Beam processing method for antenna array, antenna module and multi-fold satellite

Abstract

Provided are a beam processing method for an antenna array, an antenna module, and a multi-fold satellite. The beam processing method comprises: dividing the antenna array into a plurality of first-level subarrays, calculating a first output vector for each first-level subarray, and constructing a first-level subarray beam weighting matrix according to the first output vectors; merging the plurality of first-level subarrays into a plurality of second-level subarrays, calculating a second output vector for each second-level subarray according to the first output vectors, and calculating a second-level subarray synthesis matrix according to the second output vectors and the first-level subarray beam weighting matrix; and merging the plurality of second-level subarrays into a third-level full array, and calculating a third output vector for the third-level full array according to the second-level subarray synthesis matrix and a third-level full array synthesis matrix. The present disclosure can improve the beam calculation accuracy of the antenna array.

Description

Technical Field

[0001] This disclosure relates to the field of communications, and specifically to a beam processing method for an antenna array, an antenna module, a multi-fold satellite, a computing device, a non-transient computer-readable storage medium, and a chip system. Background Technology

[0002] To meet the future all-weather, all-time, and all-region communication needs, direct satellite connection technology for devices (such as mobile phones) has emerged, enabling mobile phone users to efficiently and seamlessly access satellite communication networks. To overcome the limitations of mobile phone transmission power and receiving sensitivity, as well as the significant losses in satellite-to-ground links, direct satellite connection technology requires satellite antennas to have extremely high gain. In turn, extremely high antenna gain requires satellite antennas to have a very large aperture and extremely narrow beam pointing accuracy.

[0003] During the satellite launch phase, the satellite antenna must remain folded due to the size limitations of the rocket fairing. After the satellite is launched into orbit, the antenna will unfold in orbit, forming a large-scale antenna array. However, for large-scale antenna arrays, there is currently a lack of effective methods to calculate accurate beam signals, resulting in insufficient beam calculation accuracy. Summary of the Invention

[0004] Providing a mechanism to alleviate, reduce or eliminate at least one of the above problems would be beneficial.

[0005] In a first aspect, a beamforming method for an antenna array is provided. The method includes: dividing the antenna array into multiple first-level subarrays; calculating a first output vector for each first-level subarray; constructing a first-level subarray beamweighting matrix based on the first output vector; merging the multiple first-level subarrays into multiple second-level subarrays; calculating a second output vector for each second-level subarray based on the first output vector; calculating a second-level subarray composite matrix based on the second output vector and the first-level subarray beamweighting matrix; merging the multiple second-level subarrays into a third-level full array; and calculating a third output vector for the third-level full array based on the second-level subarray composite matrix and the third-level full array composite matrix.

[0006] In a second aspect, an antenna module is provided. The antenna module includes: antenna modules and a DBF processor; multiple antenna modules form an antenna array; and the DBF processor is used to execute the aforementioned beam processing method for the antenna array.

[0007] In a third aspect, a multi-fold satellite is provided. This multi-fold satellite includes: a main body comprising multiple cabin modules and a folding mechanism connected to each cabin module, the folding mechanism driving the cabin modules to rotate, thereby causing the main body to be in a stacked, folded state or a flat, unfolded state; each cabin module includes an antenna module and a DBF processor; and solar panels connected to the cabin modules; wherein, when the main body is in a flat, unfolded state: the multiple antenna modules form an antenna array; and at least one DBF processor is used to execute the aforementioned beam processing method for the antenna array.

[0008] In a fourth aspect, a computing device is provided. The computing device includes: at least one processor; and at least one memory storing instructions that, when executed individually or jointly by the at least one processor, cause the computing device to perform the aforementioned antenna array beam processing method.

[0009] In a fifth aspect, a non-transitory computer-readable storage medium is provided that stores machine-executable instructions, which, when executed individually or jointly by one or more processors of a machine, cause the machine to perform the aforementioned beamforming method for an antenna array.

[0010] In a sixth aspect, a chip system is provided. This chip system includes a circuit system configured to perform the beam processing method for the antenna array described above.

[0011] It should be understood that the summary section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0012] The above and other objects, features, and advantages of this disclosure will become more apparent from the more detailed description of some embodiments thereof in the accompanying drawings, in which:

[0013] Figure 1 A flowchart illustrating a beam processing method for an antenna array according to an embodiment of the present disclosure is shown;

[0014] Figure 2 A schematic diagram of a multi-fold satellite facing the ground is shown according to some embodiments of the present disclosure;

[0015] Figure 3 A schematic diagram of a multi-fold satellite facing the sky surface according to some embodiments of the present disclosure is shown;

[0016] Figure 4 A schematic diagram of multi-level DBF processing according to some embodiments of the present disclosure is shown;

[0017] Figure 5 A schematic diagram of a multi-fold satellite facing the ground according to other embodiments of the present disclosure is shown; and

[0018] Figure 6 A simplified block diagram of a device suitable for implementing exemplary embodiments of the present disclosure is shown.

[0019] Explanation of reference numerals in the accompanying drawings for specific embodiments:

[0020] 10. Satellite;

[0021] 11. Main body;

[0022] 12. Cabin module;

[0023] 13. Antenna module;

[0024] 14. Antenna array;

[0025] 141. First-level subarray;

[0026] 142. Second-level subarray;

[0027] 143. Level 3 Full Formation;

[0028] 15. DBF processor;

[0029] 16. Infrared horizon instrument;

[0030] 17. Optical module;

[0031] 18. Solar panel;

[0032] 19. Heat pipe. Detailed Implementation

[0033] The principles of this disclosure will now be described with reference to some embodiments. It should be understood that these embodiments are described for illustrative purposes only and to assist those skilled in the art in understanding and implementing this disclosure, and do not impose any limitation on the scope of this disclosure. The disclosure described herein may be implemented in ways other than those described below.

[0034] In the following description and claims, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0035] References to "an embodiment," "embodiment," "exemplary embodiment," etc., in this disclosure indicate that the described embodiments may include specific features, structures, or characteristics, but not every embodiment needs to include specific features, structures, or characteristics. Furthermore, such phrases do not necessarily refer to the same embodiment. Moreover, when a specific feature, structure, or characteristic is described in connection with an exemplary embodiment, whether explicitly described or not, those skilled in the art will recognize that such a feature, structure, or characteristic affects its connection to other embodiments.

[0036] It should be understood that while the terms “first” and “second”, etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of the exemplary embodiments, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element. The term “and / or” as used herein includes any and all combinations of one or more of the listed terms.

[0037] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. The singular forms “a,” “an,” and “the” used herein also include the plural forms unless the context clearly indicates otherwise. The terms “a group of elements” or “a collection of elements” as used herein are intended to include one or more elements. It should also be understood that the terms “comprising,” “including,” “having,” “possessing,” “including,” and / or “comprising,” when used herein, specify the presence of the stated features, elements, and / or components, but do not exclude the presence or addition of one or more other features, elements, components, and / or combinations thereof.

[0038] As used in this disclosure, the term "circuit" may refer to one or more of the following:

[0039] (a) Implemented only in hardware circuitry (e.g., implemented only in analog and / or digital circuitry)

[0040] (b) A combination of hardware circuitry and software, such as (if applicable):

[0041] (i) a combination of analog and / or digital hardware circuitry with software / firmware; and

[0042] (ii) Any part of a hardware processor (including a digital signal processor), software, and memory that work together to enable a device such as a mobile phone or server to perform various functions, and

[0043] (c) Hardware circuitry and / or processors, such as microprocessors or a portion thereof, which require software (e.g., firmware) to operate, but may be absent when the software is not required to operate.

[0044] The definition of "circuit" applies to all uses of the term in this disclosure, including in any claim. As another example, as used in this disclosure, the term "circuit" also includes implementations of hardware circuitry or a processor (or processors) or a portion thereof and its accompanying software and / or firmware. The term "circuit" also includes, for example, a baseband integrated circuit or processor integrated circuit for a mobile device, or a similar integrated circuit in a server, cellular network device, or other computing network device, if applicable to a particular claim element.

[0045] As used herein, the term "communication network" refers to a network that conforms to any suitable communication standard, such as Long Term Evolution (LTE), LTE-Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), Narrowband Internet of Things (NB-IoT), New Radio (NR), Non-Terrestrial Network (NTN), etc. Furthermore, communication between terminal devices and network devices in a communication network can be performed according to any suitable generation of communication protocol, including but not limited to first-generation (1G), second-generation (2G), 2.5G, 2.75G, third-generation (3G), fourth-generation (4G), 4.5G, fifth-generation (5G), and future sixth-generation (6G) communication protocols, and / or any other protocols currently known or to be developed in the future. Embodiments of this disclosure can be applied to satellite communication systems. Given the rapid development in communications, future types of communication technologies and systems will naturally exist, and this disclosure can be implemented using these technologies and systems. The scope of this disclosure should not be considered limited to the aforementioned systems.

[0046] As used herein, the term "satellite network device" refers to a node located on a satellite or ground segment within a satellite communication network. Terminal devices access the network and receive services through this node. Depending on the terminology and technology applied, a satellite network device can refer to a base station (BS) or access point (AP) that serves as a satellite payload, such as a Node B (NodeB or NB), an evolved Node B (eNodeB or eNB), an NR NB (also known as a gNB), a Remote Radio Unit (RRU), a Radio Header (RH), a Remote Radio Header (RRH), or a relay node. An example of a relay node can be an Integrated Access and Backhaul (IAB) node. The Distributed Unit (DU) portion of an IAB node can perform the functions of a "satellite network device" and therefore can operate as a network device. In the following description, the terms "satellite network device," "BS," and "node" are used interchangeably.

[0047] The term "terminal device" refers to any terminal device capable of wireless communication. As an example and not a limitation, a terminal device may also be referred to as a communication device, user equipment (UE), subscriber station (SS), portable subscriber station, mobile station (MS), or access terminal (AT). This terminal device may include, but is not limited to, mobile phones, cellular phones, smartphones, Voice over IP (VoIP) phones, wireless local loop phones, tablets, wearable terminal devices, personal digital assistants (PDAs), portable computers, desktop computers, image capture terminal devices such as digital cameras, gaming terminal devices, music storage and playback devices, in-vehicle wireless terminal devices, wireless endpoints, mobile stations, laptop embedded devices (LEEs), laptop installed devices (LMEs), USB dongles, smart devices, wireless subscriber equipment (CPEs), Internet of Things (IoT) devices, watches or other wearable devices, head-mounted displays (HMDs), vehicles, drones, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in the context of industrial and / or automated processing chains), consumer electronics devices, relay nodes, devices operating on commercial and / or industrial wireless networks, etc. The mobile terminal (MT) portion of an IAB node can perform the functions of a "terminal device" and therefore can operate as a terminal device. In the following description, the terms "terminal device," "communication device," "terminal," "user equipment," and "UE" are used interchangeably.

[0048] While the functions described herein may be implemented in fixed and / or wireless network nodes in various exemplary embodiments, in other exemplary embodiments, they may be implemented in user equipment devices (such as cellular phones, tablet computers, laptop computers, desktop computers, mobile IoT devices, or fixed IoT devices). For example, the user equipment device may suitably have the corresponding capabilities described in relation to fixed and / or wireless network nodes. The user equipment device may be user equipment and / or control devices, such as chipsets or processors, configured to control the user equipment when it is installed therein. Examples of these functions include boot server functions and / or home subscriber servers, which may be implemented in the user equipment device by providing the user equipment device with software configured to cause the user equipment device to perform from the perspective of these functions / nodes.

[0049] The following section introduces the technical details of the satellite antenna and the inventive concept of this disclosure. Exemplarily, the satellite antenna or antenna module mentioned in this disclosure can be a phased array antenna. The technical means of this disclosure will be described using a phased array antenna as an example. The antenna module can be installed on a satellite or on the ground. In practical applications, the satellite antenna or antenna module can also be other types of antennas, and this disclosure does not impose any limitations.

[0050] With the rapid development of low-Earth orbit communication satellite networks, digital phased array antennas have been widely used due to their comprehensive advantages in multi-beamforming, beamforming, fast scanning, spatial filtering, anti-interference, and system reliability. Phased array antennas can serve as the basis for the most important ultra-large-scale antenna form and multi-beamforming method for direct satellite connection to mobile phones.

[0051] During satellite launch, phased array antennas need to be kept folded to meet the size constraints of the rocket fairing, so that they can be mounted in the limited space of the rocket. This makes the technology of ultra-large-scale foldable phased array antennas crucial.

[0052] Currently, the mainstream deployment method for phased array antennas is array folding deployment, rather than satellite folding deployment. The size of the deployed phased array antenna and the number of folds are related to actual application requirements. Potential problems with the current array deployment method include: First, it cannot guarantee the planar accuracy requirements of the deployed antenna array on satellite in orbit, typically requiring one-tenth or even one-twentieth of a wavelength, posing a risk of deterioration in pointing accuracy due to changes in beamforming parameters. Second, it cannot guarantee high-speed, cableless data transmission between deployed antenna arrays, posing a risk due to fiber optic cable bending.

[0053] This disclosure identifies the following main drawbacks of phased array antennas with foldable and deployable array surfaces:

[0054] (1) The planar accuracy of the antenna array cannot be measured and corrected after it is deployed on track.

[0055] To meet the link margin requirements for direct satellite connections between mobile phones and satellites, phased array antennas often need to have an aperture area of ​​10m². 2 (square meters) or more, while satellites are resource-constrained systems; typically, low-Earth orbit communication satellites only have a usable area of ​​3-4 square meters on the ground. 2 Left and right, therefore, to satisfy 10m 2 The above-mentioned ultra-large-scale antenna arrays require the antenna array surface to be folded and unfolded.

[0056] Meanwhile, ultra-large-scale antenna arrays inevitably form extremely narrow, high-gain beams, placing high demands on beam pointing accuracy. After the satellite is launched into orbit and the antenna is deployed, firstly, due to the lack of a rigid support structure, there will be vibrations at a certain frequency, which may cause some disturbance to the satellite's attitude control system. Secondly, after the antenna is deployed, there are no conditions for measuring and correcting its flatness, which may have some impact on beamforming and pointing accuracy.

[0057] (2) Problem of bending of transmission cable before and after antenna array deployment.

[0058] For the design of ultra-large-scale phased array antennas, it is necessary to rationally divide the phased array antenna into subarrays. The size of the subarrays also determines the number of cable folds and the complexity of the project. Typically, a subarray contains several antenna elements, and each element is connected to a TR (Transmit-Receive) channel component. Each TR channel component needs to undergo sampling preprocessing by a DAC (Digital-to-Analog Converter) and an ADC (Analog-to-Digital Converter) before being sent to a DBF (Digital Beam Forming) processor to complete beam weighting calculations and achieve beam scanning coverage. Therefore, each subarray inevitably has multiple fiber optic cables for transmission and reception between the data transmission layer and the DBF processor.

[0059] For example, based on a project requirements analysis, assuming a common antenna aperture and 16 transmit / receive beams, the transmit and receive DBF transmission rates would each reach over 32Gbps. Using a standard 10Gbps transmission rate fiber optic cable as an example, this would require four cables for each transmission and reception. For multi-fold satellites, such as three-fold satellites, at least 16 fiber optic cables are needed for both transmission and reception. Since the DBF processor is often housed within the satellite's main compartment, the reliability of fiber optic cable bends must be addressed for deployable antenna arrays.

[0060] This disclosure addresses potential shortcomings of some of the aforementioned technical solutions and proposes a general design concept for a phased array antenna for multi-fold satellites directly connecting to mobile phones. By combining the characteristics of phased array antenna technology and laser communication technology, a feasible design scheme for a phased array antenna for multi-fold satellites is achieved. Specifically, by expanding the phased array antenna through multi-fold satellite deployment, using an infrared horizon instrument for array surface measurement and calibration, and combining multi-stage DBF processing of digital phased array antennas with high-speed laser data transmission, a large-aperture, highly reliable phased array antenna for multi-fold satellites is designed.

[0061] The beam processing scheme for the antenna array disclosed herein employs a hierarchical beam processing method. First, the antenna array is divided into multiple first-level subarrays, and their output vectors are calculated. Then, a beam weighting matrix for each first-level subarray is constructed. Subsequently, the first-level subarrays are merged into second-level subarrays, and a composite matrix of the second-level subarrays is generated using the output vectors and the weighting matrix. Finally, the second-level subarrays are integrated into a third-level full array, and the accurate output vector of the third-level full array is calculated using the composite matrix. This achieves efficient and accurate calculation of the antenna array beam data.

[0062] This disclosure effectively reduces the computational complexity of DBF for ultra-large-scale arrays by rationally dividing the subarray size and multi-level DBF processing, and by combining centralized DBF with distributed DBF.

[0063] This paper first introduces the multi-fold satellite disclosed herein to facilitate understanding of the technical means described later. The beam processing method of the antenna array of this disclosure will be described later. The multi-fold satellite of this disclosure can be applied to communication scenarios oriented towards direct mobile phone connections.

[0064] Figure 2 A schematic diagram 200 showing a multi-fold satellite facing the ground according to some embodiments of the present disclosure is shown. Figure 3 A schematic diagram 300 of a multi-fold satellite facing the sky plane according to some embodiments of the present disclosure is shown. (Reference) Figure 2 and Figure 3 As shown, the multi-fold satellite 10 of this embodiment includes: a main body 11, comprising multiple cabin modules 12 and a folding mechanism (not shown in the figure), the folding mechanism being connected to each cabin module 12, and the folding mechanism being used to drive the cabin modules 12 to rotate so that the main body 11 is in a stacked and folded state (not shown in the figure) or a flat and unfolded state (e.g., ...). Figure 2 and Figure 3 (shown in deployed state); each cabin module 12 includes an antenna module 13 and a DBF processor 15. In some embodiments, each cabin module 12 also includes an infrared horizon instrument 16, an optical module 17, and a heat pipe 19.

[0065] refer to Figure 2 and Figure 3 As shown, the multi-fold satellite 10 also includes solar panels 18, which are connected to the cabin module 12; wherein, when the main body 11 is in a flat, unfolded state: all antenna modules 13 form an antenna array 14 (as shown in the image). Figure 2 The area outlined in the dashed box is shown in the image. An infrared horizon meter 16 is used to measure and correct the planar accuracy of the antenna array 14. An optical module 17 is used to transmit data between each DBF processor 15. At least one DBF processor 15 is used to execute the beamforming method for the antenna array of this disclosure. In some embodiments, the antenna array 14 is a phased array antenna array. The optical module 17 includes a laser module.

[0066] For example, Figure 2 and Figure 3The illustrated multi-fold satellite 10 includes three cabin modules 12, thus equivalent to a three-fold satellite. The unfolding mechanism of this disclosure can flexibly drive the cabin modules 12 to switch between stacked and unfolded states. When unfolded, the antenna modules 13 on each cabin module 12 work together to form a large antenna array. This disclosure solves key problems of rapid digital multi-beamforming, high-precision measurement and calibration of the unfolded plane, and wireless transmission of high-speed data in the multi-fold satellite 10 through multi-level DBF processing of the array antenna, measurement and calibration of the unfolded array by the infrared horizon instrument 16, and high-speed data transmission via the optical module 17. The multi-fold satellite 10 of this disclosure improves the coverage, accuracy, and flexibility of satellite communication.

[0067] Figure 5 A schematic diagram 500 showing a multi-fold satellite facing the ground according to other embodiments of the present disclosure is shown. (See reference...) Figure 5 As shown, exemplarily, this embodiment illustrates a five-fold satellite 10, which can be used to perform planar measurements using an infrared horizon instrument 16, and then compared and corrected using the original data. In practical applications, the infrared horizon instrument 16 can be replaced by other measuring devices, and this disclosure does not limit the number of folds in the multi-fold satellite 10. This disclosure uses a laser module to achieve wireless high-speed data transmission between multiple DBFs of the multi-fold satellite 10.

[0068] This disclosure also proposes an antenna module. (See reference...) Figure 2 and Figure 3 As shown, in some embodiments, the antenna module includes an antenna module 13 and a DBF processor 15. Multiple antenna modules 13 form an antenna array 14, and the DBF processor 15 is used to execute the beam processing method for the antenna array of this disclosure. Exemplarily, the antenna module can be mounted on a satellite 10 or on the ground; this application does not impose any limitations.

[0069] Figure 4 A schematic diagram 400 of a multi-level DBF processing according to some embodiments of the present disclosure is shown. Exemplarily, reference is made to... Figure 3 and Figure 4 As shown, this disclosure provides a DBF processor 15 on each cabin module 12, and a general DBF processor 15 on one of the cabin modules 12. Figure 4 As shown, the first-level subarray 141, the second-level subarray 142, and the third-level full array 143 are shown with dashed boxes of different sizes. For example, a second-level subarray 142 can be formed by three horizontal first-level subarrays 141, and a third-level full array 143 can be formed by three vertical second-level subarrays 142. This disclosure does not limit the number of first-level subarrays 141, second-level subarrays 142, and third-level full arrays 143.

[0070] The overall design concept of the multi-level DBF for the phased array antenna disclosed in this paper is as follows: The digital beamforming (DBF) algorithm, through weight control, can achieve both super-resolution and low-resolution performance, and realize beam scanning, self-calibration, and adaptive beamforming. In the multi-level DBF architecture, the entire antenna array is divided into multiple subarrays, each responsible for a portion of the beamforming task, thereby reducing computational complexity. A simplified model of the three-level processing architecture will be introduced later in this disclosure, along with the calculation method for the beamforming matrix of each level.

[0071] For example, the beneficial effects that the multi-fold satellite of this disclosure can produce are as follows.

[0072] (1) Measurement and calibration of the unfolded array.

[0073] Multi-fold satellites measure the planar accuracy of the deployed antenna by carrying an infrared horizon instrument on each fold of the satellite. The measurement accuracy is better than 0.1°, which can meet the high-precision measurement requirements of ultra-large-scale arrays. At the same time, the on-orbit measurement data is compared with the pre-stored measurement data on the ground to complete the on-orbit planar accuracy correction, thereby improving the pointing accuracy of the ultra-narrow high-gain beam.

[0074] (2) Multi-level DBF processing.

[0075] The multi-fold satellite ultimately consists of multiple satellites deployed in parallel to form an ultra-large-scale phased array antenna, with each fold of the satellite achieving a range of 3-4 meters. 2 With a large aperture area, a multi-level DBF processing architecture is adopted, which divides the entire antenna array into three levels of subarrays. Each level is responsible for a part of the beamforming task, thereby reducing the computational complexity of the ultra-large-scale array.

[0076] (3) High-speed laser data transmission.

[0077] The multi-fold satellite design incorporates a centralized DBF processor and multiple distributed DBF processors. Each fold of the satellite is equipped with a distributed DBF processor to perform DBF calculations for two levels of subarrays. The final level involves a unified calculation of the DBF across multiple satellites, with the DBF at this level fixed within a specific fold of the satellite. This disclosure utilizes a lightweight, compact laser module with a gigabit-rate capability to achieve high-speed, cable-free data transmission between the distributed and centralized DBF functions of the multi-fold satellite. Simultaneously, the on-orbit health data of each fold of the satellite can be transmitted via the laser module to the satellite's onboard base station or integrated electronics, effectively solving the problem of fiber optic cable bending during the folding and unfolding of large-scale phased array antennas.

[0078] The beam processing method for the antenna array disclosed herein will be introduced below.

[0079] Figure 1A flowchart 100 illustrates a beam processing method for an antenna array according to an embodiment of the present disclosure.

[0080] refer to Figure 1 As shown, the beam processing method for the antenna array in this embodiment includes the following steps:

[0081] Step S110: Divide the antenna array into multiple first-level subarrays, calculate the first output vector of each first-level subarray, and construct the first-level subarray beam weighting matrix based on the first output vector.

[0082] Step S120: Merge multiple first-level subarrays into multiple second-level subarrays, calculate the second output vector of each second-level subarray based on the first output vector, and calculate the second-level subarray synthesis matrix based on the second output vector and the first-level subarray beam weighting matrix.

[0083] Step S130: Merge multiple second-level subarrays into a third-level full array, and calculate the third output vector of the third-level full array based on the combined matrix of the second-level subarrays and the combined matrix of the third-level full array.

[0084] The following details steps S110 to S130:

[0085] Here we will first give a general overview of the process of first-level subarray DBF beamforming to facilitate understanding of step S110 described later.

[0086] For example, suppose there is an original antenna array that is an M×N matrix, where M is the number of array elements along the x-axis and N is the number of array elements along the y-axis. It is divided into P×Q first-level subarrays, each of which has a size of m×n. Beamforming within each subarray can be achieved by weighting the signals of various array elements, where m < M and n < N, and P·m = M, Q·n = N.

[0087] The element signals within each first-level subarray are first weighted to form the first-level subarray output. For each first-level subarray (p, q), the corresponding weight vector is calculated. Where p = 0, 1, 2, ..., P-1, q = 0, 1, 2, ..., Q-1. The input data vector for each first-order submatrix is ​​x. p,q Then the output vector of the first-order submatrix is:

[0088]

[0089] In summary, the first-level subarray DBF beam weighting matrix is:

[0090]

[0091] For example, the weighted matrix of the first-level submatrix: the weight vector of each first-level submatrix. The weight vector can be determined in various ways, such as based on the Minimum Mean Square Error (MMSE) or other beamforming techniques. Taking a certain beamforming technique as an example, the weight vector can be expressed as:

[0092]

[0093] in, It is the channel matrix of the subarray (p,q), u p,q It is a vector pointing in the direction of the target.

[0094] The following describes step S110 of this disclosure.

[0095] In step S110, the antenna array is divided into multiple first-level subarrays, the first output vector of each first-level subarray is calculated, and a beam weighting matrix of the first-level subarray is constructed based on the first output vector. For example, this configuration enables efficient and flexible control of the antenna array beam, improving the performance and accuracy of the communication system.

[0096] In some embodiments, the antenna array is disposed on a satellite, which further includes an infrared horizon instrument; before dividing the antenna array into multiple primary subarrays, the following are also included:

[0097] The planar accuracy of the antenna array is measured using an infrared horizon instrument.

[0098] If the difference between the plane accuracy and the target accuracy is greater than a preset threshold, the plane accuracy is corrected to the target accuracy.

[0099] For example, this disclosure uses an infrared horizon instrument to perform high-precision measurement of the flatness of the ultra-large-scale array deployment and compares and corrects it with pre-stored data, which can solve the problems of beamforming parameter changes and beam pointing accuracy deterioration caused by deployment plane error.

[0100] In some embodiments, the satellite further includes an optical module, which includes a laser module; during the execution of the beam processing method, the optical module is used to obtain the number of array elements and beam data of the antenna array. Exemplarily, this disclosure achieves high-speed data transmission between distributed and centralized DBFs through a laser module with a 100 gigabit rate for each fold of the satellite, solving the problem of cableless transmission between the high-speed data interface of the deployed array and the high-speed data interface of the satellite body, and avoiding the risks caused by the bending of optical fiber cables.

[0101] In some embodiments, the antenna array is divided into multiple first-level subarrays, including: the antenna array has N×N array elements, and the antenna array is divided into P×Q first-level subarrays; wherein, the antenna array includes an x-axis and a y-axis; M represents the number of array elements along the x-axis; N represents the number of array elements along the y-axis; the size of each first-level subarray is m×n, m<M, n<N, and P·m=M, Q·n=N.

[0102] For example, this disclosure ensures complete coverage of the array elements and reasonable division by dividing the antenna array, thereby achieving optimized configuration and efficient management of antenna array resources and providing a foundation for subsequent signal processing and beamforming.

[0103] In some embodiments, calculating the first output vector for each first-order subarray includes: calculating the first output vector using the following formula:

[0104]

[0105] in, The first output vector is represented by the superscript (1); the subscript (p, q) represents the first-level submatrix. The weight vectors of the first-order submatrix are p = 0, 1, 2, ..., P-1; q = 0, 1, 2, ..., Q-1; the superscript H denotes the conjugate transpose matrix; x p,q This represents the input data vector of the first-order submatrix.

[0106] In some embodiments, the weight vector of the first-level submatrix is ​​calculated using the following formula:

[0107]

[0108] in, Represents the weight vector of the first-order submatrix; It is the channel matrix of a first-order subarray (p,q); u p,q This represents a vector pointing in the direction of the target.

[0109] In some embodiments, constructing a first-level subarray beamweighting matrix based on a first output vector includes: constructing the first-level subarray beamweighting matrix using the following formula:

[0110]

[0111] Among them, Y (1) This represents the beam weighting matrix of the first-level subarray.

[0112] For example, by calculating the first output vector, calculating the weight vector of the first-level subarray, and constructing the beam weighting matrix of the first-level subarray, this disclosure can provide an accurate data foundation for subsequent signal synthesis and beamforming, and improve the performance and flexibility of the satellite communication system.

[0113] First, we will introduce the process of weighted calculation for the second-level subarray beamforming to facilitate understanding of step S120 described later.

[0114] For example, in the second-level processing, the outputs of the first-level subarrays are further merged into larger second-level subarrays. Assume that the output of the first level is divided into R×S second-level subarrays, each of which consists of r×s first-level subarrays, where r·R=P and s·S=Q.

[0115] For each second-level submatrix (r, s), its input first-level submatrix output vector is:

[0116]

[0117] The weight vector of each second-level subarray The output vector of the second-level subarray is then:

[0118]

[0119] In summary, the composite matrix of the second-order subarrays is: Y (2) =G (2) Y (1) .

[0120] For example, the weight matrix of the second-level subarray: the weight vector of the second-level subarray. The weight vector can also be designed based on the output of the first-level subarray. The weight vector can be based on channel estimation or a predefined direction vector.

[0121] The following describes step S120 of this disclosure.

[0122] In step S120, multiple first-level subarrays are merged into multiple second-level subarrays. A second output vector for each second-level subarray is calculated based on the first output vector. Finally, a composite matrix of the second-level subarrays is calculated based on the second output vector and the beam weighting matrix of the first-level subarrays. Exemplarily, this configuration allows for hierarchical optimization of antenna array signal processing, improving both efficiency and accuracy.

[0123] In some embodiments, merging multiple primary subarrays into multiple secondary subarrays includes: merging P×Q primary subarrays into R×S secondary subarrays; wherein each secondary subarray includes r×s primary subarrays; r·R=P; s·S=Q. Exemplarily, this disclosure, by merging subarrays, ensures complete coverage of the antenna array and optimized resource allocation, providing a more flexible and efficient hierarchical structure for subsequent signal processing and beamforming.

[0124] In some embodiments, calculating the second output vector for each second-level subarray based on the first output vector includes: calculating the second output vector using the following formula:

[0125]

[0126] in, This indicates the second output vector, and the superscript (2) indicates the second-level submatrix; Represents the weight vector of the second-level submatrix; This represents the first output vector of the first-level subarray.

[0127] In some embodiments, calculating the second-level subarray synthesis matrix based on the second output vector and the first-level subarray beam weighting matrix includes: calculating the second-level subarray synthesis matrix using the following formula:

[0128] Y (2) =G (2) Y (1)

[0129] Among them, Y (2) Y represents the composite matrix of second-order subarrays; (1) G represents the beam weighting matrix of the first-level subarray; (2) This indicates that during the calculation of the second output vector, the weight vector of the second-level submatrix is ​​used. The weight matrix is ​​formed.

[0130] For example, by calculating the second output vector and the secondary subarray synthesis matrix, this disclosure can provide an accurate data foundation for subsequent signal synthesis and beamforming, and improve the performance and flexibility of satellite communication systems.

[0131] First, we will introduce the weighted calculation process of the three-level full array beamforming to facilitate understanding of step S130 described later.

[0132] For example, in the third-level beamforming process, the outputs of the second-level subarrays are combined into the beamforming output of the entire third-level full array. Alternatively, the third-level process could directly combine the outputs of all second-level subarrays into the final beamforming output.

[0133] Let G be the composition matrix of the third level. (3) Then the final beamforming output vector can be expressed as:

[0134] y = G (3)H Y (2)

[0135] Among them, Y (2) It is the set of outputs from all second-level subarrays.

[0136]

[0137] For example, the weight matrix of a three-level full matrix: the three-level composite matrix G (3)It can be an equal-weighted matrix or a matrix designed based on optimization criteria to maximize the signal-to-noise ratio or meet other metrics.

[0138] Step S130 of this disclosure is described below.

[0139] In step S130, multiple secondary subarrays are merged into a tertiary full array, and the third output vector of the tertiary full array is calculated based on the secondary subarray synthesis matrix and the tertiary full array synthesis matrix. Exemplarily, this disclosure achieves further integration and optimization of antenna array signal processing, enhancing the overall performance of signal processing and the flexibility of beamforming.

[0140] In some embodiments, calculating the third output vector of the third-level full matrix based on the second-level subarray composite matrix and the third-level full matrix composite matrix includes: calculating the third output vector using the following formula:

[0141] y = G (3)H Y (2)

[0142]

[0143] Where y represents the third output vector; G (3) Y represents a three-level full matrix, with the superscript (3) indicating a three-level full matrix; (2) This represents the set of the second output vectors of all second-level subarrays.

[0144] The following section will introduce the application mode of the phased array antenna for multi-fold satellite direct connection to mobile phones proposed in this disclosure.

[0145] For example, multi-fold satellite phased array antennas can directly improve the system's EIRP (Equivalent Isotropic Radiated Power) and G / T value, meeting the satellite-to-ground link margin requirements for direct satellite connection of mobile phones and ensuring reliable access for users.

[0146] With a general-purpose mobile phone (S-band) transmit power of 23dBm, the phased array antenna of the multi-fold satellite has an aperture area of ​​10.5m². 2 (The aperture area of ​​each fold of the antenna is 3.5m) 2 Total 3.5m 2 For example, with a satellite in a 500km orbit, a mobile phone can communicate at a maximum distance of approximately 900km at a low elevation angle of 30°.

[0147] According to the antenna gain calculation formula:

[0148]

[0149] According to the link carrier-to-noise ratio calculation formula:

[0150]

[0151] By considering factors such as system noise, data rate, polarization loss, pointing loss, atmospheric loss, rainfall loss, and human body loss, it can be calculated that the on-board receive signal-to-carrier ratio reaches over 6dB, meeting the link margin requirements for direct satellite connection between mobile phones and satellites.

[0152] The overall design concept and application mode of the multi-fold satellite phased array antenna for direct mobile phone connection proposed in this disclosure increase the effective aperture area of ​​the phased array antenna by unfolding the satellite in a multi-fold manner. Combined with multi-level DBF processing, high-speed laser data transmission, and infrared horizon array measurement and correction, the phased array antenna effectively improves the transmit EIRP value and receive G / T value, ensures the satellite-to-ground link margin for direct mobile phone connection, and can meet the user's safe and reliable access requirements.

[0153] This disclosure also provides a computing device, including: at least one processor; and at least one memory storing instructions thereon, which, when executed individually or collectively by the at least one processor, cause the computing device to perform the beam processing method for the antenna array described above.

[0154] Figure 6 A simplified block diagram of a device 600 suitable for implementing exemplary embodiments of the present disclosure is shown. For example, a satellite network device and / or a terminal device may be implemented by device 600. As shown, device 600 includes one or more processors 610, one or more memories 620 coupled to processor 610, and one or more communication modules 640 coupled to processor 610.

[0155] Communication module 640 is used for bidirectional communication. Communication module 640 has at least one antenna to facilitate communication. The communication interface can represent any interface necessary for communication with other network elements.

[0156] Processor 610 can be of any type suitable for a local technology network, and as a non-limiting example, can include one or more of the following: general-purpose computer, special-purpose computer, microprocessor, digital signal processor (DSP), and processor based on a multi-core processor architecture. Device 600 can have multiple processors, such as application-specific integrated circuit (ASIC) chips, which are timely driven to a clock that synchronizes with the main processor.

[0157] Memory 620 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 624, electrically programmable read-only memory (EPROM), flash memory, hard disk, optical disc (CD), digital video disc (DVD), and other magnetic and / or optical storage. Examples of volatile memories include, but are not limited to, random access memory (RAM) 622 and other volatile memories that do not persist during power-off periods.

[0158] Computer program 630 includes computer-executable instructions that are executed by a associated processor 610. Program 630 may be stored in ROM 624. Processor 610 may perform any appropriate actions and processes by loading program 630 into RAM 622.

[0159] The embodiments of this disclosure can be implemented via program 630, enabling device 600 to execute reference... Figure 1 Any process disclosed herein. Embodiments of this disclosure may also be implemented in hardware or by a combination of software and hardware.

[0160] In some embodiments, program 630 may be tangibly contained in a computer-readable medium, which may be contained in device 600 (e.g., memory 620) or other storage device accessible to device 600. Device 600 may load program 630 from the computer-readable medium into RAM 622 for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. Program 630 is stored on the computer-readable medium.

[0161] This disclosure also provides a non-transitory computer-readable storage medium storing machine-executable instructions that, when executed individually or jointly by one or more processors of the machine, cause the machine to perform the beamforming method of the antenna array described above.

[0162] This disclosure also provides a chip system including a circuit system configured to perform the beam processing method for the antenna array described above.

[0163] Generally, the various embodiments of this disclosure can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects may be implemented in hardware, while others may be implemented in firmware or software, which may be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this disclosure are shown and described as block diagrams, flowcharts, or other graphical representations, it should be understood that, as non-limiting examples, the blocks, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0164] This disclosure also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in a program module, which execute in a device on a target real or virtual processor to perform the aforementioned references. Figure 1 The method 100. Typically, a program module includes routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of a program module can be combined or separated among program modules as needed. The machine-executable instructions for a program module can be executed locally or in a distributed device. In a distributed device, the program module can reside in both local and remote storage media.

[0165] Program code used to perform the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, partially on a remote machine, partially on a remote machine, or entirely on a remote machine or server as a standalone software package.

[0166] In the context of this disclosure, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, etc.

[0167] Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable media can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or apparatuses, or any suitable combination thereof. More specific examples of computer-readable storage media include electrical connections having one or more wires, portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable optical disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0168] Furthermore, although the operations are described in a specific order, this should not be construed as requiring that these operations be performed in the specific order or sequence shown, or that all of the operations shown be performed to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the foregoing discussion, these details should not be construed as limiting the scope of this disclosure, but rather as descriptions of features specific to particular embodiments. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0169] Although this disclosure has been described in language specific to structural features and / or methodological behavior, it should be understood that this disclosure as defined in the appended claims is not necessarily limited to the specific features or behaviors described above. Rather, the specific features and actions described above are disclosed as exemplary forms for implementing the claims.

[0170] It should be fully understood that the use of personally identifiable information should comply with privacy policies and practices generally considered to meet or exceed industry or governmental requirements for protecting user privacy. In particular, personally identifiable information data should be managed and processed to minimize the risk of unintentional or unauthorized access or use, and the nature of authorized use should be clearly indicated to the user.

Claims

1. A beam processing method for an antenna array, characterized in that, include: The antenna array is divided into multiple first-level subarrays, the first output vector of each first-level subarray is calculated, and the first-level subarray beam weighting matrix is ​​constructed based on the first output vector. The multiple first-level subarrays are merged into multiple second-level subarrays. The second output vector of each second-level subarray is calculated based on the first output vector. The second-level subarray synthesis matrix is ​​calculated based on the second output vector and the beam weighting matrix of the first-level subarray. The multiple second-level subarrays are merged into a third-level full array, and the third output vector of the third-level full array is calculated based on the combined matrix of the second-level subarrays and the combined matrix of the third-level full array.

2. The beam processing method as described in claim 1, characterized in that, The antenna array is divided into multiple first-level subarrays, including: the antenna array has M×N array elements, and the antenna array is divided into P×Q first-level subarrays; The antenna array includes an x-axis and a y-axis; M represents the number of array elements along the x-axis; N represents the number of array elements along the y-axis; the size of each first-level subarray is m×n, m<M, n<N, and P·m=M, Q·n=N.

3. The beam processing method as described in claim 2, characterized in that, Calculate the first output vector for each first-order submatrix, including: calculating the first output vector using the following formula: in, The first output vector is represented by the superscript (1); the subscript (p, q) represents the first-level submatrix. The weight vectors of the first-order submatrix are p = 0, 1, 2, ..., P-1; q = 0, 1, 2, ..., Q-1; the superscript H denotes the conjugate transpose matrix; x p,q This represents the input data vector of the first-order submatrix.

4. The beam processing method as described in claim 3, characterized in that, The weight vector of the first-order submatrix is ​​calculated using the following formula: in, This represents the weight vector of the first-order submatrix; It is the channel matrix of a first-order subarray (p,q); u p,q This represents a vector pointing in the direction of the target.

5. The beam processing method as described in claim 3, characterized in that, Constructing the first-level subarray beam weighting matrix based on the first output vector includes: constructing the first-level subarray beam weighting matrix using the following formula: Among them, Y (1) This represents the beam weighting matrix of the first-level subarray.

6. The beam processing method as described in claim 3, characterized in that, Merging the multiple first-level subarrays into multiple second-level subarrays includes: merging the P×Q first-level subarrays into R×S second-level subarrays; Each second-level subarray consists of r×s first-level subarrays; r·R=P; s·S=Q.

7. The beam processing method as described in claim 6, characterized in that, Calculating the second output vector for each second-level subarray based on the first output vector includes: calculating the second output vector using the following formula: in, This represents the second output vector, and the superscript (2) represents the second-level submatrix; Represents the weight vector of the second-level submatrix; This represents the first output vector of the first-level subarray.

8. The beam processing method as described in claim 7, characterized in that, The second-level subarray synthesis matrix is ​​calculated based on the second output vector and the first-level subarray beam weighting matrix, including: calculating the second-level subarray synthesis matrix using the following formula: AND (2) =G (2) AND (1) Among them, Y (2) Y represents the composite matrix of the second-order subarrays; (1) G represents the beam weighting matrix of the first-order subarray; (2) This indicates that during the calculation of the second output vector, the weight vector of the second-level submatrix... The weight matrix is ​​formed.

9. The beam processing method as described in claim 8, characterized in that, The third output vector of the third-level full array is calculated based on the combined matrix of the second-level subarray and the combined matrix of the third-level full array, including: calculating the third output vector using the following formula: y=G (3)H AND (2) Where y represents the third output vector; G (3) The superscript (3) indicates the composite matrix of the three-level full array; Y (2) This represents the set of the second output vectors of all second-level subarrays.

10. The beam processing method according to any one of claims 1-9, characterized in that, The antenna array is mounted on a satellite, which also includes an infrared horizon instrument; before dividing the antenna array into multiple primary subarrays, the following is also included: The planar accuracy of the antenna array is measured using the infrared horizon instrument. In response to the difference between the plane accuracy and the target accuracy being greater than a preset threshold, the plane accuracy is corrected to the target accuracy.

11. The beam processing method according to any one of claims 1-9, characterized in that, The antenna array is mounted on the satellite, which also includes an optical module, including a laser module. During the execution of the beam processing method, the optical module is used to obtain the number of array elements and beam data of the antenna array.

12. The beam processing method according to any one of claims 1-9, characterized in that, The antenna array is a phased array antenna array.

13. An antenna module, characterized in that, include: An antenna module and a DBF processor are provided, wherein multiple antenna modules constitute an antenna array, and the DBF processor is used to execute the beam processing method of the antenna array as described in any one of claims 1-12.

14. A multi-fold satellite, characterized in that, include: The main body includes multiple cabin modules and a folding mechanism. The folding mechanism is connected to each cabin module and is used to drive the cabin module to rotate so that the main body can be stacked and folded or laid out flat. Each cabin module includes an antenna module and a DBF processor. Solar panels are connected to the cabin module; Specifically, when the main body is in a flat, unfolded state: Multiple antenna modules constitute an antenna array; At least one DBF processor is used to execute the beam processing method for the antenna array as described in any one of claims 1-12.

15. The multi-fold satellite as described in claim 14, characterized in that, Each cabin module also includes an infrared horizon meter, which is used to measure and correct the planar accuracy of the antenna array.

16. The multi-fold satellite as described in claim 14, characterized in that, Each cabin module also includes an optical module, which is used to transmit data between each DBF processor.

17. A computing device, characterized in that, include: At least one processor; as well as At least one memory storing instructions that, when executed individually or jointly by the at least one processor, cause the computing device to perform a beam processing method for an antenna array according to any one of claims 1-12.

18. A non-transitory computer-readable storage medium storing machine-executable instructions, characterized in that, When the machine-executable instructions are executed individually or jointly by one or more processors of the machine, the machine performs the beam processing method for the antenna array according to any one of claims 1-12.

19. A chip system, comprising a circuit system, characterized in that, The circuit system is configured to perform the beam processing method for the antenna array according to any one of claims 1-12.

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