Angle of arrival estimation method and communication apparatus

Abstract

An angle of arrival estimation method and a communication apparatus, relating to the technical field of wireless communications, reducing the difficulty and costs of implementing antenna solutions to integrated sensing and communication technologies, and improving stability. The angle of arrival estimation method is applied to a communication apparatus, and the communication apparatus comprises a plurality of antennas. The angle of arrival estimation method comprises: by means of the plurality of antennas, transmitting on N different frequency bands sensing signals to an object to be detected, N being an integer greater than 1; by means of the plurality of antennas, receiving N echo signals; on the basis of the N echo signals, determining echo signal matrices so as to obtain N echo signal matrices; and, on the basis of the N echo signal matrices, determining the angle of arrival of said object with respect to the communication apparatus. The angle of arrival estimation method is used by communication apparatuses for ranging and angle measurement.

Description

Angle of arrival estimation method and communication device Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to an angle-of-arrival estimation method and a communication device. Background Technology

[0002] The technology of integrated communication and sensing is currently gaining increasing attention. It can also be called communication-sensing integration, which means that electronic devices combine communication and sensing capabilities. That is, while providing mobile communication capabilities, electronic devices also have radar-like functions (sensing capabilities), which can detect and track objects such as drones, cars or ships in the vicinity.

[0003] Electronic devices can measure the distance and angle of targets for positioning and sensing. When only ranging functionality is provided, the antenna system of the electronic device is typically based on a one-transmitter-one-receiver (1T1R) architecture. When both ranging and angle measurement functions are implemented, the antenna system of the electronic device is primarily based on a one-transmitter-n-receiver (1TnR) architecture or an n-transmitter-n-receiver (nTnR) architecture.

[0004] Integration is a major trend. In multi-antenna systems with angle measurement capabilities, each antenna often needs to radiate in roughly the same direction, forming an array with an inter-antenna spacing of about half a wavelength. This multi-antenna system differs from existing single-antenna systems, which consist of only a single antenna that radiates omnidirectionally. Consequently, the implementation of this integrated sensing antenna solution is challenging, costly, and unstable. Summary of the Invention

[0005] This application provides an angle-of-arrival estimation method and a communication device, which reduces the implementation difficulty and cost of antenna solutions for integrated communication and sensing technologies, and improves stability.

[0006] To achieve the above objectives, the embodiments of this application adopt the following technical solutions.

[0007] In a first aspect, embodiments of this application provide an angle-of-arrival (AOA) estimation method applied to a communication device, which includes multiple antennas. The AOA estimation method includes: transmitting sensing signals to a target object via the multiple antennas on N different frequency bands, where N is an integer greater than 1; receiving N echo signals via the multiple antennas; determining echo signal matrices based on the N echo signals to obtain N echo signal matrices; and determining the AOA of the target object relative to the communication device based on the N echo signal matrices.

[0008] In this angle-of-arrival (AOA) estimation method, the communication device can transmit sensing signals to the object under test (AUT) via multiple antennas on N different frequency bands to obtain N echo signals and construct N echo signal matrices. That is, the communication device employs a channel splicing scheme, where the radar signals or echo signals on the N different frequency bands can be equivalent to a wider bandwidth frequency-modulated continuous wave (FM continuous wave), thereby improving the distance resolution of the AUT relative to the communication device and obtaining a more accurate AOA. Furthermore, the positions of the multiple antennas in this AOA estimation method can be arbitrarily set, and there is no half-wavelength distance limitation on the distance between the multiple antennas. This method can reuse existing multi-antenna systems, resulting in low implementation difficulty, low cost, and high stability.

[0009] In one possible implementation, the echo signal matrix is ​​determined based on the N echo signals to obtain N echo signal matrices, including arranging the N echo signals in ascending order according to the frequencies of their corresponding frequency bands to obtain the echo signal matrices.

[0010] In this implementation, the N echo signals in the echo signal matrix are arranged in ascending order of frequency, which can realize a frequency-modulated continuous wave with a larger bandwidth. This can improve the distance resolution of the object under test relative to the communication device and obtain a more accurate angle of arrival of the object under test relative to the communication device.

[0011] In one possible implementation, determining the angle of arrival of the object under test relative to the communication device based on N echo signal matrices includes: performing maximum likelihood estimation on the N echo signal matrices according to a preset echo signal matrix to obtain multiple distances of the object under test relative to multiple antennas, wherein the preset echo signal matrix includes the correspondence between distances and echo signals; determining the phase of the object under test relative to the multiple antennas based on the multiple distances; and determining the angle of arrival of the object under test relative to the communication device based on the phase of the multiple antennas.

[0012] In this implementation, the communication device performs maximum likelihood estimation on N echo signal matrices based on a preset echo signal matrix. This method is compatible with target distance calculation in certain scenarios (such as channel discontinuities). By evaluating the target distance using the maximum likelihood estimation algorithm, the distance resolution of the target object relative to the communication device can be improved, and a more accurate angle of arrival of the target object relative to the communication device can be obtained.

[0013] In one possible implementation, before determining the angle of arrival of the object under test relative to the communication device based on the phases of the multiple antennas, the method further includes: if the difference in distances between two of the multiple antennas is greater than a first preset threshold, performing phase compensation on two of the multiple antennas to determine the phase of the object under test relative to two of the multiple antennas.

[0014] In this implementation, the communication device can also determine whether to perform phase compensation based on the difference in distance between the two antennas and a preset threshold, so as to obtain a more accurate phase and further improve the distance resolution.

[0015] In one possible implementation, determining the angle of arrival of the object under test relative to the communication device based on N echo signal matrices includes: determining a multi-antenna echo signal matrix based on the N echo signal matrices; performing maximum likelihood estimation processing on the multi-antenna echo signal matrix based on a preset multi-antenna echo signal matrix to obtain the distance and angle of arrival of the object under test relative to the communication device; the preset multi-antenna echo signal matrix includes the correspondence between multiple distances and multiple echo signals.

[0016] In this implementation, in scenarios involving multiple objects to be measured, the communication device can perform maximum likelihood estimation on the multi-antenna echo signal matrix to estimate the angle of arrival for multiple objects. Therefore, the angle of arrival estimation method provided in this application embodiment is compatible with both angle and distance measurement for a single object and multiple objects.

[0017] In one possible implementation, determining the angle of arrival of the object under test relative to the communication device based on N echo signal matrices includes: determining a multi-antenna echo signal matrix based on the N echo signal matrices, and inputting the multi-antenna echo signal matrix into an artificial intelligence (AI) model to obtain the distance and angle of arrival of the object under test relative to the communication device.

[0018] In this implementation, in scenarios involving multiple objects to be measured, the communication device can input a multi-antenna echo signal matrix into an AI model to estimate the angle of arrival (AOA) for multiple objects. Therefore, the AOA estimation method provided in this application is compatible with both angle and distance measurement for single and multiple objects.

[0019] In one possible implementation, before determining the angle of arrival of the object under test relative to the communication device based on the N echo signal matrices, the method further includes filtering the N echo signal matrices respectively to obtain filtered N echo signal matrices.

[0020] In this implementation, the communication device can filter the echo signal matrix to remove useless information and noise, thereby improving the quality of the echo signal and enhancing the angle and distance measurement accuracy of the communication device.

[0021] In one possible implementation, the multiple antennas include a first antenna and a second antenna, and the distance between the first antenna and the second antenna is greater than a second preset threshold.

[0022] In this implementation, the second preset threshold can be half a wavelength. Compared to the antenna array angle measurement scheme, which requires the distance between the first and second antennas to be less than half a wavelength, the distance between the first and second antennas in the communication device provided in this application embodiment can be greater than half a wavelength. Therefore, the angle of arrival estimation method provided in this application embodiment can reuse existing multi-antenna systems, and is easy to implement, low in cost, and highly stable.

[0023] Secondly, embodiments of this application provide a communication device, comprising: a processing module, multiple transmitting antennas, and multiple receiving antennas. The multiple transmitting antennas are used to transmit sensing signals to a test object on N different frequency bands, where N is an integer greater than 1. The multiple receiving antennas are used to receive N echo signals. The processing module is used to determine echo signal matrices based on the N echo signals to obtain N echo signal matrices. The processing module is also used to determine the angle of arrival of the test object relative to the communication device based on the N echo signal matrices.

[0024] In one possible implementation, the processing module is specifically used to: arrange the N echo signals in ascending order according to the frequency of the corresponding frequency band to obtain an echo signal matrix.

[0025] In one possible implementation, the processing module is specifically configured to: perform maximum likelihood estimation processing on the N echo signal matrices according to a preset echo signal matrix to obtain multiple distances of the object under test relative to the multiple antennas, wherein the preset echo signal matrix includes the correspondence between distances and echo signals; determine the phase of the object under test relative to the multiple antennas based on the multiple distances; and determine the angle of arrival of the object under test relative to the communication device based on the phase of the multiple antennas.

[0026] In one possible implementation, the processing module is further configured to: if the difference in distance between two of the plurality of antennas is greater than a first preset threshold, perform phase compensation on two of the plurality of antennas to determine the phase of the object under test relative to two of the plurality of antennas.

[0027] In one possible implementation, the processing module is specifically used to: determine a multi-antenna echo signal matrix based on the N echo signal matrices, and perform maximum likelihood estimation processing on the multi-antenna echo signal matrix based on a preset multi-antenna echo signal matrix to obtain the distance and angle of arrival of the object under test relative to the communication device. The preset multi-antenna echo signal matrix includes a correspondence between multiple distances and multiple echo signals.

[0028] In one possible implementation, the processing module is specifically used to: determine a multi-antenna echo signal matrix based on the N echo signal matrices, and input the multi-antenna echo signal matrix into an artificial intelligence (AI) model to obtain the distance and angle of arrival of the object under test relative to the communication device.

[0029] In one possible implementation, the processing module is further configured to: filter the N echo signal matrices respectively to obtain the filtered N echo signal matrices.

[0030] In one possible implementation, the plurality of antennas includes a first antenna and a second antenna, wherein the distance between the first antenna and the second antenna is greater than a second preset threshold.

[0031] The communication device in the second aspect can be a terminal device, a chip (system) or other component or assembly that can be set in the terminal device, or a device that includes the terminal device. This application does not limit this.

[0032] Thirdly, embodiments of this application provide an electronic device including a plurality of antennas, one or more processors, and one or more memories. The one or more memories are coupled to the one or more processors, and the one or more memories are used to store computer program code, which includes computer instructions. When the one or more processors execute the computer instructions, the electronic device performs the angle-of-arrival estimation method in any of the possible implementations of the first aspect described above.

[0033] Fourthly, embodiments of this application provide a computer-readable storage medium including computer instructions that, when executed on an electronic device, cause the electronic device to perform the angle of arrival estimation method in any possible implementation of the first aspect described above.

[0034] Fifthly, embodiments of this application provide a computer program product that, when run on a computer or processor, causes the computer or processor to execute the angle of arrival estimation method in any of the possible implementations of the first aspect described above.

[0035] Sixthly, embodiments of this application provide a system that may include a wireless access device and at least one electronic device. The electronic device and the wireless access device may perform the angle-of-arrival estimation method in any of the possible implementations of the first aspect described above.

[0036] It is understood that any of the communication devices, electronic devices, computer-readable storage media or computer program products provided above can be applied to the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0037] These or other aspects of this application will become more readily apparent in the following description. Attached Figure Description

[0038] Figure 1 is a schematic diagram of a communication system provided in an embodiment of this application;

[0039] Figure 2 is a schematic diagram of a time-division WIFI radar / communication sensing integrated system provided in an embodiment of this application;

[0040] Figure 3 is a schematic diagram of a triangulation angle measurement method provided in an embodiment of this application;

[0041] Figure 4 is a schematic diagram of an antenna array angle measurement provided in an embodiment of this application;

[0042] Figure 5 is a flowchart of an angle of arrival estimation method provided in an embodiment of this application;

[0043] Figure 6 is a schematic diagram of an echo signal matrix provided in an embodiment of this application;

[0044] Figure 7 is a waveform diagram of an echo signal matrix provided in an embodiment of this application;

[0045] Figure 8 is a schematic diagram of a channel splicing method provided in an embodiment of this application;

[0046] Figure 9 is a schematic diagram of another channel splicing method provided in an embodiment of this application;

[0047] Figure 10 is a flowchart of another angle of arrival estimation method provided in an embodiment of this application;

[0048] Figure 11 is a flowchart of another angle of arrival estimation method provided in an embodiment of this application;

[0049] Figure 12 is a flowchart of another angle of arrival estimation method provided in an embodiment of this application;

[0050] Figure 13 is a schematic diagram of an OTN router provided in an embodiment of this application;

[0051] Figure 14 is a schematic diagram of the structure of an antenna system in a mobile phone according to an embodiment of this application;

[0052] Figure 15 is a schematic diagram of the structure of the communication device provided in the embodiment of this application. Detailed Implementation

[0053] To better understand the embodiments of this application, the following points are explained before introducing the embodiments of this application.

[0054] First, in the embodiments of this application, the terms "first," "second," and various numerical designations are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. For example, they distinguish different instruction information. Similarly, "first network region" and "second network region" are simply used to distinguish different regions and do not limit their order. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or execution order, and that "first," "second," etc., are not necessarily different.

[0055] Second, in the embodiments of this application, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the fact that the device (e.g., a terminal device or a network device) will make corresponding processing under certain objective circumstances. They are not time limits, nor do they require the device (e.g., a terminal device or a network device) to make a judgment action when implementing it, nor do they imply any other limitations.

[0056] Third, in the embodiments of this application, the words "exemplary" or "for example" are used to indicate that they are examples, illustrations, or descriptions. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner to facilitate understanding.

[0057] Fourth, in the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of multiple items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0058] Finally, the network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0059] This application will present various aspects, embodiments, or features relating to a system that may include multiple devices, components, modules, etc. It should be understood and appreciated that individual systems may include additional devices, components, modules, etc., and / or may not include all the devices, components, modules, etc. discussed in conjunction with the accompanying drawings. Furthermore, combinations of these approaches may also be used.

[0060] The technical solutions of this application embodiment can be applied to various communication systems, such as wireless fidelity (Wi-Fi) systems, vehicle-to-everything (V2X) communication systems, device-to-device (D2D) communication systems, vehicle-to-everything (V2X) communication systems, 4th generation (4G) mobile communication systems, such as long term evolution (LTE) systems, worldwide interoperability for microwave access (WiMAX) communication systems, 5th generation (5G) mobile communication systems, such as new radio (NR) systems, and future communication systems, etc.

[0061] The relevant technologies involved in the embodiments of this application will be described below.

[0062] 1. Integrated Sensing and Communication (ISAC)

[0063] ISAC can also be called Joint Communications and Sensing (JCS) or Joint Communications and Sensing (JCAS). In future mobile communication systems, higher frequency bands (millimeter waves and even terahertz), wider bandwidths, and larger-scale antenna arrays make high-precision, high-resolution sensing possible, allowing ISAC to be implemented in a single system, making communication and sensing functions complementary. On the one hand, the entire communication network can act as a giant sensor, with network elements sending and receiving wireless signals. By utilizing the transmission, reflection, and scattering of radio waves, the physical world can be better perceived and understood. By obtaining distance, speed, and angle information from wireless signals, a wide range of new services can be provided, such as high-precision positioning, gesture capture, motion recognition, passive object detection, imaging, and environmental reconstruction, realizing "network as a sensor." On the other hand, the high-precision positioning, imaging, and environmental reconstruction capabilities provided by sensing can help improve communication performance, such as more accurate beamforming and faster beam failure recovery, realizing "sensing-assisted communication." Sensing is also a "new channel" for observing and sampling the physical and biological worlds, connecting them to the digital world. Future applications of the ISAC system are likely to include ultra-high precision positioning, synchronous imaging, map building, and human sensory enhancement.

[0064] 2. Multiple-input multiple-output (MIMO) technology

[0065] MIMO technology refers to the use of multiple antennas to transmit and receive signals in the field of wireless communication. Network devices and terminal devices can use MIMO technology to achieve power gain, spatial diversity gain, and spatial multiplexing gain. Spatial diversity refers to introducing signal redundancy in space to achieve diversity. For example, a terminal device can transmit two orthogonal data streams through two antennas to obtain diversity gain. Spatial multiplexing refers to transmitting multiple independent data streams on the same time-frequency resource on each antenna to improve spectral efficiency without increasing spectrum resources. For example, a terminal device can map the uplink data layer into two independent data streams and transmit them simultaneously through multiple antennas, thus multiplexing spatial resources on the same time-frequency resource.

[0066] 3. Antenna

[0067] An antenna is an electronic device used to transmit or receive radio waves or electromagnetic waves. Physically, an antenna is a combination of one or more conductors that can radiate an electromagnetic field due to an applied alternating voltage and associated alternating current, or it can be placed in an electromagnetic field, whereby an alternating current is induced within the antenna due to the field, resulting in an alternating voltage at its terminals. The bandwidth of an antenna refers to the frequency range in which it is effectively operated.

[0068] For example, Figure 1 is a schematic diagram of the architecture of a communication system provided in an embodiment of this application. The communication system shown in Figure 1 includes a first communication device and a second communication device. The first communication device and the second communication device can sense the target through sensing signals, or they can communicate wirelessly through communication signals. The first communication device or the second communication device can implement the acquisition of the angle of arrival (AoA) of the object to be measured based on the following method embodiments. The specific implementation process can be found in the following method embodiments, which will not be repeated here.

[0069] For example, based on angle-of-arrival (AOA) estimation technology, a communication device can perform multiple functions such as object finding, positioning, and reverse positioning. The object finding function determines the direction of the object relative to the communication device; the positioning function combines AOA estimation and ranging techniques to determine the specific location of the object relative to the communication device; and the reverse positioning function, given the known location information of multiple wireless signal transmitters, uses AOA estimation and ranging techniques to reversely determine the location information of the object.

[0070] In this embodiment, each communication device, such as the first and second communication devices, can be configured with multiple antennas. These multiple antennas may include multiple transmitting antennas for transmitting signals and multiple receiving antennas for receiving signals. Additionally, each communication device also includes a transmitter chain and a receiver chain. Those skilled in the art will understand that these may each include multiple components related to signal transmission and reception (e.g., processors, modulators, multiplexers, demodulators, demultiplexers, or antennas). Therefore, communication devices can communicate with each other using multi-antenna technology. Specifically, the communication device has an antenna array, and the multiple antennas in the antenna array can be used for sensing or communication. That is, the antenna array of the communication device has both sensing and communication functions.

[0071] In the embodiments of this application, the communication device with sensing and communication functions may be referred to as a sensing device, sensing apparatus, sensing communication device, sensing equipment, sensing communication device, etc., and there is no limitation thereto.

[0072] In a sensing scenario, a first communication device can send a sensing signal and receive an echo signal processed by a second communication device. Alternatively, the second communication device can send the sensing signal and receive an echo signal processed by the second communication device; this is not limited. The following method embodiment uses the example of a first communication device sending a sensing signal and receiving an echo signal. Specifically, the first communication device sends a sensing signal, which is then processed by the second communication device, and an echo signal is received. The first communication device measures the echo signal to obtain sensing information, which can characterize the attributes of the sensing target, such as the target's speed, distance, position, shape, and size, thereby achieving the sensing of the target. The following method embodiment can use a channel stitching algorithm with the first communication device to obtain a higher resolution distance, thereby improving the accuracy of the angle of arrival.

[0073] It should be understood that in the embodiments of this application, the antenna array of the communication device performing sensing selection forms multiple antenna clusters, each antenna cluster including multiple antennas, and the spacing between the multiple antenna clusters is arbitrary. That is, the spacing between the multiple antenna clusters is not limited to half a wavelength; for example, the spacing between the multiple antenna clusters can be greater than half a wavelength.

[0074] Furthermore, the communication system shown in Figure 1 can include both a wireless communication system and a wireless sensing system, enabling both wireless and wireless sensing functions. It is understood that communication signals and sensing signals are relative terms; for example, the communication signal is the physical downlink shared channel (PDSCH), while the sensing signal is used to sense the target (or target object).

[0075] In one example, the communication system may include a time-division wireless fidelity (WIFI) radar / communication sensing integrated system as shown in Figure 2. This time-division WIFI radar / communication sensing integrated system has the characteristics of WIFI radar and communication operating on the same frequency but at different times. Depending on the actual usage scenario, there may be situations where communication frames are continuously transmitted (i.e., the WIFI communication mode shown in Figure 2), radar frames are continuously transmitted (i.e., the WIFI radar mode shown in Figure 2), and the WIFI radar mode and WIFI communication mode have different or the same power.

[0076] In this embodiment, the communication device (such as a first communication device or a second communication device) can be a terminal device. The terminal device is a terminal that is connected to the aforementioned communication system and has wireless transceiver functionality, or a chip or chip system that can be installed in the terminal. The terminal device can also be referred to as a user device, access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user device. The terminal devices in the embodiments of this application can be mobile phones, tablets, computers with wireless transceiver capabilities, virtual reality (VR) terminal devices, augmented reality (AR) terminal devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical care, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, vehicle-mounted terminals, roadside units (RSUs) with terminal functions, etc. The terminal devices in this application can also be vehicle-mounted modules, vehicle-mounted components, vehicle-mounted chips, or vehicle-mounted units built into a vehicle as one or more components or units. The vehicle can implement the methods provided in this application through the built-in vehicle-mounted modules, vehicle-mounted components, vehicle-mounted chips, or vehicle-mounted units.

[0077] The embodiments of this application do not limit the form of the terminal device. The device used to implement the function of the terminal device can be the terminal device itself; it can also be a device that supports the terminal device in implementing the function, such as a chip system. The device can be installed in the terminal device or used in conjunction with the terminal device. In the embodiments of this application, the chip system can be composed of chips or can include chips and other discrete components.

[0078] In this embodiment, the sensing target can be a passive target, such as mountains, forests or buildings, or an active target, such as vehicles, drones, or terminal devices. The sensing scenario can include positioning, ranging, imaging, etc.

[0079] The embodiments of this application do not limit the number or type of communication devices included in the sensing communication system. For example, the communication system shown in Figure 1 may also include more sensing devices. Furthermore, integrating the wireless communication system and the wireless sensing system into a single design allows for simultaneous communication and environmental sensing. Such an integrated wireless communication and wireless sensing system is also called a sensing-communication integrated system. It should be understood that Figure 1 is merely a simplified schematic diagram for ease of understanding; the communication system may also include other network devices and / or other terminal devices, which are not shown in Figure 1.

[0080] It should be noted that the solutions in the embodiments of this application can also be applied to other communication systems, and the corresponding names can be replaced by the names of the corresponding functions in other communication systems.

[0081] Taking a mobile phone as an example, due to space constraints, it is difficult to meet the requirements of antenna radiation in the same direction and antenna array spacing. Designing and adding a dedicated antenna array in the same frequency band within the mobile phone would be difficult and costly.

[0082] Alternatively, taking a router as an example of a communication device, such as an optical network termination (OTN) all-in-one sensing router, the current antenna spacing is designed to be optimal for MIMO communication requirements, and the spacing is often greater than half a wavelength. Therefore, to achieve the angle measurement function, it is necessary to form an antenna array and add a switch to switch between sensing antennas and communication antennas, which often introduces additional insertion loss, thereby impairing communication performance.

[0083] In one possible implementation, a triangulation angle measurement algorithm is proposed to obtain the distance and phase of the sensing target, as shown in Figure 3. Figure 3(a) shows a schematic diagram of one triangulation angle measurement, and Figure 3(b) shows a schematic diagram of another triangulation angle measurement. The antenna system may include a first antenna and a second antenna. The distance between the first antenna and the second antenna is denoted by D, the distance between the first antenna and the sensing target is denoted by d1, and the distance between the second antenna and the sensing target is denoted by d2.

[0084] Specifically, Figure 3(a) shows a schematic diagram where the distance between the sensing target and the antenna system is greater than the distance between the first antenna and the second antenna, and Figure 3(b) shows a schematic diagram where the distance between the sensing target and the antenna system is less than the distance between the first antenna and the second antenna.

[0085] The distance between the sensed target and the antenna system is d. t Indicate, then

[0086] Let θ represent the target angle relative to the antenna system.

[0087] Due to limitations in distance accuracy, triangulation positioning angle measurement algorithms cannot obtain d1 and d2 with high resolution and accuracy, meaning they cannot obtain the target angle with high resolution and accuracy. Therefore, the application scenarios for triangulation positioning angle measurement algorithms are limited.

[0088] In another possible implementation, an antenna array angle measurement algorithm is proposed. This algorithm requires that the spacing between the antenna arrays in the antenna system be less than half a wavelength, such that D << d. t This means that the distance between the first and second antennas is much smaller than the target distance. Additionally, the antenna system needs to limit the phase difference angle of the target to between (-180°, +180°) so that the signal arrival angle θ is directly related to the signal phase difference Δφ.

[0089] Figure 4 shows a schematic diagram of an antenna array angle measurement. This antenna system can form a virtual array. Specifically, antennas S1 and S2 are shown in Figure 4, with a distance d between them. The forward-arriving signal first reaches antenna S1 and then antenna S2. The angle of arrival (θ) of the forward-arriving signal relative to the antenna system is denoted by θ, and the wavelength of the forward-arriving signal is denoted by λ.

[0090] Therefore, the forward-facing wave signal received by antenna S2 can be represented as: in,

[0091] When d = λ / 2

[0092] Where dsin θ represents the additional distance the forward-facing signal travels to antenna S2 compared to antenna S1, denoted as Δd. This distance is equal to the wavelength divided by the number of periods, where one period is 2π.

[0093] In other words, triangulation and antenna array angle measurement algorithms can be applied to scenarios where the antenna array spacing is less than half a wavelength. However, triangulation cannot solve the distance measurement accuracy problem, while antenna array angle measurement algorithms require restrictions on the antenna array spacing. Therefore, they cannot be quickly and directly used in existing antenna systems, which would increase costs or cause performance degradation if used in existing antenna systems. For example, in scenarios where the antenna array spacing is greater than half a wavelength, the phase exceeds 360°, leading to ambiguity, a phenomenon known as grating lobes, which reduces the accuracy of angle measurement.

[0094] Therefore, this application provides an angle-of-arrival estimation method. This method improves the distance resolution of the perceived target relative to the communication device by using channel stitching, resulting in a more accurate angle of arrival for the perceived target relative to the communication device. Furthermore, the positions of the multiple antennas in this method can be arbitrarily set, and there is no half-wavelength limitation on the spacing between the multiple antennas. This method can reuse existing multi-antenna systems, and is characterized by low implementation difficulty, low cost, and high stability.

[0095] The angle of arrival estimation method provided in the embodiments of this application will be further explained below with reference to the accompanying drawings.

[0096] This application provides an angle-of-arrival estimation method, which is applied to a communication device including multiple antennas. The communication device can be one described above, and will not be repeated here.

[0097] As shown in Figure 5, Figure 5 is a flowchart of an angle of arrival estimation method provided in an embodiment of this application. The angle of arrival estimation method includes the following process.

[0098] S501. The communication device sends sensing signals to the object under test through multiple antennas on N different frequency bands, where N is an integer greater than 1.

[0099] For example, N different frequency bands can also be understood as N channels. In the embodiments of this application, each antenna sends sensing signals to the object under test on N different channels, that is, the communication device can splice multiple channels to obtain a frequency-modulated continuous wave with a larger bandwidth.

[0100] For example, each antenna transmits the same number of channels, the same number of waveforms, and the same waveform length.

[0101] For example, sensing signals are also called detection signals, radar signals, radar sensing signals, radar detection signals, environmental sensing signals, etc. Sensing signals can be signals used to sense an object to be measured (or a target object). Alternatively, sensing signals can be signals used to sense or detect environmental information. For instance, a sensing signal can be an electromagnetic wave transmitted by a communication device through multiple antennas to sense environmental information.

[0102] The sensing signal in this application embodiment can be a radar signal, a pulse signal, such as a stepped frequency continuous waveform (SFCW) signal, a frequency modulated continuous waveform (FMCW) signal, a linear frequency modulated (LFM) signal, etc. It can also be a possible signal in a wireless communication system, such as a sounding reference signal (SRS), a demodulation reference signal (DMRS), a channel state information reference signal (CSI-RS), or an orthogonal frequency division multiplexing (OFDM) signal, etc.

[0103] For example, the object to be measured, also known as the sensing target, can include various tangible objects on the ground that can be sensed, such as mountains, forests, or buildings, and can also include movable objects such as vehicles and terminal devices. The sensing target is a target that a communication device with sensing capabilities can sense, and this target can feed back electromagnetic waves to the communication device. The sensing target can also be called the target to be detected, the object to be sensed, the object to be detected, or the device to be sensed, etc., and this application embodiment does not limit this terminology.

[0104] S502, the communication device receives N echo signals through multiple antennas respectively.

[0105] For example, the echo signal is the signal generated by the sensing signal through the action of the sensing target in the environment. The time delay of the echo signal relative to the transmitted sensing signal reflects the distance of the sensing target; the Doppler frequency shift of the echo signal relative to the transmitted sensing signal reflects the speed of the sensing target.

[0106] In this embodiment of the application, the signal of the sensing signal acting on the sensing target can also be referred to as the signal of the sensing signal reflected by the sensing target, the signal of the sensing signal refracted by the sensing target, the signal of the sensing signal diffracted by the sensing target, the signal of the sensing signal transmitted by the sensing target, the signal of the sensing signal scattered or diffracted by the sensing target, etc., and no specific limitation is made thereto.

[0107] S503, the communication device determines the echo signal matrix based on the N echo signals to obtain the N echo signal matrix.

[0108] For example, taking a direct data acquisition frequency modulation continuous wave waveform system that uses time-sequentially switched continuous channels as an example, the size of the echo signal matrix can be: channel * fast time sampling * slow time sampling * antenna channel.

[0109] For example, fast time sampling involves sampling the echo signal at a high frequency over a short period of time. The main purpose of fast time sampling is to obtain high-resolution range information. Slow time sampling, on the other hand, involves a longer time scale, typically referring to sampling the radar signal over multiple pulse repetition intervals. The main purpose of slow time sampling is to obtain Doppler information and other long-term characteristics, such as the velocity and trajectory of the object being measured.

[0110] The elements in the echo signal matrix can be IQ samples or real numbers. When the elements in the echo signal matrix are real numbers, positive and negative information about the angle and velocity of the object being measured will be lost, but it still has practical value in some scenarios.

[0111] Taking the elements in the echo signal matrix as IQ samples as an example, assuming the number of antenna channels is 1 and the number of channels is 3, as shown in Figure 6, Figure 6 shows a schematic diagram of an echo signal matrix. Figure 6 specifically shows the fast and slow time matrices of channel 1, channel 2, and channel 3. Taking the fast and slow time matrix of channel 1 as an example, the row directions of the fast and slow time matrix of channel 1 represent slow time samples, and the column directions represent fast time samples.

[0112] Due to the different bandwidths and frequencies of each channel, the echo signal matrix on the same slow-time sampling is shown in Figure 7(a). Furthermore, the waveform of the echo signal matrix on the same slow-time sampling is shown in Figure 7(b). Figure 7 specifically shows the waveforms of the sensing signals and echo signals of the three channels, namely channel 1, channel 2, and channel 3. The channels 1, 2, and 3 are continuous, meaning the end bandwidth of the previous channel overlaps with the start bandwidth of the next channel. Moreover, the communication device maintains continuous phase without abrupt changes during signal switching.

[0113] The time difference Δt between the sensing signal and the echo signal of each channel represents the signal transmission time. Therefore, the distance between the object under test and the communication device can be: Δt*c / 2, where c is the speed of light.

[0114] The equivalent diagram of the channel splicing shown in Figure 7(b) is shown in Figure 8, which illustrates another type of channel splicing. In this diagram, the total signal bandwidth of the communication device is the sum of the bandwidths of channel 1, channel 2, and channel 3. As can be seen from Figure 8, the communication device achieves a larger bandwidth frequency-modulated continuous wave.

[0115] It is understood that the channel splicing algorithm provided in this application embodiment can also be other schemes. For example, the communication device can switch continuous channels out of order in time, or the communication device can receive part of the echo signal at the same time, or the communication device can receive all the echo signal at the same time. This application embodiment does not limit this.

[0116] S504. The communication device determines the angle of arrival of the object under test relative to the communication device based on the N echo signal matrices.

[0117] For example, the communication device determines the distance of the object to be measured relative to the communication device based on N echo signal matrices. Since the communication device uses a channel stitching algorithm, the distance determined by the communication device has high resolution. Therefore, the communication device can further apply a triangulation angle measurement algorithm based on this high-resolution distance to obtain the angle of arrival of the object to be measured relative to the communication device.

[0118] Furthermore, the positions of multiple antennas in this angle of arrival estimation method can be arbitrarily set, and there is no half-wavelength distance limitation on the distance between the multiple antennas. Therefore, this angle of arrival estimation algorithm can reuse existing multi-antenna systems, offering low implementation difficulty, low cost, and high stability.

[0119] Optionally, S503 may include: the communication device arranging the N echo signals in ascending order according to the frequencies of the corresponding frequency bands to obtain an echo signal matrix.

[0120] For example, by arranging N echo signals in order of arrival from the smallest frequency in the corresponding frequency band, a frequency-modulated continuous wave with a larger bandwidth can be achieved. This can improve the distance resolution of the object under test relative to the communication device and obtain a more accurate angle of arrival of the object under test relative to the communication device.

[0121] For example, the communication device may also arrange the N echo signals in descending order of their corresponding frequency bands to obtain an echo signal matrix. Alternatively, the communication device may arrange the N echo signals in other orders, and this application embodiment does not limit this.

[0122] Optionally, prior to S504, the angle of arrival estimation method may include: the communication device filtering the N echo signal matrices respectively to obtain the filtered N echo signal matrices.

[0123] For example, the primary purpose of filtering the echo signal matrix by a communication device is to remove noise to improve signal quality and extract useful feature information. For instance, the communication device can remove information about the environment in which the object under test exists from the echo signal matrix.

[0124] For example, a communication device can use low-pass filtering to filter the echo signal matrix, i.e., suppressing high-frequency noise and retaining low-frequency components. A communication device can also use high-pass filtering to filter the echo signal matrix, i.e., suppressing low-frequency noise and retaining high-frequency components. A communication device can also use band-pass filtering to filter the echo signal matrix, i.e., allowing signals within a specific frequency range to pass through, such as retaining only the target echo signal while excluding other cluttered signals. It is understood that a communication device can use one filtering method or a combination of multiple filtering methods to filter the echo signal matrix, and the embodiments of this application do not limit this.

[0125] Optionally, in scenarios involving a single object under test, S504 may include: the communication device performing maximum likelihood estimation (MLE) processing on N echo signal matrices based on a preset echo signal matrix to obtain multiple distances of the object under test relative to multiple antennas, wherein the preset echo signal matrix includes the correspondence between distances and echo signals. The communication device determines the phase of the object under test relative to the multiple antennas based on the multiple distances, and determines the angle of arrival of the object under test relative to the communication device based on the phase of the multiple antennas.

[0126] For example, in various scenarios, multiple channels are not continuous, and the communication device experiences phase discontinuity or abrupt changes during signal switching (e.g., due to phase-locked loop (PLL) reset). A schematic diagram of channel splicing in this situation is shown in Figure 9. Specifically, Figure 9 uses splicing a 2.4GHz band with a 5.6GHz band as an example. The area between the 2.4GHz and 5.6GHz bands is an unlicensed band, meaning the channels cannot be continuous. In this case, the actual channel response differs at different times, i.e., the ideal echo waveform differs from the measured echo waveform. Therefore, the waveforms of multiple channels cannot be simply equated to a larger bandwidth FMCW waveform.

[0127] Therefore, the communication device can perform maximum likelihood estimation on N echo signal matrices based on a preset echo signal matrix to calculate the distance Doppler spectrum. Specifically, when the received echo signal includes frequency shift information, such as frequency changes caused by the movement of the object under test (i.e., Doppler frequency shift), this frequency shift can be estimated based on the Doppler spectrum.

[0128] Specifically, when processing Doppler spectra, the basic idea of ​​maximum likelihood estimation is to assume a probability distribution model for the echo signal, usually a certain probability density function, such as a Gaussian distribution or a Rayleigh distribution, and then calculate the maximum probability value of the model parameters (e.g., Doppler frequency shift) under a preset echo signal matrix. This involves maximizing the probability that the data sample falls into this probability distribution, thus using it as the parameter estimate closest to the real situation. Specific steps may include: (1) Establishing a mathematical model: Assuming that the echo signal follows a certain known distribution and determining the influence of Doppler frequency shift on signal characteristics. (2) Calculating the likelihood function: Based on the observed data, constructing a likelihood function about the Doppler frequency shift, representing the probability that the data appears in the simulation. (3) Finding the maximum likelihood solution: By taking the derivative and setting the derivative to zero, finding the Doppler frequency shift value that maximizes the likelihood function, which is the maximum likelihood estimation result. Understandably, maximum likelihood estimation can also be iterated multiple times using numerical methods until the global optimal solution is found.

[0129] Therefore, the communication device can obtain a high-resolution and accurate distance between the object under test and the communication device through this channel splicing algorithm. Next, the communication device can calculate the angle of arrival of the object under test relative to the communication device according to the triangulation angle measurement algorithm. The triangulation algorithm can be referred to the relevant description in Figure 3, which will not be repeated here.

[0130] Optionally, before determining the angle of arrival of the object under test relative to the communication device based on the phases of the multiple antennas, the angle of arrival estimation method further includes: if the difference in distance between two of the multiple antennas is greater than a first preset threshold, performing phase compensation on two of the multiple antennas to determine the phase of the object under test relative to two of the multiple antennas.

[0131] For example, the first preset threshold can be set by those skilled in the art based on the ranging accuracy and angle measurement accuracy, and the embodiments of this application do not limit this.

[0132] If the distance between two of the multiple antennas is greater than a preset threshold, indicating that the phase of the communication device exceeds 360°, a grating lobe phenomenon will occur. Therefore, the angle of arrival estimation method provided in this application can perform phase compensation to improve ranging accuracy and angle measurement accuracy.

[0133] For example, if the distance between two of the multiple antennas is less than or equal to a first preset threshold, it can be characterized that the phase of the communication device does not exceed 360 degrees, and the communication device does not need to perform phase compensation.

[0134] In a scenario involving a single object under test, as shown in Figure 10, which is a flowchart of another angle-of-arrival estimation method provided by an embodiment of this application, Figure 10 illustrates an example using a first antenna and a second antenna. This angle-of-arrival estimation method may include the following steps.

[0135] Specifically, on the first antenna side:

[0136] S1001. Send the first sensing signal to the object under test on N different frequency bands;

[0137] S1002, Receive N first echo signals;

[0138] S1003. Determine the first echo signal matrix based on the N first echo signals;

[0139] S1004. Filter the first echo signal matrix;

[0140] S1005. Perform maximum likelihood estimation on the first echo signal matrix based on the preset echo signal matrix;

[0141] S1006, Target Selection;

[0142] S1007. Select the low-frequency channel phase;

[0143] Specifically, on the second antenna side:

[0144] S1008. Send a second sensing signal to the object under test on N different frequency bands;

[0145] S1009, Receive N second echo signals;

[0146] S1010. Determine the second echo signal matrix based on the N first echo signals;

[0147] S1011. Filter the second echo signal matrix;

[0148] S1012. Perform maximum likelihood estimation on the second echo signal matrix based on the preset echo signal matrix;

[0149] S1013. Select the target;

[0150] S1014. Select the low-frequency channel phase;

[0151] On the communication device side:

[0152] S1015. Determine whether the distance difference is greater than a preset threshold. If the distance difference is greater than the first preset threshold, then execute S1016; if the distance difference is less than or equal to the first preset threshold, then execute S1017.

[0153] S1016, Phase compensation;

[0154] S1017, Angle estimation.

[0155] Optionally, in a scenario involving multiple objects to be measured, S504 may include: the communication device determining a multi-antenna echo signal matrix based on N echo signal matrices. The communication device performs maximum likelihood estimation processing on the multi-antenna echo signal matrix based on a preset multi-antenna echo signal matrix to obtain the distance and angle of arrival of the object to be measured relative to the communication device. The preset multi-antenna echo signal matrix includes the correspondence between multiple distances and multiple echo signals.

[0156] For example, as shown in FIG11, FIG11 is a flowchart of another angle of arrival estimation method provided by an embodiment of the present application, wherein a first antenna and a second antenna are used as examples for illustration. The angle of arrival estimation method may include the following process.

[0157] Specifically, on the first antenna side:

[0158] S1101. Send the first sensing signal to the object under test on N different frequency bands;

[0159] S1102, Receive N first echo signals;

[0160] S1103. Determine the first echo signal matrix based on the N first echo signals;

[0161] S1104. Filter the first echo signal matrix;

[0162] Specifically, on the second antenna side:

[0163] S1105. Send a second sensing signal to the object under test on N different frequency bands;

[0164] S1106, Receive N second echo signals;

[0165] S1107. Determine the second echo signal matrix based on N first echo signals;

[0166] S1108. Filter the second echo signal matrix;

[0167] On the communication device side:

[0168] S1109. Determine the multi-antenna echo signal matrix based on the first echo signal matrix and the second echo signal matrix;

[0169] S1110. Perform maximum likelihood estimation on the multi-antenna echo signal matrix based on the preset multi-antenna echo signal matrix.

[0170] S1111, Target Recognition.

[0171] Optionally, in a scenario including at least one object to be measured, S504 may include: the communication device determining a multi-antenna echo signal matrix based on N echo signal matrices, and inputting the multi-antenna echo signal matrix into an artificial intelligence model to obtain the distance and angle of arrival of the object to be measured relative to the communication device.

[0172] As exemplarily shown in Figure 12, which is a flowchart of another angle-of-arrival estimation method provided in an embodiment of this application, Figure 12 illustrates the method using a first antenna and a second antenna as examples. The angle-of-arrival estimation method may include the following steps.

[0173] Specifically, on the first antenna side:

[0174] S1201. Send the first sensing signal to the object under test on N different frequency bands;

[0175] S1202, Receive N first echo signals;

[0176] S1203. Determine the first echo signal matrix based on N first echo signals;

[0177] S1204. Filter the first echo signal matrix;

[0178] Specifically, on the second antenna side:

[0179] S1205. Send a second sensing signal to the object under test on N different frequency bands;

[0180] S1206, Receive N second echo signals;

[0181] S1207. Determine the second echo signal matrix based on N first echo signals;

[0182] S1208. Filter the second echo signal matrix;

[0183] On the communication device side:

[0184] S1209. Determine the multi-antenna echo signal matrix based on the first echo signal matrix and the second echo signal matrix;

[0185] S1210. Input the multi-antenna echo signal matrix into the AI ​​model;

[0186] S1211, Target Recognition.

[0187] Optionally, the multiple antennas include a first antenna and a second antenna, and the distance between the first antenna and the second antenna is greater than a second preset threshold.

[0188] For example, the second preset threshold can be half a wavelength. Compared to the antenna array angle measurement scheme, which requires the distance between the first and second antennas to be less than half a wavelength, the distance between the first and second antennas in the communication device provided in this application embodiment can be greater than half a wavelength. Therefore, the angle of arrival estimation method provided in this application embodiment can reuse existing multi-antenna systems, and is easy to implement, low in cost, and highly stable.

[0189] For example, when the distance between the first and second antennas in the communication device is less than or equal to half a wavelength, the communication device can select the frequency band corresponding to half a wavelength for angle estimation, and then select a suitable frequency band for distance estimation. When the distance between the first and second antennas in the communication device is greater than half a wavelength, the communication device can use a channel stitching algorithm to obtain a high-resolution distance, and then use a triangulation angle measurement algorithm for angle estimation.

[0190] In some embodiments, the communication device provided in this application can also be applied to an OTN router, as shown in FIG13. FIG13(a) shows a schematic diagram of an OTN router, and FIG13(b) shows a schematic diagram of another OTN router.

[0191] An OTN router can include one transmitter (TX) antenna and two receiver (RX) antennas, such as RX antenna_1 and RX antenna_2. OTN routers generally use 2.4G / 5G dual-band multi-antenna designs. The spacing between the antennas in the antenna array system of an OTN router varies depending on the design positioning and appearance.

[0192] In Figure 13(a), the distance between RX antenna_1 and RX antenna_2 is less than or equal to 6 centimeters (cm), which achieves a half wavelength of 2.4 gigahertz (GHz), thus allowing direct angle measurement at 2.4 GHz.

[0193] In Figure 13(b), when the distance between RX antenna_1 and RX antenna_2 is greater than 6cm, 2.4GHz and 5GHz can be used for channel splicing until the resolution reaches 6cm. The corresponding distances are measured on RX antenna_1 and RX antenna_2 respectively, and the angle is measured in combination with the phase.

[0194] In some embodiments, the angle-of-arrival estimation method provided in this application can also be applied to mobile phones, as shown in Figure 14, which illustrates a schematic diagram of an antenna system in a mobile phone. Mobile phones typically use at least two 2.4G / 5G antennas to form a Wi-Fi MIMO, such as 2.4G / 5G antenna_1 and 2.4G / 5G antenna_2. 2.4G / 5G antenna_1 can be positioned at one end of the phone's screen, and 2.4G / 5G antenna_2 can be positioned at the other end of the screen. Since the length of a mobile phone screen is generally greater than 6cm, meaning the antenna array spacing is greater than 6cm, a channel stitching scheme can be used to provide sufficient distance resolution, and angle estimation can be performed using a triangulation method.

[0195] It is understood that, in order to achieve the above functions, the electronic device includes hardware and / or software modules that perform the respective functions. Based on the algorithmic steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is implemented in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in conjunction with the embodiments, but such implementation should not be considered beyond the scope of this application.

[0196] This embodiment can divide the electronic device into functional modules according to the above method example. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0197] With each functional module divided according to its corresponding function, Figure 15 shows a possible compositional schematic diagram of the communication device 1500 involved in the above embodiment. As shown in Figure 15, the communication device 1500 may include: a processing module 1501, multiple transmitting antennas 1502 and multiple receiving antennas 1503.

[0198] The processing module 1501 can be used to support the communication device 1500 in performing the above-described steps S503 and S504, and / or other processes used in the technology described herein.

[0199] The transmitting antenna 1502 can be used to support the communication device 1500 in performing the above-described steps S501, and / or other processes for the technology described herein.

[0200] The receiving antenna 1503 can be used to support the communication device 1500 in performing the above-described steps S502, etc., and / or other processes for the techniques described herein.

[0201] It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0202] The communication device 1500 provided in this embodiment is used to execute the above-described angle of arrival estimation method, and thus can achieve the same effect as the above-described implementation method.

[0203] When using an integrated unit, the communication device 1500 may include a processing module, a storage module, and a communication module. The processing module can be used to control and manage the operation of the communication device 1500; for example, it can support the communication device 1500 in executing the steps performed by the processing module 1501, the multiple transmitting antennas 1502, and the multiple receiving antennas 1503. The storage module can be used to support the communication device 1500 in storing program code and data. The communication module can be used to support communication between the communication device 1500 and other devices, such as communication with a wireless access device.

[0204] The processing module can be a processor or a controller. It can implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module can be a memory. The communication module can specifically be a radio frequency circuit, a Bluetooth chip, a Wi-Fi chip, or other devices that interact with other electronic devices.

[0205] This application also provides an electronic device, including one or more processors and one or more memories. The one or more memories are coupled to the one or more processors, and the one or more memories are used to store computer program code, including computer instructions. When the one or more processors execute the computer instructions, the electronic device performs the aforementioned method steps to implement the angle-of-arrival estimation method in the above embodiments.

[0206] Embodiments of this application also provide a computer storage medium storing computer instructions. When the computer instructions are executed on an electronic device, the electronic device performs the aforementioned method steps to implement the angle of arrival estimation method in the above embodiments.

[0207] Embodiments of this application also provide a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to implement the angle of arrival estimation method executed by the electronic device in the above embodiments.

[0208] In addition, embodiments of this application also provide an apparatus, which may specifically be a chip, component, or module. The apparatus may include a connected processor and a memory. The memory is used to store computer execution instructions. When the apparatus is running, the processor can execute the computer execution instructions stored in the memory to cause the chip to execute the angle of arrival estimation method executed by the electronic device in the above-described method embodiments.

[0209] In this embodiment, the electronic device, computer storage medium, computer program product or chip are all used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the corresponding method provided above, and will not be repeated here.

[0210] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0211] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0212] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0213] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0214] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially or in other words, the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0215] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for estimating angle of arrival, characterized in that, The method is applied to a communication device, the communication device including multiple antennas, and the method includes: The multiple antennas transmit sensing signals to the object under test on N different frequency bands, where N is an integer greater than 1. N echo signals are received through the multiple antennas respectively; The echo signal matrix is ​​determined based on the N echo signals to obtain N echo signal matrices; The angle of arrival of the object under test relative to the communication device is determined based on the N echo signal matrices.

2. The method according to claim 1, characterized in that, The step of determining the echo signal matrix based on the N echo signals to obtain N echo signal matrices includes: The N echo signals are arranged in ascending order of frequency according to their corresponding frequency bands to obtain an echo signal matrix.

3. The method according to claim 1 or 2, characterized in that, Determining the angle of arrival of the object under test relative to the communication device based on the N echo signal matrices includes: The maximum likelihood estimation process is performed on the N echo signal matrices according to the preset echo signal matrix to obtain multiple distances of the object under test relative to the multiple antennas. The preset echo signal matrix includes the correspondence between distance and echo signal. Based on the multiple distances, the phase of the object under test relative to the multiple antennas is determined; The angle of arrival of the object under test relative to the communication device is determined based on the phase of the plurality of antennas.

4. The method according to claim 3, characterized in that, Before determining the angle of arrival of the object under test relative to the communication device based on the phases of the plurality of antennas, the method further includes: If the difference in distance between two of the plurality of antennas is greater than a first preset threshold, phase compensation is performed on two of the plurality of antennas to determine the phase of the object under test relative to two of the plurality of antennas.

5. The method according to claim 1 or 2, characterized in that, Determining the angle of arrival of the object under test relative to the communication device based on the N echo signal matrices includes: Based on the N echo signal matrices, determine the multi-antenna echo signal matrix; The maximum likelihood estimation process is performed on the multi-antenna echo signal matrix based on the preset multi-antenna echo signal matrix to obtain the distance and angle of arrival of the object under test relative to the communication device. The preset multi-antenna echo signal matrix includes the correspondence between multiple distances and multiple echo signals.

6. The method according to claim 1 or 2, characterized in that, Determining the angle of arrival of the object under test relative to the communication device based on the N echo signal matrices includes: Based on the N echo signal matrices, determine the multi-antenna echo signal matrix; The multi-antenna echo signal matrix is ​​input into an artificial intelligence (AI) model to obtain the distance and angle of arrival of the object under test relative to the communication device.

7. The method according to any one of claims 1-6, characterized in that, Before determining the angle of arrival of the object under test relative to the communication device based on the N echo signal matrices, the method further includes: The N echo signal matrices are filtered respectively to obtain the filtered N echo signal matrices.

8. The method according to any one of claims 1-7, characterized in that, The plurality of antennas includes a first antenna and a second antenna, wherein the distance between the first antenna and the second antenna is greater than a second preset threshold.

9. A communication device, characterized in that, The communication device includes: a processing module, multiple transmitting antennas, and multiple receiving antennas; The plurality of transmitting antennas are used to send sensing signals to the object under test on N different frequency bands, where N is an integer greater than 1; The plurality of receiving antennas are used to receive N echo signals respectively; The processing module is used to determine the echo signal matrix based on the N echo signals respectively, so as to obtain N echo signal matrices; The processing module is also used to determine the angle of arrival of the object under test relative to the communication device based on the N echo signal matrices.

10. A computer-readable storage medium, characterized in that, Includes computer instructions that, when executed on an electronic device, cause the electronic device to perform the method described in any one of claims 1-8.

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