that γ hat obtained when changing θ with ρ=0 dB is distributed around zero, and the accuracy of calculating ρ from γ hat can be high. If there is no leakage coefficient gisatisfying the above conditions, giwhere distribution with respect to θ of γ hat when ρ=0 dB becomes the minimum is selected (S109).

By repeating the above procedures with respect to different frequency bands, a configuration having a plurality of pairs of leakage blocking matrix circuits can be designed. At this time, although respective frequency bands are selected in a manner of not overlapping each other basically, a serious problem will not be caused unless they overlap in an extremely large amount. As described above, with a plurality of pairs of vertical connections of leakage blocking matrix circuits and filters being provided, signal components of frequency bands which have not been used when those pairs were not present can be used. As such, a mutual-correlation calculated by the correlation calculation section920causes a large difference between a target signal and interference, and distinction between the target signal and the interference using mutual-correlation can be performed accurately. This means that a target signal block where the target signal is prevailing and an interference block where the interference is prevailing can be separated accurately. Other operations and their effects are the same as those of the first exemplary embodiment which has been described usingFIG. 1.

FIG. 21shows a second exemplary configuration of the identification information generation section810. The difference fromFIG. 31in which the first exemplary configuration is a gain control section900. The gain control section900corrects an estimation value of the target signal power adaptively corresponding to the characteristics of the target signal. As such, it is possible to enhance a specific frequency component adaptively to thereby realize a frequency and spatial selectivity having high flatness, so that the target signal power can be estimated accurately. The target signal power, which is estimated accurately, is transmitted to the SIR estimation section and used for SIR calculation. Based on the estimated SIR value with high accuracy acquired in this manner, it is possible to appropriately control coefficient update of the adaptive array processing device by controlling parameters determining the following property and the operational accuracy of adaptive filters such as a coefficient update step size and a forgetting coefficient. As a result, it is possible to acquire high-quality array processing outputs which are less influenced by the frequency characteristics of input signals and directions of the target signal and the interference.

FIG. 22shows an exemplary configuration of the gain control section900. The gain control section900includes a storage section901, a Fourier transform section902, an analyzing section903, a gain calculation section904, a spectrum correcting section905, an inverse Fourier transform section906, and a storage section907. An output of the fixed beamformer200is supplied to the storage section901and is framed. The framed signal is transmitted to the Fourier transform section902and is applied with Fourier transform. The Fourier transform result is supplied to the analyzing section903and the spectrum correcting section905. The analyzing section903analyzes the input signal using the Fourier transform result, and detects an input signal having a specific characteristic. The information regarding the characteristics of the input signal and the detection result are transmitted to the gain calculation section904. Although typical information regarding the characteristics of the input signal is spectrum, the amount of characteristic such as cepstrum and information in which cepstrum is thinned out may be used in place of spectrum. The gain calculation section904calculates a correction gain corresponding to the input signal, and supplies it to the spectrum correcting section905.

An example of a specific characteristic may be fricative sound. It is known that the frequency spectrum of a fricative sound has a power up to a higher range, and is flat compared with a non-fricative sound. With these facts, an appropriate correction gain can be obtained according to the power value in a high range and flatness of spectrum. Specifically, a high-range power and spectrum flatness are compared with reference values, and a value according to the magnitude relationship may be set as a correction gain. Further, in a simpler example, if the high range power and spectrum flatness are larger than the predetermined threshold, a correction gain may be set to a value other than 1, and if not, a correction gain may be set to 1. The value of correction gain may be the same or different for respective frequency components.

The spectrum correcting section905corrects spectrum by correcting the Fourier transform result supplied from the Fourier transform section902by using one or more correction gains supplied from the gain calculation section904. Specifically, the spectrum correcting section905corrects amplitude or power of the Fourier transform result with a correction gain, and supplies the result to the inverse Fourier transform section906. The phase information is directly supplied to the inverse Fourier transform section906without any correction. The inverse Fourier transform section906applies inverse Fourier transform to the data supplied from the spectrum correcting section905, and transmits the result to the storage section907. The storage section907outputs stored data by one sample to thereby apply inverse-frame to the signal sample. It is clearly understood that the Fourier transform section902and the inverse Fourier transform section906may be replaced with another pair of transform/inverse transform processing. Examples of such transform include cosine transform, correction discrete cosine transform also known as MDCT, Hadamard transform, and Haar transform. Further, prior to such transform processing, or following inverse transform processing, window processing using a window function may be performed so as to improve accuracy of a high-range component, particularly.

FIG. 23shows another exemplary configuration of the gain control section900. The gain control section900shown inFIG. 3includes a band division filter bank911, an analyzing section912, a gain calculation section913, a spectrum correcting section914, and a band synthesis filter bank915. An output of the fixed beamformer200is supplied to the band division filter bank911, and is divided into a plurality of frequency bands. Signals of the respective frequency bands are supplied to the analyzing section912and the spectrum collecting section914. Operation of the analyzing section912and the gain calculation section913are the same as those of the analyzing section903and the gain calculation section904. The spectrum correcting section914uses one or more correction gains supplied from the gain calculation section913to correct the level of each frequency band signal, and transmits the result to the band synthesis filter bank915. The band synthesis filter bank915synthesizes data supplied from the spectrum correcting section914, converts into a whole band signal, and outputs the result. Different from the exemplary configuration shown inFIG. 22, the present exemplary configuration is capable of performing equivalent processing by sequential processing without accumulating signal samples in the storage circuit. As such, a delay due to a gain control can be reduced, and the following characteristics with respect to the varying system will be increased.

It should be noted that the respective frequency bands of the band division filter bank and the band synthesis filter bank may have equal or unequal intervals. In this case, by dividing the band in unequal intervals, it is possible to lower the time resolution by dividing the bank to have narrow bands in the low frequency and to increase the time resolution by dividing the bank to have wide bands in the high frequency. Typical unequal division includes octave division in which the band becomes a half sequentially toward a lower band, and critical band division corresponding to human auditory characteristics. It has been known that unequal division has high consistency with audio signals, particularly. It should be noted that as the detail of the band division filter bank and the band synthesis filter bank and their design method are disclosed in Non-Patent Document 12, they are omitted.

FIG. 24shows a third exemplary embodiment of the identification information generation section810. A difference from that shown inFIG. 21showing the second exemplary configuration is a multiple blocking matrix circuit320. Hereinafter, configuration and effects will be described mainly based on the operation of the multiple blocking matrix circuit320.

Input/output signals of the multiple blocking matrix circuit320are equal to the input/output signals of the blocking matrix circuit310of the second exemplary configuration.FIG. 25shows a first exemplary configuration of the multiple blocking matrix circuit320. InFIG. 25, the multiple blocking matrix circuit320includes subtractors3210to321M−1and an adder322. The configuration ofFIG. 25is the same as the configuration ofFIG. 6which has been described above, the effects thereof are also the same.

FIG. 26shows a second exemplary configuration of the multiple blocking matrix circuit320. InFIG. 26, the multiple blocking matrix circuit320includes subtractors3210to321M−1, filters3230to323M−1, and an adder322. A subtractor i calculates a difference zi(k)=X0(k)−Xi(k) between the first sensor signal X0(k) and the ithsensor signal Xi(k), and transmits the difference to the filter323i. A signal i is an integer in the range from 0 to M−2. The filter323itransmits a signal component of a pass band to the adder322. The adder322adds all of the M−1 pieces of input signals, and output the addition result as z(k). The pass band of the filter323iis determined by the microphone interval between the 0thand the ith. The filter323iis designed such that the frequencies in which the directivity determined by the 0thand the ithmicrophone signals, particularly, attenuation characteristics with respect to directions other than the front, become flat with respect to the directions, becomes a pass band.

The multiple blocking matrix circuit320may have another configuration. In a series array configured of M pieces of sensors, an interval between two sensors is set to be D, 2D, 3D, - - - or (M−1)D, from the shortest. There are M−1 pairs of sensors in which the sensor interval is D, and M−2 pairs of sensors in which the sensor interval is 2D, and similarly, there are one pair in which the sensor interval is (M−1)D. Accordingly, the multiple blocking matrix circuit320exhibits the above-described effects as long as it has a configuration such that a pair of sensors corresponding to each sensor interval is set, and differences between signals obtained therefrom are calculated, and the differences are added by the adder322. Such an exemplary configuration is shown inFIG. 27as a third exemplary configuration. InFIG. 27, operation of the subtractors3210and321M−2is different from that shown inFIG. 26. Although, inFIG. 26, those subtractors output differential signals corresponding to sensor intervals D and (M−1)D, inFIG. 27, they output differential signals corresponding to sensor intervals (M−1)D and D. Besides, various similar configurations can be adopted. It should be noted that it is clearly understood that a configuration not having the filters3230to323M−1is also acceptable inFIG. 27.

Even in the case of a configuration not using signals corresponding to specific sensor intervals inFIG. 26, a blocking effect of a target signal is higher than that of the conventional blocking matrix circuit310.FIG. 28shows a fourth exemplary configuration of the multiple blocking matrix circuit320. Compared withFIG. 26,FIG. 28does not include the subtractor3211. As such, as there is no differential signal corresponding to a sensor interval of 2D, no effect caused by the sensor interval 2D is expectable. However, with signals corresponding to other sensor intervals, it is possible to obtain the blocking matrix circuit having comprehensively-excellent spatial selectivity, although it is less than the example ofFIG. 26. It should be noted that it is clearly understood that a configuration not having the filters3230to323M−1is also acceptable inFIG. 28.

The configuration of the blocking matrix circuit320can be the one in which a plurality of blocking matrix circuits corresponding to a plurality of sensor intervals are combined. For example, null can be formed in the target signal direction by adjusting the filter characteristics in the filter-and-sum beamformer described above. Array processing for forming such null is performed independently for a plurality of times corresponding to a plurality of sensor intervals, and the results can be combined.

FIG. 29shows a fourth exemplary configuration of the identification information generation section810. The relationship between the fourth exemplary configuration and the third exemplary configuration shown inFIG. 24is the same as the relationship between the first exemplary configuration described inFIG. 31and the second exemplary configuration described inFIG. 21, and a difference is only the gain control section900. Accordingly, as the operation and effects have been clear, the description is omitted.

Second Exemplary Embodiment

FIG. 30is a block diagram showing an adaptive array device having an adaptive array control device according to a fourth exemplary embodiment of the invention. The second exemplary embodiment of the invention includes a computer (CPU; processor; data processing device)1000which operates in accordance with a program control, input terminals1010to101M−1, and an output terminal600. The computer (CPU; processor; data processing device)1000includes the fixed beamformer200, the adaptive blocking matrix circuit300, the delay element400, the multi-input canceller500, the identification information generation sections810and820, the correction signal generation section830, the correction section840, and the controller800.

Target signals and interferences supplied to the input terminals1010to101M−1are supplied to the array processing device in the computer1000where the interferences are suppressed. The main components of the array processing device are the fixed beamformer200, the adaptive blocking matrix circuit300, the delay element400, and the multi-input canceller500. The adaptive mode control device including the identification information generation sections810and820, the correction signal generation section830, the correction section840and the control section800controls accuracy and coefficient updating speed of adaptive filters included in the adaptive blocking matrix circuit300and the multi-input canceller500.

The adaptive mode control device receives outputs of a group of a plurality of sensors, corrects identification information of the target signal and the interference by amplitude, according to identification information of the target signal and the interference by phase, and performs identification of the target signal and the interference using the correction result. Whereby, highly accurate identification information of the target signal and the interference, in which identification information by amplitude and identification information by phase are combined, can be acquired. As such, a coefficient updating control of the adaptive array processing device can be performed appropriately, so high-quality array processing outputs can be obtained.

Although description has been given above using microphones as sensors, sensors such as ultrasonic sensors, sonar receivers, and antennas may be used instead of microphones.

INDUSTRIAL APPLICABILITY

According to the present invention, a coefficient updating control of an adaptive array processing device can be performed appropriately, so that it is possible to obtain high-quality array processing outputs which is less influenced by the frequency characteristics of input signals and directions of a target signal and interference. Accordingly, it is possible to enhance and receive only a specific signal from among a plurality of signal sources. This method is widely applicable to acquisition of audio signals by adaptive microphone array, and wireless transmission-reception devices by means of sonar and adaptive antenna array in the hydroacoustic field, providing large effects on businesses of those fields.

DESCRIPTION OF REFERENCE NUMERALS