CN114586097A

CN114586097A - Differential directional sensor system

Info

Publication number: CN114586097A
Application number: CN201980101111.2A
Authority: CN
Inventors: 黄伟隆; 冯津伟
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2019-11-05
Filing date: 2019-11-05
Publication date: 2022-06-03
Also published as: WO2021087728A1

Abstract

Obtaining input signals received by a plurality of directional sensors arranged in a particular configuration; transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band; applying a predetermined set of weights to respective frequency bands in the frequency domain to obtain a combined frequency band; and transforming the combined frequency band from the frequency domain to the time domain to obtain an output signal. The particular geometric configuration may be two-dimensional or three-dimensional. In addition, the particular geometric configuration may be formed, for example, by a plurality of circles having a common center or groups of circles having different centers, where each group of circles has the same center.

Description

Differential directional sensor system

Background

With the advent of signal sensing and processing technology, omni-directional sensors and omni-directional sensor arrays (i.e., omni-directional sensor arrays) have been developed and applied to various technical fields. The omni-directional sensor or array of omni-directional sensors is configured to receive and detect signals from all directions and therefore does not need to be mechanically rotated to periodically point in different directions. Examples of omni-directional sensors may include omni-directional microphones, omni-directional cameras, omni-directional radio antennas, and the like.

However, due to this omnidirectional nature, there are many inherent problems with existing omnidirectional sensors and omnidirectional sensor arrays. Take an omnidirectional microphone/omnidirectional microphone array as an example. The omni-directional sensor/omni-directional sensor array may also receive unnecessary signals since it may pick up signals from all directions. Although algorithms have been proposed to filter these unwanted signals, existing omni-directional sensor arrays still suffer from certain problems. For example, existing omnidirectional microphone arrays suffer from low White Noise Gain (WNG) at low frequencies and from a reduced directivity index (a measure of directivity characteristics) at high frequencies. Furthermore, the array performance of existing omni-directional sensor arrays is not sufficient to meet certain criteria (e.g., array gain).

Disclosure of Invention

This disclosure presents a simplified concept of a differential directional sensor system, which will be further described in the detailed description below. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

This application describes implementation examples of differential directional sensor systems. In implementations, input signals received by a plurality of directional sensors arranged in a particular configuration are obtained. The input signal may then be transformed from the time domain to the frequency domain to obtain the corresponding frequency band. In an implementation, a predetermined set of weights may be applied to respective frequency bands in the frequency domain to obtain a combined frequency band, which may then be transformed from the frequency domain to the time domain to obtain an output signal.

Drawings

The detailed description refers to the accompanying drawings. In the drawings, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different figures indicates similar or identical items.

FIG. 1 illustrates an example environment in which a differential directional sensor system may be used.

Fig. 2 shows an example of a differential directional sensor system in more detail.

FIG. 3 illustrates an example method of signal processing using an example differential directional sensor system.

Fig. 4A-4F illustrate examples of geometric configurations of orientation sensors.

Fig. 5 shows an example of a circular configuration of a directional microphone.

Fig. 6A-6F show a comparison of beam patterns for two different designs between CDDMA and a Circular Differential Microphone Array (CDMA) using omni-directional microphones.

Figures 7A and 7B show a comparison of CDDMA and CDMA in terms of WNG and DI.

Detailed Description

SUMMARY

As described above, existing omni-directional sensors and omni-directional sensor arrays, while allowing signal detection in all directions, have a number of inherent problems that can severely affect the use of omni-directional sensors and omni-directional sensor arrays, thereby limiting the practical applications of these omni-directional sensors and omni-directional sensor arrays.

This application describes an example of a differential directional sensor system. A differential directional sensor system may include a plurality of directional (e.g., unidirectional) sensors arranged in a particular geometric configuration. The particular geometric configuration may be two-dimensional or three-dimensional, for example, depending on the respective application or use of the differential orientation sensor system. In an implementation, the geometrical configuration may be formed by several circles having a common center or groups of circles having different centers, for example, wherein each group of circles has the same center.

In implementations, the differential orientation sensor system may further include one or more processors configured to control, coordinate, and process signals received by the plurality of orientation sensors to produce output signals.

In implementations, the differential directional sensor system may obtain input signals received by a plurality of directional sensors and transform the input signals from a time domain to a frequency domain to obtain respective frequency bands. In an implementation, the differential directional sensor system may apply a predetermined set of weights to each frequency band in the frequency domain to obtain a combined frequency band, and transform the combined frequency band from the frequency domain to the time domain to obtain an output signal.

In implementations, the differential directional sensor system may store a set of predetermined sets of weights, or may access a set of predetermined sets of weights stored in a peripheral or remote device. Each set of predetermined weights (each set of predetermined weights) may cause the differential directional sensor system to preferentially weight or emphasize signals received from multiple directional sensors from a particular preferred or desired direction relative to a particular point (e.g., a common center) in a particular geometry. In this case, the differential directional sensor system may select a set of predetermined weights from a set of predetermined sets of weights and apply the set of predetermined weights to the respective frequency bands to obtain a combined frequency band. In other words, by selecting a different set of predetermined weights (e.g., a set of predetermined weights for a particular preference or desired direction), the differential orientation sensor system can electronically adjust the plurality of orientation sensors to receive signals from the preferred or desired direction without mechanically moving the plurality of orientation sensors and/or any physical portion of the differential orientation sensor system.

In implementations, the differential directional sensor system may estimate or determine the direction of an expected or certain signal origin or source. By way of example and not limitation, the differential directional sensor system may determine respective signal strengths of desired signals or certain signals received by multiple directional sensors. Based on the directional properties of the directional sensors and the geometry of the directional sensors, the differential directional sensor system may estimate or determine the direction of origin or origin of a desired or particular signal, e.g., a weighted average of the directions of such one or more directional sensors based on the detected signal strength of the desired or particular signal.

Further, the differential directional sensor system can easily filter unwanted signals in directions other than a signal from a desired direction using the directional characteristics of the directional sensor in consideration of the use of the directional sensor.

In implementations, the functions described herein as being performed by a differential directional sensor system may be performed by a plurality of separate units or services. For example, the acquisition service may obtain input signals received by the plurality of directional sensors, and the transformation service may convert the input signals from the time domain to the frequency domain to obtain corresponding frequency bands. The combination service may apply a set of predetermined weights to respective frequency bands in the frequency domain to obtain a combined frequency band, and the transformation service may transform the combined frequency band from the frequency domain to the time domain to obtain an output signal. In an implementation, the selection service may select a predetermined set of weights from a set of predetermined weights and provide the predetermined set of weights to the combination service to be applied to the corresponding frequency bands to obtain the combined frequency band.

Further, while in the examples described herein, the differential directional sensor system may be implemented as a combination of software and hardware installed in a single device, in other examples, the differential directional sensor system may be implemented and distributed across multiple devices, or as a service provided in one or more computing devices over a network and/or in a cloud computing architecture.

This application describes a number of different embodiments and implementations. The following section describes an example framework that is suitable for practicing various embodiments. Next, this application describes example systems, devices, and processes for implementing a differential directional sensor system.

Exemplary Environment

FIG. 1 illustrates an example environment 100 that can be used to implement a differential directional sensor system. The environment 100 may include a differential directional sensor system 102. In this example, the differential directional sensor system 102 is described as existing as a separate entity or device. In some cases, the differential directional sensor system 102 may be included in a computing device, such as the client device 104. In other cases, the differential directional sensor system 102 may be included in one or more servers, such as one or more servers 106 in the cloud. For example, some or all of the functionality of the differential directional sensor system 102 may be included in the client device 104 or provided by the client device 104 and/or one or more servers 106 connected and communicating over the network 108.

In implementations, the environment 100 may also include one or more sets of orientation sensors 110, with corresponding orientation sensors in each set arranged in a respective geometric configuration. In implementations, some or all of the one or more sets of directional sensors 110 may be peripheral devices to the differential directional sensor system 102 and, in implementations, communicate data with the differential directional sensor system 102 via local connections and/or short-range communications (e.g., cable/wire, bluetooth, infrared, WiFi, etc.). In an implementation, some or all of the one or more sets of directional sensors 110 may be remote from the differential directional sensor system 102 and communicate data with the differential directional sensor system 102 over a network, such as the network 108.

In an implementation, the client device 104 may be implemented as any of a variety of computing devices, including but not limited to a desktop computer, a notebook or portable computer, a handheld device, a netbook, an internet appliance, a tablet or tablet computer. Mobile devices (e.g., mobile phones, personal digital assistants, smart phones, etc.), server computers, and the like, or combinations thereof.

The network 108 may be a wireless or wired network, or a combination thereof. The network 108 may be a collection of individual networks interconnected with each other and functioning as a single large network (e.g., the internet or an intranet). Examples of such separate networks include, but are not limited to, telephone networks, wireline networks, local area networks (lans), wide area networks (wan), and metropolitan area networks (mans). Further, the various networks may be wireless or wired networks, or a combination thereof. A wired network may include electrical carrier wave connections (such as communication cables, etc.) and/or optical carrier waves or connections (such as fiber optic connections, etc.). The wireless network may include, for example, a WiFi network, other radio frequency networks (e.g., Zigbee, etc.), and the like.

In an implementation, the differential directional sensor system 102 may obtain an input signal from a certain set of the one or more sets of directional sensors 110 and transform the input signal from the time domain to the frequency domain to obtain a corresponding frequency band. The differential directional sensor system 102 may then apply a predetermined set of weights to the respective frequency bands in the frequency domain to obtain a combined frequency band, and transform the combined frequency band from the frequency domain to the time domain to obtain an output signal.

Differential orientation sensor System example

Fig. 2 shows the differential directional sensor system 102 in more detail. In an implementation, the differential directional sensor system 102 may include, but is not limited to, one or more processors 202, memory 204, and program data 206. In an implementation, the differential directional sensor system 102 may also include an input/output (I/O) interface 208 and/or a network interface 210. In an implementation, some of the functionality of the differential directional sensor system 102 may be implemented using hardware, such as an ASIC (i.e., an application specific integrated circuit), an FPGA (i.e., a field programmable gate array), and/or other hardware.

In implementations, the differential orientation sensor system 102 can also include a plurality of orientation (e.g., unidirectional) sensors 212 arranged in a particular geometric configuration. Although in this example, the differential orientation sensor system 102 is described as including a plurality of orientation sensors, in some cases, a plurality of orientation (e.g., unidirectional) sensors 212 may not be included in the differential orientation sensor system 102 and may be accessible to the differential orientation sensor system 102 over a network, such as the network 108, or provided to the differential orientation sensor system 102 as an auxiliary or peripheral device or component. In some cases, the differential directional sensor system 102 may include or be associated with (e.g., peripherally or remotely connected) multiple sets of directional sensors, with corresponding directional sensors in each set arranged in a respective geometric configuration. The sets of directional sensors may be of the same type or of different types. In implementations, depending on the type of signal to be detected or sensed, the directional sensor may include, but is not limited to, a directional microphone, a directional light sensor, a directional antenna (such as a directional radio antenna), a directional satellite antenna, or an antenna, etc.

In implementations, the one or more processors 202 may be configured to execute instructions stored in the memory 204 and/or received from the input/output interface 208 and/or the network interface 210. In implementations, the one or more processors 202 may be implemented as one or more hardware processors including, for example, microprocessors, dedicated instruction set processors, Physical Processing Units (PPUs), Central Processing Units (CPUs), graphics processing units, digital signal processors, tensor processing units, and the like. In addition, the functions described herein may be performed, at least in part, by one or more hardware logic components. By way of example, and not limitation, exemplary types of hardware logic components that may be used include Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), System On Chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.

The memory 204 may include processor readable media in the form of volatile memory, such as Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash RAM. Memory 204 is an example of a processor-readable medium.

Processor-readable media may include volatile or nonvolatile types of removable or non-removable media, which may implement storage of information using any method or technology. The information may include processor-readable instructions, data structures, program modules, or other data. Examples of a processor-readable medium include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other internal storage technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a processor-readable medium does not include any transitory medium such as a modulated data signal and a carrier wave.

Although only hardware components are described in the differential orientation sensor system 102 in this example, in other cases, the differential orientation sensor system 102 may also include other hardware components and/or other software components, such as program elements, to execute instructions stored in the memory 204 to perform various operations, such as processing, determining, assigning, storing, and so forth. In implementations, the differential orientation sensor system 102 can also include a weight database 214 configured to store a set of predetermined weights. Each set of predetermined weights may cause the differential orientation sensor system 102 to preferentially weight or emphasize signals received by the plurality of orientation sensors 208 from a particular preferred or desired direction relative to a particular point (e.g., a common center) in a particular geometry.

Example of the method

FIG. 3 shows a schematic diagram depicting an example method of signal processing using an example differential directional sensor system. The method of fig. 3 may (but need not) be implemented in the environment of fig. 1 and use the system of fig. 2. For ease of illustration, the method 300 is described with reference to fig. 1 and 2. However, the method 300 may alternatively be implemented in other environments and/or using other systems.

The method 300 is described in the general context of computer-executable instructions. Generally, computer-executable instructions can include routines, programs, objects, components, data structures, procedures, modules, functions, and the like that perform particular functions or implement particular abstract data types. Further, each example method is illustrated as a collection of blocks in a logical flow graph, which represent a sequence of operations that can be implemented in hardware, software, firmware, or a combination thereof. The order in which the method is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method, or an alternate method. Additionally, various blocks may be omitted from the method without departing from the spirit and scope of the subject matter described herein. In the context of software, the blocks represent computer instructions that, when executed by one or more processors, perform the recited operations. In a hardware environment, some or all of the blocks may represent Application Specific Integrated Circuits (ASICs) or other physical components that perform the operations described.

Referring to fig. 3, at block 302, the differential directional sensor system 102 may obtain or collect input signals received by a plurality of directional sensors arranged in a particular geometric configuration.

In implementations, the plurality of directional sensors may detect and receive input signals and transmit the input signals to the differential directional sensor system 102 in a wireless or wired manner depending on whether the plurality of directional sensors are included in the differential directional sensor system 102 or assisted by the differential directional sensor system 102. By way of example and not limitation, the plurality of orientation sensors may be included in the differential orientation sensor system 102. Or may be an auxiliary or peripheral device to the differential directional sensor system 102. In this case, the plurality of directional sensors may transmit input signals to the differential directional sensor system 102 through cables or wires, for example.

In practice, the particular geometric configuration may be two-dimensional or three-dimensional. In addition, the particular geometry may be formed, for example, by a plurality of circles having a common center (e.g., a two-dimensional geometry) or groups of circles having different centers, where each group of circles has the same center (e.g., a three-dimensional geometry). By way of example, and not limitation, fig. 4A-4F illustrate schematic diagrams depicting exemplary geometries of a plurality of orientation sensors. The black dots in fig. 4A-4F represent the orientation sensors and their respective locations in each geometry. The respective number of black dots in the figures (i.e., the respective number of orientation sensors) is merely an example and not a limitation. The number of orientation sensors in the particular geometry may vary and depend on the respective application specifications of the plurality of orientation sensors and/or the differential orientation sensor system 102. FIG. 4A illustrates an example configuration in which a plurality of directional sensors are distributed in a circular environment. Fig. 4B-4D illustrate different exemplary configurations, each having a plurality of concentric circles (two concentric circles are shown by way of example and not limitation) and a plurality of orientation sensors based on an environmental distribution of the plurality of concentric circles. As shown in fig. 4B-4D, the plurality of orientation sensors form different geometric configurations or shapes depending on the distribution of the plurality of orientation sensors. 4A-4D, FIGS. 4A-4D correspond to two-dimensional geometries.

Fig. 4E and 4F show examples of different geometrical configurations of the orientation sensor in three-dimensional space. Fig. 4E shows an exemplary configuration of a plurality of orientation sensors distributed over the cylindrical surface of a cylinder. Fig. 4F shows an exemplary configuration of multiple orientation sensors distributed over the spherical surface of a sphere. It is clear that other geometrical configurations, such as the configuration of a plurality of orientation sensors distributed over a plurality of coaxial cylindrical surfaces, the geometrical configuration of a plurality of orientation sensors distributed over a plurality of concentric spherical surfaces, etc. are also possible, depending on the use and application of the plurality of orientation sensors, without being limited by the invention.

In implementations, multiple orientation sensors in a geometry (such as the geometry shown in fig. 4A-4F) may or may not be equally spaced from each other. In implementations, the plurality of orientation sensors (or the respective signal sensing or detection components of the plurality of orientation sensors) may face outward from a particular point(s) of a particular geometry. For example, the plurality of orientation sensors may face outward from a center of a particular geometry (such as the geometries shown in fig. 4A-4D), or from one or more centers of the particular geometry (such as the geometries shown in fig. 4E and 4F). 4A-4F, the number of orientation sensors in the particular configuration is not so limited and may be any positive integer, such as 3, 4, 5, 8, 10, 20, 50, etc., depending on the use and application of the multiple orientation sensors or differential orientation sensor system 102, the desired quality and/or sensitivity of the multiple orientation sensors or differential orientation sensor system 102, and the type of input signal detected by the multiple orientation sensors or differential orientation sensor system 102, etc.

In an implementation, the input signal may comprise a signal from a particular direction in a predefined coordinate system associated with a particular geometry of the plurality of orientation sensors. By way of example and not limitation, the origin of the predefined coordinate system may be set at the center of the particular geometric configuration.

In implementation, the type of the plurality of directional sensors used by the differential directional sensor system 102 depends on the type of input signal. For example, if the input signal is a sound or audio signal, the type of the plurality of directional sensors is an acoustic sensor such as a directional microphone. If the input signal is a radio signal, the type of the plurality of directional sensors is a radio sensor such as a directional antenna. If the input signal is a visual signal, the type of the plurality of orientation sensors is a visual sensor such as an orientation camera.

In implementations, the orientation sensors of the plurality of orientation sensors may be unidirectional, or substantially unidirectional, with a limited signal detection range (e.g., an angular range of-2 ° to 2 °, -5 ° to 5 °, or-10 ° to 10 °, etc.) and/or with a reduced signal detection capability or gain as the angle deviates from a central axis of the signal sensing or detecting component of the orientation sensor.

At block 304, the differential directional sensor system 102 may perform a first predetermined transformation on the input signal to obtain a corresponding transformed signal.

In an implementation, after obtaining or collecting input signals from the plurality of directional sensors, the differential directional sensor system 102 may perform a first predetermined transformation on the input signals to convert the input signals from one domain to another. By way of example and not limitation, differential directional sensor system 102 may apply a first predetermined transform to the input signal to convert the input signal from the time domain to the frequency domain and obtain a corresponding frequency band. In implementations, the first predetermined transform may include, but is not limited to, a short-time fourier transform, a set of predetermined filter banks, or any transform capable of transforming a signal from the time domain to the frequency domain, etc.

Additionally or alternatively, the differential directional sensor system 102 may apply a first predetermined transformation or decomposition to the input signal to convert the input signal from one representation to another. Examples of the first predetermined transform or decomposition may include, but are not limited to, a wavelet transform or the like, depending on the type of input signal, such as an audio signal, a radio signal, or a visual signal.

At block 306, the differential directional sensor system 102 may apply a set of predetermined weights to the respective transformed signals to obtain a combined signal.

In implementations, the differential directional sensor system 102 may apply a predetermined set of weights to the respective transformed signals after obtaining the respective transformed signals from the input signals. In implementations, a number of the predetermined weights in the set of predetermined weights is equal to a number of the orientation sensors in the geometry of the plurality of orientation sensors. In implementations, the predetermined weights of the predetermined set of weights have a one-to-one correspondence with the plurality of orientation sensors in the geometric configuration.

In an implementation, the differential directional sensor system 102 may select the set of predetermined weights from a set of predetermined weights based on a particular direction. The set of predetermined weights may comprise respective sets of predetermined weights for the predetermined weights for different directions in a predetermined coordinate system associated with the particular geometry. In implementations, the set of predetermined weights selected by the differential orientation sensor system 102 may correspond to a particular direction under a predetermined coordinate system associated with a particular geometry of the plurality of orientation sensors.

In an implementation, the differential directional sensor system 102 may store a set of predetermined sets of weights in the memory 204 (e.g., the weight database 214). Additionally or alternatively, the set of predetermined sets of weights may be stored in a remote or peripheral device of the differential orientation sensor system 102, such as one or more servers 106 or a peripheral device of the differential orientation sensor system 102, and the differential orientation sensor system 102 is allowed to access the set of predetermined sets of weights from the remote or peripheral device.

In implementations, each set of predetermined weights may prioritize weighting or emphasizing signals received by the plurality of orientation sensors 208 from a particular preferred or desired direction relative to a particular point in a particular geometry (e.g., a common center) or coordinate system origin associated with a particular geometry, e.g., the origin is a common center. In this case, the differential directional sensor system 102 may select a set of predetermined weights from a set of predetermined weights and apply the set of predetermined weights to the corresponding transformed signals to obtain a combined signal. In other words, by selecting a set of different predetermined weights (e.g., a particular set of predetermined weights for a particular preferred or desired direction), the differential orientation sensor system 102 can electronically adjust the plurality of orientation sensors to receive signals from the preferred or desired direction without mechanically moving the plurality of orientation sensors and/or any physical portion of the differential orientation sensor system 102.

In implementations, the set of predetermined sets of weights may be predetermined or calculated based at least in part on one or more predefined constraints, a beam pattern of the plurality of directional sensors, a number of the plurality of directional sensors, and a relative position of the plurality of directional sensors in a coordinate system associated with the particular geometry. In an implementation, the predetermined weights may be frequency dependent, i.e. each predetermined weight is a function dependent on frequency. An example method of determining or calculating a set of predetermined weight sets associated with a particular geometry of a plurality of orientation sensors of different input signal directions or angles will be described in a subsequent section.

At block 308, the differential directional sensor system 102 may perform a second predetermined transformation on the combined signal to obtain an output signal.

In implementations, after applying the predetermined set of weights to the respective transformed signals to obtain the combined signal, the differential directional sensor system 102 may perform a second predetermined transformation on the combined signal to obtain an output signal. In implementations, the second predetermined transformation is the inverse or inverse of the first predetermined transformation. For example, if a first predetermined transformation is used to transform a signal from a first representation or domain (e.g., the time domain) to a second representation or domain (e.g., the frequency domain), the second predetermined transformation is used to transform a signal from the second representation or domain to the first representation or domain.

Although the method blocks described above are described as being performed in a particular order, in some implementations some or all of the method blocks may be performed in other orders, or in parallel. For example, the differential directional sensor system 102 may obtain new input signals from a plurality of directional sensors while processing (such as transforming, weighting, inverse transforming, etc.) input signals previously obtained from the plurality of directional sensors, or input signals obtained from another set or sets of directional sensors to which the differential directional sensor system 102 is connected and responsible, and so forth.

Additionally, although in this example, the differential orientation sensor system 102 is described as including or being associated with a particular set of orientation sensors (i.e., a plurality of orientation sensors arranged in a particular geometric configuration as described above), the differential orientation sensor system 102 may include or be associated with a plurality of sets of orientation sensors and process respective signals received from each set of orientation sensors as described above. The sets of directional sensors may or may not be of the same type (i.e., acoustic, radio, visual, etc.) and may or may not be of the same geometric configuration. In this case, the differential directional sensor system 102 may store or access a set of various predetermined sets of weights applicable to these multiple sets of directional sensors.

Additionally, the differential directional sensor system 102 may estimate or determine the direction from which or from which a desired or determined signal originates. By way of example and not limitation, the differential directional sensor system 102 may determine respective signal strengths of desired or particular signals received by a plurality of directional sensors. The differential directional sensor system 102 may then estimate or determine the direction from or from which the desired signal or particular signal originated, based on the detected signal strength of the desired signal or particular signal, by, for example, a weighted average direction of one or more directional sensors.

Example orientation sensor configuration

By way of example, and not limitation, directional microphones are used herein as examples of the directional sensors described above. It should be noted that the present application is not limited to this example of an orientation sensor, and other types of orientation sensors may be used and applied to the present application.

In an implementation, the beam pattern of the directional microphone may be expressed as p + (1-p) cos α, where α is the off-axis angle and p defines the properties of the directional microphone. For example, a cardioid beam pattern is generated when p is 0.5, and a dipole is generated when p is 0. In implementation, the directional microphone may be implemented using two methods, namely, a first method using a dedicated directional microphone with a microphone case having two sound inlets, and a second method using a dual omnidirectional element system with appropriate digital signal processing. Since in the first method the signal processing to generate directivity is done by means of acoustic front and back sound entrances of dedicated directional microphones, the directional microphones generated by the first method are better in terms of signal-to-noise ratio (SNR) than the second method. In implementation, the dedicated directional microphone may be implemented in the form of an ECM (electret condenser microphone) or MEMS (micro electro mechanical system).

For ease of description, a circular configuration is exemplified having directional sensors (e.g., directional microphones) distributed in a circular environment. Nevertheless, the following description may also be applicable to other more complex geometries of directional sensors (e.g., directional microphones) as they may be formed from, or broken down into, multiple concentric circles, or groups of circles with different centers, each group of circles having the same center, with the directional sensors distributed accordingly in the environment of the multiple concentric circles, or in the environment of multiple ones of the groups of circles, as shown in fig. 4A-4F. The results for these complex geometries of the orientation sensor can then be obtained by superimposing the respective results for the individual circles of the orientation sensor.

In implementations, this circular configuration of directional microphones may be referred to as a Circular Differential Directional Microphone Array (CDDMA). In this example, a single desired sound source in the far field is considered and appears as a plane wave impinging on a circular configuration of M directional microphones of radius r. As shown in fig. 5, the directional microphones are distributed in a circular environment and directed to the outside. The directional microphones may be uniformly distributed or may be non-uniformly distributed. For simplicity and without loss of generality, in this example, the directional microphones are described as being uniformly distributed. The azimuth angle θ represents the direction in which sound arrives from the sound source, and c represents the sound velocity.

In this case, the steering vector is defined as:

d(ω,θ)＝[d 1,d 2,…,d m,…,d M]T (1)

wherein the superscript T is a transpose operator, and for a uniformly distributed CDDMA, each element in equation (1) can be obtained by the following equation:

wherein is prepared from

Imaginary unit, ω ═ 2 π f is angular frequency, f is temporal frequency, and

is the angular position of the mth element in the CDDMA, which is evenly distributed in this example.

Using equation (2), the steering vector d (ω, θ) can be rewritten as d (ω, θ) ═ U (p, θ) a (ω, θ) (3)

Wherein a (ω, θ) ═ a₁,a₂,…,a_m,…,a_M]^T (4)

Wherein the content of the first and second substances,

and U (p, θ) ═ diag (U)₁,u₂,…,u_M,…,u_M) (5)

U (p, θ) is called the microphone response matrix, where

In implementation, differential beamforming with an array of microphones (or differential beamformer or simply beamformer below) may be used to estimate a target signal arriving from a desired direction in the presence of noise and interference. In this example, differential beamforming can be interpreted as a spatial filter to estimate signals from a desired direction and suppress signals from other undesired directions by applying complex weight vectors:

h(ω)＝[H₁(ω)H₂(ω)…H_M(ω)]^T (6)

given a signal model, the beamformer may exhibit a response in the desired direction θ that is undistorted, but some distortion in the response to other undesired directions, i.e.,

wherein the superscript H is the conjugate transpose operator.

In an implementation, three performance metrics are defined herein, namely White Noise Gain (WNG), Directivity Factor (DF), and (frequency invariant) beam pattern. In an implementation, WNG may show the ability of the beamformer to suppress spatially uncorrelated noise and may be used to assess the sensitivity of the beamformer to certain imperfections (e.g., sensor noise, position errors, etc.). In an implementation, WNG may be defined as:

in implementation, the beam pattern may account for the directional sensitivity of the beamformer to plane waves incident on the array from the angle of incidence θ (as shown in fig. 1):

in practice, power mode

I.e. may be used to represent performance. It should be noted that the frequency is notA varying beam pattern is generally desirable or preferred. In implementation, DF may be defined as the ratio between the signal power in the desired steering direction (in the array output) and the signal power averaged over all directions:

wherein, theta is an azimuth angle,

is the angle of elevation,

is the beam pattern in the spherical coordinate system. In an implementation, a Directional Index (DI) may be defined as

In implementation, to design a CDDMA beamformer, the problem can be formulated as a system of linear equations, as follows:

R(ω,θ)h(ω)＝cθ (11)

where h (ω) is the CDDMA beamforming weight to be obtained (i.e., the set of predetermined weights as described above). c. C_θIs a constraint vector which is

Wherein θ ═ θ₁,θ₂,…,θ_N]Is an angle vector, N is the number of constraints that N ≦ m. R (ω, θ) is a constraint matrix of n × m, given by:

in implementation, based on equation (11), the properties of the beamformer can be represented by the constraint vector c_θAnd the angular parameter vector theta that needs to be specified in the design. By way of example and not limitation, if in equation (11)

The steering vector at θ 1 follows d^H(ω,θ₁) h (ω) ═ 1, which means that θ 1 becomes the desired direction of the CDDMA beamformer, which produces an undistorted output of sound from that direction. For i ═ 2,3, …, the remainder of N

Can be set to zero, i.e. these theta_iThe null value of the beam pattern is determined or decided.

In an implementation, a linear system equation such as equation (11) may be solved using a minimum norm solution, and the CDDMA beamformer may be obtained by the following equation:

h(ω)＝R^H(ω,θ)[R(ω,θ)R^H(ω,θ)]^-1c_θ (13)

for example, if the desired direction θ is 0 degrees, i.e., c in equation (11)₀1 and p in equation (2) is 0.5, i.e. with a cardioid element as an example of a directional microphone to form a CDDMA beamformer. Fig. 6A-6F show a comparison of beam patterns of two different designs between CDDMA and a Circular Differential Microphone Array (CDMA) using omni-directional microphones with frequencies of 1khz, 3khz and 6khz, where r-1.5 cm and M-8 are used. The first design is to construct a first heart line (c)_π0) and the second design is to construct a second order cardioid

As shown in fig. 6A, 6C and 6E, the beam patterns for CDDMA and CDMA are very close to the 1 st order cardioid required at 1kHz and 3 kHz. The CDMA beam pattern deviates significantly at 6kHz while the CDDMA beam pattern is still suitable for the desired design. Thus, CDDMA is more frequency invariant than CDMA for a 1 st order cardioid design. As shown in fig. 6B, 6D, and 6F, CDMA and CDDMA are both very frequency invariant for the 2 nd order cardioid design.

Figures 7A and 7B show a comparison of CDDMA and CDMA in WNG and DI in the same design described above. As can be seen in fig. 7A, CDDMA of both designs exhibits a higher WNG than CDMA at low frequencies. As can be seen from fig. 7B, CDDMA is improved in DI of a high frequency band compared to CDMA. Finally, for CDMA and CDDMA, a high order beamformer would result in a higher DI and a lower WNG at low frequencies. Thus, CDDMA with the small norm solution is more frequency invariant than CDMA using omni-directional microphones, the WNG of the CDDMA beamformer is significantly improved at low frequencies, while the DI of the CDDMA beamformer is improved at high frequencies compared to CDMA.

Conclusion

Although embodiments have been described in language specific to structural features and/or methodological acts, it is to be understood that the claims are not necessarily limited to the specific features or acts described. Rather, the specific features and acts are disclosed as exemplary forms of implementing the claimed subject matter. Additionally or alternatively, some or all of the operations may be implemented by one or more ASICS, FPGAs, or other hardware.

The present application may be further understood using the following clauses.

Clause 1 a method implemented by a computing device, the method comprising obtaining input signals received by a plurality of orientation sensors arranged in a particular configuration; transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band; applying a predetermined set of weights to respective frequency bands in the frequency domain to obtain a combined frequency band; and transforming the combined frequency band from the frequency domain to the time domain to obtain an output signal.

Clause 2-the method of clause 1, wherein the particular configuration comprises a circular configuration, wherein the orientation sensor is located in a circular environment having a predetermined radius, and the orientation sensor faces outward from a center of the circle.

Clause 3-the method of clause 1, wherein the particular configuration comprises a configuration in which the orientation sensor is located in one or more environments corresponding to one or more concentric circles having different radii, and the orientation sensor is outside of a common central plane of the one or more concentric circles.

Clause 4-the method of clause 1, wherein transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band comprises: a short time fourier transform or a predetermined filter bank is applied to the input signal.

Clause 5-the method of clause 1, wherein the input signal comprises a signal from a particular direction in a predetermined coordinate system associated with the plurality of orientation sensors.

Clause 6 the method of clause 5, further comprising: determining the set of predetermined weights from a set of predetermined weights based on the particular direction, the set of predetermined weights comprising respective sets of predetermined weights for different directions under a predetermined coordinate system associated with centers of the plurality of orientation sensors.

Clause 7 the method of clause 1, wherein the predetermined weight is calculated based on at least a portion of: one or more predetermined constraints, a beam pattern of the directional sensors, a number of the directional sensors, and a relative position of the directional sensors in a coordinate system associated with the plurality of directional sensors.

Clause 8-the method of clause 1, wherein the predetermined weight is dependent on frequency.

Clause 9-the method of clause 1, wherein the plurality of directional sensors comprises a plurality of directional microphones.

Clause 10-a system, comprising a plurality of orientation sensors arranged in a particular configuration, the plurality of orientation sensors configured to receive an input signal; a memory configured to store a set of predetermined sets of weights; one or more processors configured to obtain input signals received by a plurality of orientation sensors arranged in a particular configuration; transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band; applying a predetermined set of weights to respective frequency bands in the frequency domain to obtain a combined frequency band; and transforming the combined frequency band from the frequency domain to the time domain to obtain an output signal.

Clause 11-the system of clause 10, wherein the particular configuration comprises a circular configuration, wherein the orientation sensor is located in a circular environment having a predetermined radius, and the orientation sensor faces outward from a center of the circle.

Clause 12-the system of clause 10, wherein the particular configuration comprises a configuration in which the orientation sensor is located in one or more environments corresponding to one or more concentric circles having different radii, and the orientation sensor is outside of a common central plane of the one or more concentric circles.

Clause 13-the system of clause 10, wherein transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band comprises: a short time fourier transform or a predetermined filter bank is applied to the input signal.

Clause 14-the system of clause 10, wherein the input signal comprises a signal from a particular direction in a predetermined coordinate system associated with the plurality of orientation sensors.

Clause 15 the system of clause 14, wherein the one or more processors are further configured to: determining the set of predetermined weights from a set of predetermined weights based on the particular direction, the set of predetermined weights comprising respective sets of predetermined weights for different directions under a predetermined coordinate system associated with centers of the plurality of orientation sensors.

Clause 16 the system of clause 10, wherein the predetermined weight is calculated based on at least a portion of: one or more predetermined constraints, a beam pattern of the directional sensors, a number of the directional sensors, and a relative position of the directional sensors in a coordinate system associated with the plurality of directional sensors.

Clause 17-the system of clause 10, wherein the predetermined weight is dependent on frequency.

Clause 18-the system of clause 10, wherein the plurality of directional sensors comprises a plurality of directional microphones.

Clause 19 one or more computer-readable media storing executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising obtaining input signals received by a plurality of orientation sensors arranged in a particular configuration; transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band; applying a predetermined set of weights to respective frequency bands in the frequency domain to obtain a combined frequency band; and transforming the combined frequency band from the frequency domain to the time domain to obtain an output signal.

Clause 20 the one or more computer-readable media of clause 19, wherein the input signal comprises a signal from a particular direction in a predetermined coordinate system associated with the plurality of orientation sensors, the operations further comprising: determining the set of predetermined weights from a set of predetermined weights based on the particular direction, the set of predetermined weights comprising respective sets of predetermined weights for different directions under a predetermined coordinate system associated with centers of the plurality of orientation sensors.

Claims

1. A method implemented by a computing device, the method comprising obtaining input signals received by a plurality of orientation sensors arranged in a particular configuration; transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band; applying a predetermined set of weights to respective frequency bands in the frequency domain to obtain a combined frequency band; and transforming the combined frequency band from the frequency domain to the time domain to obtain an output signal.

2. The method of claim 1, wherein the particular configuration comprises a circular configuration, wherein the orientation sensor is located in a circular environment having a predetermined radius, and the orientation sensor faces outward from a center of the circle.

3. The method of claim 1, wherein the particular configuration comprises a configuration in which the orientation sensor is located in one or more environments corresponding to one or more concentric circles having different radii, and the orientation sensor is outside of a common centerplane of the one or more concentric circles.

4. The method of claim 1, wherein transforming the input signal from a time domain to a frequency domain to obtain respective frequency bands comprises: a short time fourier transform or a predetermined filter bank is applied to the input signal.

5. The method of claim 1, wherein the input signal comprises a signal from a particular direction in a predetermined coordinate system associated with the plurality of directional sensors.

6. The method of claim 5, further comprising: determining the set of predetermined weights from a set of predetermined weights based on the particular direction, the set of predetermined weights comprising respective sets of predetermined weights for different directions under a predetermined coordinate system associated with centers of the plurality of orientation sensors.

7. The method of claim 1, wherein the predetermined weight is calculated based on at least a portion of: one or more predetermined constraints, a beam pattern of the directional sensors, a number of the directional sensors, and a relative position of the directional sensors in a coordinate system associated with the plurality of directional sensors.

8. The method of claim 1, wherein the predetermined weight is frequency dependent.

9. The method of claim 1, wherein the plurality of directional sensors comprises a plurality of directional microphones.

10. A system comprising a plurality of orientation sensors arranged in a particular configuration, the plurality of orientation sensors configured to receive an input signal; a memory configured to store a set of predetermined sets of weights; one or more processors configured to obtain input signals received by a plurality of orientation sensors arranged in a particular configuration; transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band; applying a predetermined set of weights to respective frequency bands in the frequency domain to obtain a combined frequency band; and transforming the combined frequency band from the frequency domain to the time domain to obtain an output signal.

11. The system of claim 10, wherein the particular configuration comprises a circular configuration, wherein the orientation sensor is located in a circular environment having a predetermined radius, and the orientation sensor faces outward from a center of the circle.

12. The system of claim 10, wherein the particular configuration comprises a configuration in which the orientation sensor is located in one or more environments corresponding to one or more concentric circles having different radii, and the orientation sensor is outside of a common centerplane of the one or more concentric circles.

13. The system of claim 10, wherein transforming the input signal from the time domain to the frequency domain to obtain respective frequency bands comprises: a short time fourier transform or a predetermined filter bank is applied to the input signal.

14. The system of claim 10, wherein the input signal comprises a signal from a particular direction in a predetermined coordinate system associated with the plurality of directional sensors.

15. The system of claim 14, wherein the one or more processors are further configured to: determining the set of predetermined weights from a set of predetermined weights based on the particular direction, the set of predetermined weights comprising respective sets of predetermined weights for different directions under a predetermined coordinate system associated with centers of the plurality of orientation sensors.

16. The system of claim 10, wherein the predetermined weight is calculated based at least on a portion of: one or more predetermined constraints, a beam pattern of the directional sensors, a number of the directional sensors, and a relative position of the directional sensors in a coordinate system associated with the plurality of directional sensors.

17. The system of claim 10, wherein the predetermined weight is frequency dependent.

18. The system of claim 10, wherein the plurality of directional sensors comprises a plurality of directional microphones.

19. One or more computer-readable media storing executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising obtaining input signals received by a plurality of orientation sensors arranged in a particular configuration; transforming the input signal from the time domain to the frequency domain to obtain a corresponding frequency band; applying a predetermined set of weights to respective frequency bands in the frequency domain to obtain a combined frequency band; and transforming the combined frequency band from the frequency domain to the time domain to obtain an output signal.

20. The one or more computer-readable media of claim 19, wherein the input signal comprises a signal from a particular direction in a predetermined coordinate system associated with the plurality of orientation sensors, the operations further comprising: determining the set of predetermined weights from a set of predetermined weights based on the particular direction, the set of predetermined weights comprising respective sets of predetermined weights for different directions under a predetermined coordinate system associated with centers of the plurality of orientation sensors.