Methods and apparatus for adaptive beamforming

In view of the foregoing, what is claimed is:

1. Signal processing apparatus for combining a plurality of frequency-dependent signals wherein each frequency-dependent signal has a magnitude component and a phase angle component, said apparatus comprising

reference means for defining one of said frequency-dependent signals as a reference signal having a user-selected phase angle,

a plurality of alignment means, each coupled to a respective one of said frequency-dependent signals, for adjusting the phase angles of said signals relative to said reference signal, said alignment means having

phase difference estimator means for generating a delay signal representative of a time delay between said reference signal and said frequency-dependent signal, and

phase alignment means for generating, as a function of said delay signal, an output signal having a magnitude component representative of the magnitude component of said frequency-dependent signal and having a phase angle component adjusted to a select phase relationship with said reference signal, and

summation means, coupled to said plurality of alignment means for summing together said phase aligned output signals to generate a beam signal.

2. Apparatus according to claim 1 further comprising

means for generating said plurality of frequency-dependent signals, said means including

an array of spatially distributed sensor elements, wherein each sensor element includes means for detecting a signal and generating a respective one of said plural frequency-dependent signals to represent said signal detected at said spatially distributed sensor element.

3. Apparatus according to claim 2 wherein

said array includes a linear array of spatially distributed sensor elements.

4. Apparatus according to claim 2 wherein

said array includes a two-dimensional array of spatially distributed sensor elements.

5. Apparatus according to claim 2 wherein

said array includes a three-dimensional array of spatially distributed sensor elements.

6. Apparatus according to claim 1 wherein said phase difference estimator means includes

means for generating said delay signal as a function of said reference signal and said respective one of said frequency-dependent signal.

7. Apparatus according to claim 1 wherein said phase difference estimator means couples to a delay signal of a second alignment means and includes

summing means for summing said delay signals to generate a signal representative of the time delay between said respective one of said frequency-dependent signal and said reference signal.

8. A signal processing apparatus according to claim 1 further comprising

weighting means, connected to one or more phase alignment means, for increasing or decreasing the magnitude component of each of said output signals.

9. A signal processing apparatus according to claim 1 further comprising

weighted averaging means, connected to at least a portion of said phase alignment means, for increasing or decreasing the magnitude component of said output signals as a function of a normalizing factor representative of the number of output signals summed together.

10. Signal processing apparatus for combining a plurality of frequency-dependent signals wherein each frequency-dependent signal has a magnitude component and a frequency component, said apparatus comprising

reference means for defining one of said frequency-dependent signals as a reference signal having a user-selected phase angle,

a plurality of alignment means, each coupled to a respective one of said frequency-dependent signals, for adjusting the phase angles of said frequency-dependent signals relative to said reference signal, said alignment means having

storage means for storing a magnitude component and a phase angle component of said frequency-dependent signal,

delay estimator means for generating, as a function of the difference in phase angles of two frequency-dependent signals, a delay signal representative of a time delay between said reference signal and said frequency-dependent signal, and

phase alignment means for generating as a function of said delay signal, an output signal having a magnitude component representative of the magnitude component of said frequency-dependent signal and having a phase angle adjusted to a select phase relationship with said reference signal, and

summation means, coupled to said plurality of alignment means and having means for summing frequency-dependent signals, for generating a beam signal representative of a summation of said output signals.

11. A signal processing apparatus according to claim 10 wherein said delay estimator includes weighting means for generating as a function of said magnitude components of said frequency-dependent signal, said difference in phase angles.

12. A signal processing apparatus according to claim 10 further including

error detection means for generating, as a function of said delay signal and said phase angle component of said frequency-dependent signal, an error signal representative of the accuracy of said delay signal.

13. A signal processing apparatus according to claim 12 wherein said summation means includes means for monitoring said error signal to adjust said beam signal responsive to an error signal larger than a user-selected error-parameter.

14. A signal processing apparatus according to claim 12 further comprising

means for generating said error signal as a function of the geometric mean of the magnitude components of two frequency-dependent signals.

15. A beamforming apparatus for combining a plurality of frequency-dependent signals wherein each frequency-dependent signal has a magnitude component and a phase angle component comprising

means for generating said plurality of frequency-dependent signals, having an array of spatially distributed sensor elements, wherein each sensor element includes transducer means for detecting a signal and for generating a respective one of said plural signals to represent said signal detected at said spatially distributed sensor element,

reference means for storing one of said frequency-dependent signals as a reference signal having a user-selected phase angle,

a plurality of alignment means, each coupled to a respective one of said frequency-dependent signals, for adjusting the phase angle components of said frequency-dependent signals relative to said reference signal, said alignment means having

storage means for storing said magnitude component and said phase angle component of said frequency-dependent signal,

delay estimator means for generating, as a function of the difference in phase angles of two frequency-dependent signals, a delay signal representative of a time delay between said reference signal and said frequency-dependent signal, and

phase alignment means for generating as a function of said delay signal, an output signal having a magnitude component representative of the magnitude component of said frequency-dependent signal and having a phase angle component adjusted to a select phase relationship with said reference signal, and

summation means, coupled to said plurality of alignment means and having means for summing frequency-dependent signals, for generating a beam signal representative of a combination of said output signals.

16. Apparatus according to claim 15 wherein

said array includes a linear array of spatially distributed sensor elements and said detection means includes means for detecting audio signals.

17. Apparatus according to claim 15 wherein

said array includes a linear array of spatially distributed microphones of the type amenable for detecting audio signals.

18. Apparatus according to claim 15 wherein

said array includes digital conversion means, coupled to each of said sensor elements, for generating said respective signal as digital electrical signal.

19. Apparatus according to claim 18 wherein

said array includes window filter means, coupled to each of said sensor elements, for generating said respective signal to represent a discrete portion of said digital electrical signal.

20. Apparatus according to claim 18 wherein

said array includes a 512 point hanning window filter means, coupled to each of said sensor elements, for generating said respective signal to represent a 512 point portion of said digital electrical signal.

21. Apparatus according to claim 15 wherein said array further comprises

time-to-frequency transform means, coupled to each of said sensor elements, for generating said respective signal as a frequency-dependent representation of said detected signal.

22. Apparatus according to claim 21 wherein said frequency transform means includes

fast fourier transform means for generating a plurality of fourier coefficients representative of at least a portion of the spectral content of said detected signal.

23. Apparatus according to claim 15 wherein said delay estimator further comprises

spatial aliasing filter means for generating said delay signal as a function of the spatial distribution of said sensor elements.

24. Apparatus according to claim 15 where in said summation means further comprises

frequency-to-time transform means, coupled to said signal summation means, for generating said beam signal as a time-dependent signal.

25. Apparatus according to claim 15 wherein

said array of spatially distributed sensor elements has a first array of sensor elements spatially distributed relative to a first axis and a second array of sensor elements spatially distributed relative to a second axis extending transversely to said first axis,

said reference means has means for storing a first reference signal and a second reference signal representative of frequency magnitudes and phase angles of one of said frequency-dependent signals generated by said first array and said second array respectively, and

said delay estimator means has means for generating, a first delay signal and a second delay signal representative of the time delay between said first reference signal and a frequency-dependent signal generated by said first array and said second reference signal and a frequency-dependent signal generated by said second array, and means for generating a position signal, as a function of said first delay signal and said second delay signal, representative of the position of said detected signal relative to said first and second arrays.

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FIELD OF THE INVENTION

The present invention relates to methods and apparatus for adaptive signal processing and, more particularly, to methods and apparatus for adaptively combining a plurality of signals, e.g., electrically represented audio signals, to form a beam signal.

BACKGROUND OF THE INVENTION

Many communication systems, such as radar systems, sonar systems and microphone arrays, use beamforming to enhance the reception of signals. In contrast to conventional communication systems that do not discriminate between signals based on the position of the signal source, beamforming systems are characterized by the capability of enhancing the reception of signals generated from sources at specific locations relative to the system.

Generally, beamforming systems include an array of spatially distributed sensor elements, such as antennas, sonar phones or microphones, and a data processing system for combining signals detected by the array. The data processor combines the signals to enhance the reception of signals from sources located at select locations relative to the sensor elements. Essentially, the data processor "aims" the sensor array in the direction of the signal source. For example, a linear microphone array uses two or more microphones to pick up the voice of a talker. Because one microphone is closer to the talker than the other microphone, there is a slight time delay between the two microphones. The data processor adds a time delay to the nearest microphone to coordinate these two microphones. By compensating for this time delay, the beamforming system enhances the reception of signals from the direction of the talker, and essentially aims the microphones at the talker.

A major factor in the effectiveness of these beamforming systems is the accuracy of the time delays necessary for aiming the sensor array. One known technique for determining the time delays necessary for aiming the sensor array employs a priori knowledge of the source position, the source orientation and the radiation pattern of the signal. Essentially, the data processor determines from the position of the source and, from the position of the sensor elements, a delay factor for each of the sensor elements. The data processor then applies such delay factors to the respective sensor elements to aim the sensor array in the direction of the signal source.

Although these systems work well if the position of the signal source is precisely known, the effectiveness of these systems drops off dramatically with slight errors in the estimated a priori information. For instance, in some systems with source-location schemes, it has been shown that the data processor must know the location of the source within a few centimeters to enhance the reception of signals. Therefore, these systems require precise knowledge of the position of the source, and precise knowledge of the position of the sensors. As a consequence, these systems require both that the sensor elements in the array have a known and static spatial distribution and that the signal source remains stationary relative to the sensor array. Furthermore, these beamforming systems require a first step for determining the talker position and a second step for aiming the sensor array based on the expected position of the talker.

Other techniques for determining the direction for aiming the sensor array rely on a priori information regarding the signal waveform and the signal radiation pattern. For example, radar systems use beamforming to transmit signals in a select direction. If an object is present in that direction, the signal reflects off the object and travels back toward the radar system. Therefore, the radar system is transmitting and receiving very similar signals. Furthermore, the data processor assumes that the objects are sufficiently distant from the sensor array that the incoming signals have a particular radiation pattern. The assumed radiation pattern can be a particularly simple pattern that reduces the complexity of the time delay computation.

The radar system capitalizes on the similarity of the transmitted and received signals by using signals that have features which facilitate signal processing. The data processor can directly compare the features of the received signal against the features of the transmitted signal and determine differences between the two signals that relate to the relative time delays between each sensor. Furthermore, the radar system can use the assumptions regarding the radiation pattern of the incoming signals to simplify the signal processing techniques necessary to calculate the time delays. The data processor then compensates for the respective time delays between each sensor element to aim the sensor array in the direction of the object.

Although these systems work well if the signal waveform is known, these systems less effective where the a priori information regarding the signal waveform is unavailable or insufficient to allow the received signals to be compared against a known signal waveform. Therefore, these systems are generally limited to active systems that both transmit and receive signals. Furthermore, these systems are less effective when assumptions regarding the radiation pattern cannot be made. Therefore, these systems are usually limited to those applications where the signal source is sufficiently distant from the sensor array that a signal pattern can be assumed.

A known technique for determining the direction of incoming signals without a priori information employs correlation strategies that compare signals received by the array at spatially distinct sensors to estimate the time delays between the sensors. The time delay information, along with assumptions about the radiation pattern, are used to estimate the location of the signal source. One example of correlation strategies for locating talker position with a microphone array in a near-field environment is set forth in Silverman et al., A Two-Stage Algorithm for Determining Talker Location from Linear Microphone Array Data, Computer Speech and Language, at 129-152 (1992). In general, the cross-correlation function of two signals received at two distinct sensors is computed and filtered in some optimal sense. The data processor includes a peak detector that detects the maximum value of the filtered signal. While the filtering criteria and the methods used for peak detection may vary considerably, these techniques are all based on maximizing the correlation between two received signals and determining from the detected peak the relative time delays between the associated sensors. Once the time delays are determined, techniques, such as triangulation, can be used to determine the location of the signal source.

Although these systems can work well, there is generally a trade-off between the accuracy of the time delay estimate and the computational expense incurred by the procedure. Furthermore, there can be a tradeoff between the accuracy of the delay estimate and the rate at which the system can acquire the incoming signals. The cross-correlation function is a computationally intensive operation, and the accuracy of the peak data increases with the number of comparisons made during the correlation. In order to achieve a peak that is sufficiently accurate and well defined to identify precisely the position of the source, the computational burden can be prohibitive. Therefore, these systems can fail to produce the desired accuracy and update rate required for effective beamforming in a real-time environment.

In view of the foregoing, an object of the present invention is to provide improved signal processing methods and systems for combining a plurality of signals, and more particularly, to provide improved systems and methods for beamforming that dynamically determine the time delay estimates for a sensor array as part of the beamforming process.

A further object of the present invention is to provide systems and methods for real-time beamforming without the need of a priori information about the position of the signal source or knowledge of the signal radiation pattern.

Another object of the present invention is to provide signal processing systems and methods for adaptively aiming an array of sensor elements at a moving signal source.

A yet further object of the present invention is to provide signal processing systems and methods that can dynamically compensate for a sensor array that has a non-uniform or unknown spatial distribution of sensors.

A still further object of the present invention is to provide systems and methods for real-time beamforming without the need of a priori information about the signal waveform.

Still another object of the present invention is to provide computationally efficient systems and methods to determine the relative time delays between the signals received by the sensor elements of a sensor array and employ these delay estimates for computationally efficient beamforming and source location.

These and other objects of the invention are evident in the sections that follow.

SUMMARY OF THE INVENTION

The aforementioned objects are obtained by the present invention which provides in one aspect an adaptive beamforming apparatus which operates to combine a plurality of frequency-dependent signals to enhance the reception of signals from a signal source located at a select location relative to the apparatus.

In one embodiment, the beamforming apparatus connects to an array of sensors, e.g. microphones, that can detect signals generated from a signal source, such as the voice of a talker. The sensors can be spatially distributed in a linear, a two-dimensional array or a three-dimensional array, with a uniform or non-uniform spacing between sensors. In a typical practice, the sensor array can be mounted on a wall or a podium and the talker is free to move relative to the sensor array. Each sensor detects the voice audio signals of the talker and generates electrical response signals that represent these audio signals. The adaptive beamforming apparatus provides a signal processor that can dynamically determine the relative time delay between each of the audio signals detected by the sensors. Further, the signal processor includes a phase alignment element that uses the time delays to align the frequency components of the audio signals. The signal processor has a summation element that adds together the aligned audio signals to increase the quality of the desired audio source while simultaneously attenuating sources having different delays relative to the sensor array. Because the relative time delays for a signal relate to the position of the signal source relative to the sensor array, the beamforming apparatus provides, in one aspect, a system that "aims" the sensor array at the talker to enhance the reception of signals generated at the location of the talker and to diminish the energy of signals generated at locations different from that of the desired talker's location.

A beamforming apparatus constructed according to the present invention can include a signal processor that determines the relative time delay between a plurality of frequency-dependent signals. The signal processor can store one frequency-dependent signal as a reference signal and can align the remaining frequency-dependent signals relative to this reference signal. The reference channel can include a memory for storing one of the frequency dependent signals as a reference signal having a user selected phase angle. The reference channel can connect to a plurality of alignment channels, where each alignment channel couples to a respective one of the frequency-dependent signals. The alignment channels can operate to adjust the phase angle of each of the frequency-dependent signals in order to align the signals relative to the reference signal. Each alignment channel can have a phase difference estimator that generates a delay signal which represents the time delay between the reference signal and the respective signal connected to the alignment channel. The alignment channel can also include a phase alignment element that generates an output signal as a function of the delay signal, which has a magnitude that represents the magnitude of the respective signal and a phase angle that is adjusted into a select phase relationship with the reference signal. The signal processor can further include a summation element that couples to the alignment channels and to the reference channel. The summation element can generate a beam signal by summing the output signals with the reference signal.

The adaptive beamforming apparatus can include an array of spatially distributed sensor elements for generating the plurality of frequency-dependent signals. The sensor elements can be any one of a number of different types of elements capable of detecting a signal. Examples of such sensor elements include antennas, microphones, sonar transducers and various other transducers capable of detecting a propagating signal and transmitting the signal to the signal processor.

The sensor elements are spatially distributed to form an array for detecting a signal. Each sensor in the array can generate a single signal that represents the signal detected at that sensor element as a function of time. The spatial distribution of sensor elements can be unknown or non-uniform. The invention can be practiced with a linear array, a two dimensional array, or a three dimensional array.

In one embodiment of the invention, the reference channel of the signal processor can connect to the phase difference estimator of each alignment channel. In this practice, the phase difference estimator includes a memory for storing the reference signal and for storing the respective frequency-dependent signal associated with the respective alignment channel. The phase difference estimator has a processing means to generate the delay signal as a function of the reference signal and the respective frequency-dependent signal.

In an alternative embodiment, the signal processor can include interconnected alignment channels that determine the relative time delay between spatially adjacent sensors. In this practice, the phase difference estimator can include a memory for storing the respective frequency-dependent signal of the associated alignment channel and the respective frequency-dependent signal of the second alignment channel. The memory can further store the delay signal of the second alignment channel. The phase difference estimator can include a summing element that generates a delay signal as a function of the signal associated with the respective alignment channel and delay signal of the second alignment channel.

In an alternative embodiment of the invention the signal processor can include a weighting element, that can increase or decrease the magnitude component of selected output signals. The weighting element can be a weighted averaging element that can affect the magnitudes of the output as a function of the number of output signals summed together.

In a further alternative embodiment of the present invention, an error detector is associated with each of the delay estimators and determines from the delay signals and the frequency-dependent signals, an error signal that represents the accuracy of the delay signals. The error signal can be used by the weighted averaging element to determine which of the output signals has an associated error signal that is larger than a user-selected error parameter. The summation means can effect the weighting of that output signal responsive to the error signal, including deleting that output signal from the signal summation.

In another further embodiment of the invention, the delay estimator generates a delay signal that represents the time delay between a reference signal and a respective one of the frequency dependent signals, by measuring the difference between the phase angle components to the frequency-dependent signals. In one embodiment the delay estimator measures the difference in phase angles between the reference signal and the respective frequency-dependent signal of that alignment channel. The delay estimator can calculate from the differences in phase angles and from the frequency associated with each phase angles, the relative phase shift between the two signals. In one embodiment of the invention, the delay estimator can further include a weighting system that multiplies the difference in phase angles of each frequency component of two respective signals, by the magnitude of that frequency component.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other aspects of the invention may be more fully understood from the following description, when read together with the accompanying drawings in which like reference number indicate like parts in the several figures, and in which:

FIG. 1 illustrates a schematic block diagram of one embodiment of a beamforming apparatus constructed according to the present invention;

FIG. 2 illustrates a schematic block diagram of one alignment channel of the beamforming apparatus depicted in FIG. 1;

FIG. 3 illustrates an alternative embodiment of a beamforming apparatus constructed according to the present invention that includes phase difference estimators connected between spatially adjacent sensor elements;

FIG. 4 illustrates the operation of a delay estimator that includes an unwrapping element for limiting spatial aliasing;

FIG. 5 illustrates a further embodiment of the present invention that includes an orthogonal array of sensor elements;

FIG. 6 illustrates in more detail the orthogonal array of FIG. 1.

DETAILED DESCRIPTION

FIG. 1 depicts an adaptive beamforming apparatus 10 constructed in accord with the invention. The illustrated apparatus 10 includes a sensor array 12 and a signal processor 14. The sensor array 12 includes the sensors 16, sampling units 18, window filters 20 and time-to-frequency transform elements 22. The signal processor 14 includes a reference channel 24 and plural alignment channels 26. Each alignment channel 26 includes a phase difference estimator 28, phase alignment element 30 and an optional weighting element 32. The illustrated system 10 further includes a summation element 34 and a frequency-to-time transform element 36.

The illustrated sensor array 12 includes a plurality of sensor elements 16. The sensors 16, in the depicted embodiment, are arranged to form a spatially distributed linear array of sensors 16 each spaced apart by a distance X and arranged to receive input signals having signal components from a signal source, such as the target source 38. In the illustrated embodiment, each sensor 16 is the front end of an reception channel that includes a sampling unit 18, a window filter 20 and a time-to-frequency transform element 22 all connected in electrical circuit. Each of the illustrated reception channels is a distinct subsystem of the sensor array 12 and can operate simultaneously with and independently from the other reception channels.

Each sensor 16 detects signals, including signals generated from the target source 38, and generates an electrical response signal that includes a component that represents the signal generated frown the signal source 38. The sensors 16 in the sensor array 12 can be microphones, antennas, sonar phones or any other sensor capable of detecting a signal propagating from the source 38 and generating an electrical response signal that represents the detected signal.

Each illustrated sampling element 18 is in electrical circuit with one sensor 16 and generates a digital response signal by sampling the electrical response signal generated by the associated sensor 16. The sampling element 18 can be a conventional analog-to-digital converter circuit of the type commonly used to sample analog electrical signals and generate digital electrical signals that represent the sampled signal. The sampling element 18 generates samples of the electrical response signal at a rate, f.sub.rate, selected according to the application of the beamforming apparatus 10. The sampling rate is generally determined according to the highest frequency component of the propagating signal of interest and according to the Nyquist rate. The sampling elements 18 are discussed in further detail below.

The window filter 20 can be a conventional digital window filter for selecting a discrete portion of a digital response signal. In the illustrated embodiment the window filter 20 is in electrical circuit with the output of the sampling element 18, and generates a finite length digital signal by truncating the digital signal generated by the sampling unit 18. In one embodiment, the window filter 20 can be a rectangular w