Navigation signal correction method, device, equipment, medium, product and chip system

Abstract

The invention provides a navigation signal correction method and device, equipment, a medium, a product and a chip system.The method comprises the steps that an initial response model is constructed through nonlinear characteristics of load hardware of satellite equipment under different input conditions, adjustment coefficients of the initial response model are updated through preset environment influence parameters, and therefore a target correction model is obtained; and correcting the navigation signal to obtain a corrected signal. Thus, the hardware nonlinear characteristic and the dynamic environment nonlinear characteristic of the satellite equipment are subjected to dual comprehensive modeling, so that the target correction model can improve the accuracy and the stability of the navigation signal, and the interference of the nonlinear characteristic on the navigation signal is remarkably reduced.

Description

Technical Field

[0001] The present disclosure mainly relates to the field of communication technology, and in particular to a navigation signal correction method, device, computer equipment, computer storage medium, computer program product and chip system. Background Art

[0002] The low-orbit satellite navigation system provides high-precision positioning services by transmitting navigation signals, and the signal quality will directly affect the positioning accuracy of the terminal.

[0003] However, the existing navigation signals are affected by hardware and environmental distortion during transmission. For example, the hardware nonlinear characteristics of satellite payload equipment (such as power amplifiers and filters) cause signal distortion. At the same time, the Doppler frequency shift effect caused by high-speed satellite movement, temperature changes, and frequent satellite switching cause signal parameter drift and transient interference, which will further produce dynamic nonlinear characteristics. The combined effect of hardware nonlinear characteristics and dynamic nonlinear characteristics will greatly reduce the stability and accuracy of navigation signals. Summary of the invention

[0004] It would be advantageous to provide a mechanism that mitigates, alleviates or eliminates at least one of the problems discussed above.

[0005] In a first aspect, the present disclosure provides a navigation signal correction method, the method comprising: Constructing an initial response model of the satellite device; the initial response model characterizes the nonlinear characteristics of the payload hardware of the satellite device under different input conditions; Based on preset environmental impact parameters, updating the adjustment coefficient of the initial response model to obtain a target correction model; the adjustment coefficient represents the influence of the environmental impact parameter on the nonlinear characteristic; Based on the target correction model, the navigation signal is corrected to obtain a correction signal.

[0006] In a second aspect, the present disclosure provides a navigation signal correction device, the device comprising: a device for executing the above-mentioned navigation signal correction method.

[0007] In a third aspect, the present disclosure provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, any one of the navigation signal correction methods described in the first aspect is implemented.

[0008] In a fourth aspect, the present disclosure provides a computer storage medium, wherein the computer-readable storage medium stores computer program instructions, and the computer program instructions are executed by a processor to perform any one of the navigation signal correction methods in the first aspect.

[0009] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, comprising computer program instructions, which, when executed by a processor, implement any one of the navigation signal correction methods in the first aspect.

[0010] In a sixth aspect, an embodiment of the present disclosure provides a chip system of a computer device, comprising at least one processor, wherein the at least one processor is configured to individually or jointly execute a computer program stored in a memory of the computer device in the third aspect above, so that the computer device performs any one of the navigation signal correction methods in the first aspect above.

[0011] It should be understood that the invention summary is not intended to identify the key or essential features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings are included to provide a further understanding of the present disclosure, and they are included and constitute a part of the present disclosure. The accompanying drawings illustrate embodiments of the present disclosure and together with the specification serve to explain the principles of the present disclosure. In the accompanying drawings: Figure 1 is a schematic diagram of an application scenario provided by an embodiment of the present disclosure; Figure 2 is a flowchart of a navigation signal correction method provided by an embodiment of the present disclosure; Figure 3 is a schematic diagram of another process of navigation signal correction provided by an embodiment of the present disclosure; Figure 4 A schematic diagram of the structure of a computer device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present disclosure. For ordinary technicians in this field, the present disclosure can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0014] In the following description and claims, unless defined otherwise, 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 belongs.

[0015] References in this disclosure to "one embodiment," "an embodiment," "an exemplary embodiment," etc. indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment necessarily includes the particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment. In addition, when a particular feature, structure, or characteristic is described in conjunction with an exemplary embodiment, whether or not explicitly described, those skilled in the art will recognize that such feature, structure, or characteristic affects incorporation into other embodiments.

[0016] As shown in the present disclosure, unless the context clearly indicates an exception, the words "one", "a", "a kind of" and / or "the" do not specifically refer to the singular, and may also include plural forms. Unless the context clearly indicates otherwise. "A group of elements" or "element set" used herein is intended to include one or more elements. It should also be understood that the terms "include", "comprise", "have", "have", "include" and / or "include", when used in this article, specify the existence of the features, elements and / or parts, etc., only prompt the inclusion of clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements, and therefore does not exclude the existence or addition of one or more other features, elements, parts and / or their combinations. Unless otherwise specified, the relative arrangement of the parts and steps described in these embodiments, the numerical expressions and numerical values ​​do not limit the scope of the present disclosure. At the same time, it should be understood that for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The techniques, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and equipment should be regarded as part of the specification. In all examples shown and discussed herein, any specific value should be interpreted as being merely exemplary and not limiting. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0017] In the description of the present disclosure, it is necessary to understand that the orientation or positional relationship indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present disclosure and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the scope of protection of the present disclosure; the directional words "inside and outside" refer to the inside and outside relative to the outline of each component itself.

[0018] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0019] In addition, it should be noted that the use of words such as "first" and "second" to define parts is only for the convenience of distinguishing the corresponding parts. If not otherwise stated, the above words have no special meaning and cannot be understood as limiting the scope of protection of the present disclosure. Therefore, although the terms "first" and "second" can be used to describe various elements in this article, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the exemplary embodiment, the first element can be referred to as the second element, and similarly, the second element can be referred to as the first element. The term "and / or" used herein includes any and all combinations of one or more of the listed terms. In addition, although the terms used in the present disclosure are selected from well-known and commonly used terms, some of the terms mentioned in the present disclosure may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description of this article. In addition, it is required to understand the present disclosure not only by the actual terms used, but also by the meaning implied by each term.

[0020] To facilitate understanding of the technical solution provided by the embodiments of the present disclosure, some key terms used in the embodiments of the present disclosure are explained here: Navigation signal: A radio signal sent by a navigation satellite to ground equipment (such as a receiver) for ground equipment to determine relevant location information. The receiver can demodulate and analyze the navigation signal to extract the location information and time synchronization information.

[0021] Receiver: A terminal device that can receive and process signals from navigation satellites to determine the location information (including longitude, latitude and altitude) of ground targets and time synchronization information. Its main functions include signal capture, demodulation, pseudo-code tracking and position calculation.

[0022] Low Earth Orbit Satellite (LEO Satellite): refers to an artificial satellite operating in low Earth orbit (LEO), with an orbital altitude usually between 160 kilometers and 2,000 kilometers.

[0023] As used herein, the term "communication network" refers to a network that complies with any appropriate 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. In addition, the communication between the terminal equipment and the network equipment in the communication network can be performed according to any appropriate generation of communication protocols, including but not limited to the first generation (1G), second generation (2G), 2.5G, 2.75G, third generation (3G), fourth generation (4G), 4.5G, fifth generation (5G), future sixth generation (6G) communication protocols, and / or any other protocols currently known or to be developed in the future. The embodiments of the present disclosure can be applied in satellite communication systems. In view of the rapid development in communication, there will certainly be future types of communication technologies and systems, and the present disclosure can be implemented with these technologies and systems. It should not be considered that the scope of the present disclosure is limited to the aforementioned system.

[0024] The term "satellite network equipment" used in this article refers to a node set on a satellite or ground segment in a satellite communication network. The terminal device accesses the network through this node and receives services from it. Depending on the terminology and technology applied, the satellite network equipment may refer to a base station (BS) or access point (AP) as a satellite payload, such as a node B (NodeB or NB), an evolved NodeB (eNodeB or eNB), a NR NB (also known as a gNB), a remote radio unit (RRU), a radio head (RH), a remote radio head (RRH), and a relay node. An example of a relay node may be an integrated access and backhaul (IAB) node. The distributed unit (DU) part of the IAB node can perform the functions of a "satellite network device" and can therefore operate as a network device. In the following description, the terms "satellite network equipment", "BS" and "node" can be used interchangeably.

[0025] 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, a user equipment (UE), a user station (SS), a portable user station, a mobile station (MS), or an access terminal (AT). The terminal device may include, but is not limited to, a mobile phone, a cellular phone, a smart phone, a voice over IP (VoIP) phone, a wireless local loop phone, a tablet computer, a wearable terminal device, a personal digital assistant (PDA), a portable computer, a desktop computer, an image capture terminal device such as a digital camera, a game terminal device, a music storage and playback device, a vehicle-mounted wireless terminal device, a wireless endpoint, a mobile station, a notebook embedded device (LEE), a laptop mounted device (LME), a USB dongle, a smart device, a wireless user equipment (CPE), an Internet of Things (IoT) device, a watch or other wearable device, a head mounted display (HMD), a vehicle, a drone, medical equipment and applications (e.g., remote surgery), industrial equipment and applications (e.g., robots and / or other wireless devices operating in the context of an industrial and / or automated processing chain), consumer electronic devices, relay nodes, devices operating on commercial and / or industrial wireless networks, etc. The mobile terminal (MT) part of the IAB node can perform the functions of a "terminal device" and can therefore operate as a terminal device. In the following description, the terms "terminal device", "communication device", "terminal", "user equipment" and "UE" can be used interchangeably.

[0026] Although the functions described herein may be performed in fixed and / or wireless network nodes in various exemplary embodiments, in other exemplary embodiments, the functions may be implemented in a user equipment device (such as a cellular phone, or a tablet computer, or a laptop computer, or a desktop computer, or a mobile Internet of Things device, or a fixed Internet of Things device). For example, the user equipment device may appropriately have the corresponding capabilities described in relation to fixed and / or wireless network nodes. The user equipment device may be a user device and / or a control device, such as a chipset or a processor, which is configured to control the user device when the user device is installed therein. Examples of these functions include boot server functions and / or home user servers, which may be implemented in a user equipment device by providing the user equipment device with software configured to cause the user equipment device to execute from the perspective of these functions / nodes.

[0027] It is understandable that in the following specific implementations of the present disclosure, data related to navigation satellites, etc. are involved. When the various embodiments of the present disclosure are applied to specific products or technologies, relevant licenses or consents need to be obtained, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions. For example, relevant volunteers can be recruited and relevant agreements on volunteer authorization data can be signed, and then the data of these volunteers can be used for implementation; or, by implementing within the scope of an authorized organization, the following implementation methods are implemented by using the data of members within the organization to manage data; or, the relevant data used in the specific implementation are all simulated data, such as simulated data generated in a virtual scene.

[0028] The following is a brief introduction to the design concept of the embodiment of the present disclosure: The low-orbit satellite navigation system provides high-precision positioning services by transmitting navigation signals, and the signal quality will directly affect the positioning accuracy of the terminal. For example, in high-precision positioning scenarios such as autonomous driving, aviation navigation or ship navigation, terminal devices (such as vehicles, drones, and ships) rely on low-orbit satellite navigation signals for real-time position calculation.

[0029] However, the existing navigation signals are affected by hardware and environmental distortion during transmission. For example, the hardware nonlinear characteristics of satellite payload equipment (such as power amplifiers and filters) cause signal distortion. At the same time, the Doppler frequency shift effect caused by high-speed satellite movement, temperature changes, and frequent satellite switching cause signal parameter drift and transient interference, which will further produce dynamic nonlinear characteristics. The combined effect of hardware nonlinear characteristics and dynamic nonlinear characteristics will greatly reduce the stability and accuracy of navigation signals, especially causing a significant increase in the positioning error of navigation signals in complex scenarios, which seriously restricts the practical value of low-orbit satellite navigation systems.

[0030] For example, when a satellite transmits a navigation signal to a ground user, if the signal power is high, the amplifier gain no longer increases linearly at high power input, but tends to saturation. The amplifier cannot provide linear amplification, and the amplitude of the output signal is clipped, resulting in distortion of the navigation signal, making the signal power measured by the receiving end inaccurate, affecting the distance measurement accuracy.

[0031] At the same time, the rapid movement of low-orbit satellites and dynamic environmental factors (Doppler shift, satellite switching, temperature changes, etc.) will further aggravate the nonlinear effects of navigation signals. For example, the frequency of navigation signals from low-orbit satellites will change due to the Doppler effect. For example, when the satellite moves toward the receiver, the signal frequency will increase, and when the satellite moves away from the receiver, the signal frequency will decrease. At the same time, the operating point of the amplifier may drift due to the change in the input signal frequency, introducing additional distortion.

[0032] In view of the above problems, an embodiment of the present disclosure provides a navigation signal correction method, which constructs an initial response model representing the nonlinear characteristics of the satellite equipment's payload hardware under different input conditions through the hardware nonlinear characteristics of the satellite equipment, and updates the adjustment coefficient of the initial response model through preset environmental impact parameters to obtain a target correction model, thereby correcting the navigation signal through the target correction model to obtain a correction signal. In this way, the present disclosure performs dual comprehensive modeling of the hardware nonlinear characteristics of the satellite equipment and the nonlinear characteristics of the dynamic environment, so that the target correction model can improve the accuracy and stability of the navigation signal, significantly reduce the interference of the nonlinear characteristics on the navigation signal, thereby adapting to the low-orbit navigation requirements in complex dynamic environments, and providing reliable support for high-dynamic, high-precision navigation applications.

[0033] The following briefly introduces the application scenarios to which the technical solution of the present disclosure can be applied. It should be noted that the application scenarios introduced below are only used to illustrate the present disclosure and are not limited. In the specific implementation process, the technical solution provided by the present disclosure can be flexibly applied according to actual needs.

[0034] Figure 1 1 shows an exemplary communication network 100 in which embodiments of the present disclosure may be implemented. The communication network 100 includes a satellite network device 110 and terminal devices 120A and 120B served by the satellite network device 110. The terminal devices 120A and 120B may also be collectively referred to as terminal devices 120. Figure 1 In the example of , as a satellite communication network, the communication network 100 also includes a ground station 130, a gNB 140, a next generation core network NGC 150 and a data network 160. The satellite communication network may include a low orbit satellite (LEO), a medium orbit satellite (MEO) and a geosynchronous orbit satellite (GEO).

[0035] The ground station 140 acts as a gateway for connecting non-terrestrial networks and public data networks. The gNB 140 acts as an access network, connecting the ground station 130 to the core network NGC 150. The NGC 150 can also be connected to the data network 160 to provide, for example, Internet content services. It will be understood that the communication network 100 is not required to include Figure 1 All elements shown in .

[0036] In some embodiments, the satellite network device 110 can be used as a base station to communicate with the terminal devices 120A and 120B, or as a transparent forwarding node to transparently transmit the signal sent by the ground station 130 to the terminal devices 120A and 120B. In the former case, the satellite network device 110 has all or part of the functions of a base station. For example, the satellite network device 110 can be a gNB or a gNB-DU, and the satellite network device 110 with the gNB function can be with an inter-satellite link ISL or without an inter-satellite link ISL. In the case of a transparent forwarding node, the satellite network device 110 only performs transparent forwarding.

[0037] It should be understood that the number of satellite network devices 110, terminal devices 120A and 120B is for illustration purposes only and is not intended to impose any limitation. Communication network 100 may include any appropriate number of satellite network devices and terminal devices suitable for implementing the embodiments of the present disclosure.

[0038] In the communication network 100, the satellite network device 110 can send navigation signals to the terminal devices 120A and 120B. The terminal devices 120A and 120B correct and optimize the navigation signals based on the navigation signal correction method provided in the embodiment of the present disclosure, and implement subsequent navigation processing through the correction signals, and feedback relevant data and control information to the satellite network device 110.

[0039] The communication in the communication network 100 may conform to any suitable standard, but is not limited to Long Term Evolution (LTE), LTE Evolution, LTE-Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), Code Division Multiple Access (CDMA), and Global System for Mobile Communications (GSM). In addition, the communication may be performed according to any generation of communication protocols currently known or developed in the future. Examples of communication protocols include, but are 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 sixth generation (6G) communication protocols.

[0040] The following describes the navigation signal correction method provided by the exemplary embodiment of the present disclosure in combination with the application scenarios described above and with reference to the accompanying drawings. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principles of the present disclosure, and the embodiments of the present disclosure are not limited in this respect.

[0041] The following describes the data transmission method provided by the exemplary embodiment of the present disclosure in combination with the application scenarios described above and with reference to the accompanying drawings. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principles of the present disclosure, and the embodiments of the present disclosure are not limited in this respect.

[0042] Please refer to Figure 2 , Figure 2 Flowchart showing an exemplary method 200 for navigation signal correction according to some embodiments of the present disclosure. The method 200 may be implemented on a device, such as Figure 1 For the purpose of discussion, reference will be made to the terminal device 120. Figure 1 Method 200 is described. Method 200 may involve Figure 1 Satellite network device 110 and terminal devices 120A and 120B are shown. It should be understood that method 200 may include additional steps not shown and / or may omit some of the steps shown, and the scope of the present disclosure is not limited in this regard.

[0043] Step 201: construct an initial response model of the satellite equipment.

[0044] In the disclosed embodiment, the initial response model represents the nonlinear characteristics of the payload hardware of the satellite device under different input conditions. Thus, the hardware nonlinear characteristics of the satellite device can be fully captured through the initial response model, providing a basis for subsequent signal correction.

[0045] In some embodiments, the present disclosure can model the nonlinear characteristics of the payload hardware of low-orbit satellite equipment, such as the traveling wave tube amplifier, power amplifier and filter hardware of the satellite equipment, so as to construct an initial response model to accurately describe the nonlinear characteristics of each payload hardware in the low-orbit satellite navigation system.

[0046] In some embodiments, the present disclosure may use any model that can accurately capture the nonlinear characteristics of complex hardware such as power amplifiers and filters under different input conditions. For example, Volterra series models, Hammerstein models, Wiener models, and orthogonal polynomial models, etc. Taking the Volterra series model as an example, the Volterra series model can effectively describe the high-order nonlinear characteristics of the system, and is particularly suitable for modeling the nonlinear behavior of complex hardware such as low-orbit satellite payloads.

[0047] In some embodiments, in the Volterra series model, the output signal is the input signal The nonlinear response is usually expressed as a combination of the convolution of the input signal and higher-order terms, as shown below:

[0048] in, is a constant term, which means that when there is no input signal (i.e. ), the static response of the system; is the time delay variable; is a first-order Volterra kernel function, which is used to describe the linear response of the system, that is, the input signal The impact of different delays on output; are independent time-delay variables; It is a second-order Volterra kernel function, which is used to describe the second-order nonlinear response of the system, that is, the influence of the quadratic interaction term of the input signal on the output, that is, the influence of the two different time points of the input signal on the current output.

[0049] is a higher-order kernel function used to describe higher-order nonlinear responses.

[0050] In some embodiments, the present disclosure may determine the kernel function corresponding to the initial response model through the input and output data of each load hardware in combination with a preset kernel function fitting strategy, and construct the initial response model based on the determined kernel function.

[0051] In the disclosed embodiment, in order to accurately obtain the parameters of kernel functions of each order in the initial response model, the specific parameters of the kernel function in the initial response model can be determined according to the input and output data of each payload hardware of the satellite equipment through experimental measurement and kernel function fitting to construct the initial response model.

[0052] In some embodiments, the present disclosure may pre-collect input and output data of each payload hardware of the satellite equipment, including but not limited to traveling wave tube amplifiers, solid-state power amplifiers, filters, etc. The present disclosure may connect the input and output ports of each payload equipment to the navigation signal generator and receiver, respectively, to ensure the comprehensiveness and accuracy of data collection. In this way, through laboratory testing, output data under different input signals (for example, sine waves, linear frequency modulation, multi-frequency signals, etc.) are obtained, so that the collected input and output data cover different power ranges, and the hardware nonlinear characteristics such as gain compression and intermodulation distortion of each payload hardware are analyzed more accurately and comprehensively.

[0053] In some embodiments, in order to fully cover the impact of different low-orbit navigation signals on the nonlinear characteristics of satellite equipment, the present disclosure can collect input signals of different types and amplitudes, including but not limited to sine wave signals, linear frequency modulation signals, multi-frequency sine superposition signals and other input signals, and the amplitude gradually increases from low power to high power, so as to more comprehensively capture the nonlinear gain compression and saturation characteristics of the payload equipment. The specific amplitude range of the signal in the present disclosure can be set according to the equipment specifications, for example, from 0dBm to the maximum output power of the equipment (such as 30dBm or higher), and the present disclosure does not make specific limitations on this.

[0054] In some embodiments, in order to ensure that the amount of collected signal data is sufficient, the present disclosure may continuously collect each input signal for at least 10 minutes, and repeat the collection at different power levels to generate input signals and output signal sets under conditions of different signal types, different input powers, etc., to cover different working conditions. The specific time can be flexibly set according to the actual scene requirements, and the present disclosure does not specifically limit this.

[0055] In some embodiments, the initial response model of the present disclosure may include a first-order kernel function and at least one multi-order kernel function, and the multi-order kernel function may include a second-order kernel function, a third-order kernel function, etc. In order to balance computational efficiency and modeling accuracy, the present disclosure may use first-order and second-order kernel functions to model the initial response model.

[0056] It is worth mentioning that the model in the present disclosure is not limited to first-order and second-order kernel functions, and under specific high-power or more complex nonlinear conditions, it can be extended to third-order kernel functions or even higher-order kernel functions to further improve the model accuracy.

[0057] Next, the kernel function fitting methods of different orders in this disclosure are specifically introduced: For the first-order kernel function , the present disclosure can use the least squares method to linearly fit the convolution term of the input signal with the output data. , the fitting error of the first-order kernel function can be obtained for:

[0058] For the second-order kernel function , the present disclosure can use the double least squares method to fit the second-order interaction term of the input signal. , the fitting error of the second-order kernel function can be obtained for:

[0059] In this way, the present disclosure can minimize the fitting error and , and obtain the first-order kernel function and the second-order kernel function Specific parameters.

[0060] In some embodiments, the third-order kernel function The fitting error As shown below:

[0061] Thus, the present disclosure can be minimized Get the third-order kernel function .

[0062] In summary, the present disclosure fits the input and output data of each payload hardware through the Volterra kernel function, determines the first-order, second-order, and third-order kernel function parameters (for complex nonlinearity in high-power cases), and stores the modeling data, that is, the calculated model parameters are used as a hardware nonlinear model database and stored at the receiving end or the satellite control center.

[0063] In some embodiments, after experimental measurement and kernel function fitting, the present disclosure can establish an initial response model of satellite equipment payload hardware by determining the first-order, second-order, or even third-order Volterra kernel function parameters. In this way, the constructed initial response model reflects the hardware nonlinear characteristics of the satellite equipment, and can accurately and comprehensively describe the nonlinear characteristics of the satellite equipment under various input conditions on the basis of comprehensive consideration of computational efficiency and modeling accuracy, providing a basis for subsequent signal correction and adaptive parameter adjustment.

[0064] In some embodiments, in order to balance computational efficiency and model accuracy, the first response in the present disclosure may first use first-order and second-order kernel functions to construct an initial model, and the initial output of the model obtained by fitting is It can be expressed as: in, represents the static response of the system, represents the first-order Volterra kernel function, Represents the second-order Volterra kernel function.

[0065] Furthermore, in order to further improve the accuracy of the model, the model can be extended to a third-order kernel function according to the actual scenario requirements. The third-order kernel function is particularly suitable for specific high-power or more complex nonlinear conditions, such as third-order intermodulation and saturation effect under high power. The model expression obtained by fitting is:

[0066] in, is the third-order Volterra kernel function.

[0067] Step 202: Based on multiple environmental impact parameters, update the adjustment coefficient of the initial response model to obtain a target correction model.

[0068] In the embodiments of the present disclosure, it is considered that during the operation of the satellite in orbit, the navigation signal will also be affected by a variety of dynamic environmental factors, such as Doppler frequency shift, temperature changes, and frequent satellite switching. These factors will cause the nonlinear characteristics of the payload hardware of the satellite equipment to change, further affecting the stability and accuracy of the navigation signal. Therefore, the present disclosure will introduce environmental impact parameters on the basis of the constructed initial response model reflecting the nonlinear characteristics of the hardware to update the adjustment coefficient of the initial response model. The adjustment coefficient represents the influence of the corresponding environmental impact parameters on the nonlinear characteristics of the model. In this way, the comprehensive modeling of the nonlinear characteristics of the signal for dynamic environmental factors such as Doppler frequency shift, temperature changes, and satellite switching can enable the target correction model to accurately reflect the operating status of the satellite equipment in orbit.

[0069] In some embodiments, the environmental impact parameter in the present disclosure may include at least one of a Doppler impact parameter, a temperature impact parameter, and a signal switching parameter. The Doppler impact parameter represents the impact of the frequency and phase changes of the signal on the nonlinear characteristics of the initial response model; the temperature impact parameter represents the impact of the temperature change on the nonlinear characteristics of the initial response model; and the signal switching parameter represents the impact of the signal mutation amount generated during the signal switching process on the nonlinear characteristics.

[0070] In some embodiments, the initial response model in the present disclosure may include a first-order kernel function and one or more multi-order functions. Among them, the first-order kernel function corresponds to a first-order adjustment coefficient, and each multi-order function corresponds to a multi-order adjustment coefficient, for example, the second-order kernel function corresponds to the second-order adjustment coefficient, the third-order kernel function corresponds to the third-order adjustment coefficient, and the higher-order kernel function corresponds to the higher-order adjustment coefficient. In this way, by updating the adjustment coefficients of the kernel functions of each order through the environmental impact parameters, the influence of dynamic environmental factors such as Doppler frequency shift, temperature change and satellite switching on the nonlinear characteristics of the signal can be introduced into the model, so as to realize the comprehensive modeling of the nonlinear characteristics of the signal.

[0071] In some embodiments, when the environmental impact parameter includes a Doppler impact parameter, the present disclosure can update the frequency shift part coefficient in the first-order adjustment coefficient by the Doppler impact parameter. The frequency domain part coefficient is an item of the first-order adjustment coefficient, so that the Doppler frequency shift can be modeled.

[0072] In some embodiments, considering that the navigation signal will be affected by the Doppler effect at the receiving end due to the high-speed operation of the satellite, thereby affecting the decoding accuracy of the navigation signal. Therefore, the present disclosure will determine the Doppler effect parameter based on the influence of the Doppler effect, combined with the satellite relative speed and the signal center frequency. , that is, the influence of the Doppler effect on the kernel function of the initial response model, which can be expressed as:

[0073] in, represents the speed of light, Represents the center frequency of the navigation signal; Represents the relative speed between the satellite and the receiver.

[0074] Furthermore, since the Doppler effect mainly affects the frequency and phase changes of the signal, adjusting the adjustment coefficient of the first-order kernel function is sufficient to capture its main effect. In this way, the present disclosure integrates the influence of the Doppler effect on the kernel function into the first-order adjustment coefficient An item in , as follows:

[0075] In some embodiments, due to the large temperature difference of the satellite in-orbit environment, the temperature of the satellite equipment's payload hardware will change dramatically with factors such as sunlight and earth shadow, thereby affecting the nonlinear characteristics of the satellite equipment, such as the gain of the amplifier and the center frequency of the filter. Therefore, when the environmental influencing parameters include temperature influencing parameters, the present disclosure can determine the influence of the temperature influencing parameters on the kernel function of the initial response model according to the influence of temperature changes on the nonlinear characteristics, thereby determining the temperature partial coefficients corresponding to the first-order adjustment coefficient and each multi-order adjustment coefficient.

[0076] In some embodiments, the present disclosure takes into account that the temperature-affected parameter mainly has a greater impact on the nonlinear response of the second-order and third-order kernel functions, and may also have a certain impact on the first-order kernel function. Therefore, the present disclosure integrates the impact of the temperature-affected parameter on the nonlinear characteristics into the multi-section adjustment coefficient , , The expression is as follows: The temperature effect on the first-order kernel function can be expressed as:

[0077] The temperature effect on the second-order kernel function can be expressed as:

[0078] The temperature effect on the third-order kernel function can be expressed as:

[0079] in, is the current temperature, which can be collected by the on-board temperature sensor. is the reference temperature.

[0080] They are the sensitivity coefficients of the temperature-affected parameters to the first-order, second-order, and third-order kernel functions, respectively, and are used to correct the nonlinear parameter drift caused by temperature.

[0081] In some embodiments, due to the low altitude and small coverage area of ​​low-orbit satellites, the receiver needs to frequently switch between different satellite signals. Signal mutations may occur during the switching process, resulting in instantaneous nonlinear distortion. Therefore, when the environmental impact parameters include signal switching parameters, the present disclosure can determine the first-order adjustment coefficient and the signal part coefficients corresponding to each multi-order adjustment coefficient through the signal switching parameters, thereby introducing the signal mutations generated during the signal switching process into the adjustment coefficient of the kernel function.

[0082] In some embodiments, the effect of the signal switching parameter on the first-order kernel function can be expressed as;

[0083] The effect of signal switching parameters on the second-order kernel function can be expressed as;

[0084] in: are the switching sensitivity coefficients of the first-order and second-order kernel functions, respectively.

[0085] In some embodiments, after determining the frequency shift part coefficient, temperature part coefficient and signal part coefficient of each order adjustment coefficient, the present disclosure will update the first-order kernel function and each multi-order kernel function of the initial response model respectively to obtain the target correction model, thereby realizing comprehensive modeling of the nonlinear impact of the navigation signal.

[0086] In some embodiments, after using the Volterra model to describe the nonlinear distortion introduced by the hardware to construct the initial response model, the present disclosure will further consider dynamic environmental factors such as Doppler frequency shift, temperature change, and satellite switching, and express them by adjusting the adjustment coefficient of the Volterra kernel function to achieve comprehensive modeling of the nonlinear impact of the navigation signal, thereby affecting the nonlinear response of the entire system. After integrating the impact of Doppler frequency shift, temperature change, and satellite switching, the comprehensive nonlinear impact modeling formula is as follows:

[0087]

[0088]

[0089]

[0090] in, Represents the first-order adjustment coefficient, which integrates the effects of Doppler shift, temperature change and satellite switching on the nonlinear characteristics of satellite equipment.

[0091] Represents the second-order adjustment coefficient, which combines the effects of temperature change and satellite switching: is a third-order adjustment factor that only includes the effects of temperature changes.

[0092] Step 203: Based on the target correction model, the navigation signal is corrected to obtain a corrected signal.

[0093] In the embodiment of the present disclosure, the receiving end receives the navigation signal actually transmitted by the satellite during the period of being in orbit, and the navigation signal contains the influence of the nonlinear characteristics of the hardware and the real dynamic environment influence (such as Doppler frequency shift, temperature change and satellite switching, etc.). Therefore, in order to ensure the accuracy of the signal, the present disclosure will correct the navigation signal through the target correction model to obtain the correction signal, and realize the real-time compensation of the nonlinear distortion of the signal.

[0094] In some embodiments, after receiving the navigation signal, the present invention can convert the loaded signal data into a baseband signal to remove the influence of the carrier frequency and retain the characteristics of the signal such as amplitude and phase, so that the model can adaptively and accurately capture the nonlinear changes of the signal in different environments and states, thereby automatically adjusting the model parameters according to dynamic environmental changes to compensate for signal distortion in real time and ensure the accuracy of the signal.

[0095] In some embodiments, after obtaining the target correction model reflecting the comprehensive nonlinear characteristics, the present disclosure can adjust the coefficients , , Implement adaptive correction to obtain the compensation output of the signal, that is, the correction signal , as shown below:

[0096] Represents the baseband signal after real-time compensation. In this way, the target correction model can achieve effective correction of the navigation signal.

[0097] In one possible implementation, in order to further enhance the adaptability of the target correction model, the present disclosure also designs a feedback mechanism, which can adaptively update the adjustment coefficient of the model according to the error between the preset ideal signal and the correction signal, thereby updating the target correction model, so that the target correction model can adapt to the rapidly changing signal characteristics of the low-orbit satellite while in orbit.

[0098] In some embodiments, the present disclosure may calculate the correction signal output by the target correction model at each time t. With the ideal signal The real-time error between , as shown below:

[0099] Among them, the ideal signal It is a signal without hardware distortion and environmental interference, derived through signal simulation or based on known standards under specific environmental conditions. This ideal signal can be obtained by the ground control center through simulation, laboratory measurement, etc.

[0100] Next, using the real-time error , the present disclosure can dynamically update the adjustment coefficient , , , ensuring that the parameters of the target correction model are adaptively adjusted as the environment changes.

[0101] In some embodiments, the present disclosure may use a least mean square algorithm, that is, by minimizing the sum of squared errors, to adaptively adjust the model parameters, as shown below:

[0102] in, represents the learning rate, which may be 10e-3 to 10e-2, and is not specifically limited in the present embodiment.

[0103] In this way, by real-time adjustment and optimization of the adjustment coefficient through error feedback, the target correction model can be adaptive to current environmental changes, further improving the efficiency and accuracy of signal correction.

[0104] In some embodiments, considering that the error may accumulate over time during the long-term operation of the satellite, in order to further improve the accuracy of signal correction and the stability of the long-term operation of the model, the present invention can continuously monitor the error after signal correction, and automatically trigger the adaptive adjustment algorithm when it is determined that the error exceeds the preset threshold for a long time, so as to speed up the update frequency of the model parameters. At the same time, with the support of the ground control center, calibration signals can be sent regularly to verify the accuracy of the on-orbit model. By comparing the errors before and after the correction of the calibration signal, the parameter accuracy of the model is evaluated. If the calibration error is large, the model is recalibrated and optimized through the feedback mechanism.

[0105] In some embodiments, reference Figure 3 FIG. 3 is a process diagram of another navigation signal correction method 300 provided by the present disclosure. Figure 3In the first phase, the first, second and third order Volterra kernel function models are used to realize hardware nonlinear modeling, so as to fully capture the nonlinear characteristics of the satellite equipment's payload hardware and establish an initial response model at the device level. Next, dynamic environmental nonlinear modeling is carried out, focusing on analyzing the time-varying effects of dynamic environmental factors such as Doppler frequency shift, temperature change and satellite switching on the transmission of navigation signals, and realizing comprehensive modeling of signal nonlinear characteristics. Based on the modeling of the first two stages, the coupling analysis of hardware characteristics and environmental disturbances is realized through the comprehensive modeling of nonlinear effects, and a target correction model is constructed. When receiving satellite on-orbit signals, adaptive correction of navigation signals is performed based on the established target correction model to improve the accuracy of navigation signals. At the same time, the error feedback mechanism is used to continuously optimize the model parameters. The minimum mean square error algorithm and dynamic learning rate optimization are used to correct the signal output in real time to ensure the high accuracy and stability of the navigation signal, thus forming a complete signal processing closed loop covering equipment hardware characteristics, environmental dynamic changes and real-time feedback correction.

[0106] It is worth mentioning that flow charts are used in the present disclosure to illustrate the operations performed by the system according to the embodiments of the present disclosure. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, various steps may be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0107] The basic concepts have been described above. Obviously, for those skilled in the art, the above application disclosure is only an example and does not constitute a limitation of the present disclosure. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements and corrections to the present disclosure. Such modifications, improvements and corrections are suggested in the present disclosure, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of the present disclosure.

[0108] At the same time, the present disclosure uses specific words to describe the embodiments of the present disclosure. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present disclosure. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different locations in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of the present disclosure may be appropriately combined.

[0109] Figure 44 is a simplified block diagram of a device 400 suitable for implementing an embodiment of the present disclosure. For example, the terminal device 120 can be implemented by the device 400. As shown in the figure, the device 400 includes one or more processors 410, one or more memories 420 coupled to the processor 410, and one or more communication modules 440 coupled to the processor 410.

[0110] The communication module 440 is used for two-way communication. The communication module 440 has at least one antenna to facilitate communication. The communication interface may represent any interface necessary for communicating with other network elements.

[0111] Processor 410 may be of any type suitable for the local technology network, and may include, as non-limiting examples, one or more of: a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), and a processor based on a multi-core processor architecture. Device 400 may have multiple processors, such as application specific integrated circuit chips, which are driven in time to a clock that synchronizes a master processor.

[0112] The memory 420 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) 424, electrically programmable read-only memory (EPROM), flash memory, hard disk, compact disk (CD), digital video disk (DVD), and other magnetic and / or optical memories. Examples of volatile memories include, but are not limited to, random access memory (RAM) 422 and other volatile memories that do not persist during the duration of a power outage.

[0113] Computer program 430 includes computer executable instructions that are executed by associated processor 410. Program 430 may be stored in ROM 424. Processor 410 may perform any appropriate actions and processes by loading program 430 into RAM 422.

[0114] The embodiments of the present disclosure may be implemented by a program 430, so that the device 400 may execute the reference Figure 2 and Figure 3 Any process of the disclosure discussed. The embodiments of the present disclosure may also be implemented by hardware or by a combination of software and hardware.

[0115] In some embodiments, program 430 may be tangibly contained in a computer-readable medium, which may be contained in device 400 (e.g., memory 420) or other storage devices accessible to device 400. Device 400 may load program 430 from the computer-readable medium to RAM 422 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. The computer-readable medium has program 430 stored thereon.

[0116] Generally, various embodiments of the present disclosure may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. Certain aspects may be implemented in hardware, while other aspects may be implemented in firmware or software, which may be executed by a controller, microprocessor, or other computer device. Although various aspects of the embodiments of the present disclosure are shown and described as block diagrams, flow charts, or using some 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 circuits or logic, general hardware or controllers or other computer devices, or some combination thereof.

[0117] The present 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 program modules, which are executed in a device on a target real or virtual processor to perform the above-mentioned reference Figure 2 The method 200 and / or the above reference Figure 3 The method 300 described. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules can be combined or separated between program modules as needed. Machine executable instructions for program modules can be executed in local or distributed devices. In distributed devices, program modules can be located in local and remote storage media.

[0118] The program code for executing the disclosed method can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing equipment so that when the program code is executed by the processor or controller, the function / operation specified in the flow chart and / or block diagram is realized. The program code can be executed completely on the machine as an independent software package, partially on the machine, partially on the machine, partially on a remote machine, partially on a remote machine, or all on a remote machine or server.

[0119] In the context of the present disclosure, computer program codes or related data may be carried by any appropriate carrier to enable a device, apparatus or processor to perform various processes and operations as described above. Examples of carriers include signals, computer readable media, etc.

[0120] The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or apparatuses, or any suitable combination of the foregoing. More specific examples of computer readable storage media include an electrical connection having one or more conductors, a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0121] In addition, although the operations are described in a specific order, this should not be understood as requiring the specific order or sequence shown to be performed, or performing all the operations shown, to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these details should not be interpreted as limitations on the scope of the present disclosure, but can be interpreted as descriptions of features specific to a particular embodiment. Certain features described in the context of a separate embodiment may also be implemented in combination in a single embodiment. On the contrary, the various features described in the context of a single embodiment may also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0122] Although the disclosure has been described in language specific to structural features and / or methodological acts, it should be understood that the disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

[0123] It should be fully understood that the use of personally identifiable information should be subject to privacy policies and practices generally recognized as meeting or exceeding industry or government requirements for maintaining user privacy. In particular, personally identifiable information data should be managed and processed to minimize the risk of inadvertent or unauthorized access or use, and the nature of authorized use should be clearly indicated to users.

Claims

1. A navigation signal correction method, characterized in that: The method comprises: Constructing an initial response model of a satellite device, wherein the initial response model represents the nonlinear characteristics of the payload hardware of the satellite device under different input conditions; Based on preset environmental impact parameters, updating the adjustment coefficient of the initial response model to obtain a target correction model; the adjustment coefficient represents the influence of the environmental impact parameter on the nonlinear characteristic; Based on the target correction model, the navigation signal is corrected to obtain a correction signal.

2. The method according to claim 1, characterized in that The constructing of the initial response model of the satellite equipment includes: Based on the input and output data of the load hardware and in combination with a preset kernel function fitting strategy, determine the kernel function of the initial response model; Based on the kernel function, the initial response model is constructed.

3. The method according to claim 1, characterized in that The initial response model includes a first-order kernel function and at least one multi-order kernel function, the first-order kernel function corresponds to a first-order adjustment coefficient, and each multi-order function corresponds to a multi-order adjustment coefficient.

4. The method according to claim 3, characterized in that When the environmental impact parameter includes a Doppler impact parameter, and the Doppler impact parameter characterizes the impact of frequency and phase changes of the navigation signal on the nonlinear characteristics of the initial response model, updating the adjustment coefficient of the initial response model based on the preset environmental impact parameter includes: Based on the Doppler influence parameter, the frequency shift part coefficient corresponding to the first-order adjustment coefficient is updated; the Doppler influence parameter is determined based on the satellite relative speed and the signal center frequency.

5. The method according to claim 3, characterized in that When the environmental impact parameter includes a temperature impact parameter, and the temperature impact parameter represents the influence of temperature change on the nonlinear characteristic, the updating of the adjustment coefficient of the initial response model based on the preset environmental impact parameter further includes: Based on the temperature influence parameter, the temperature partial coefficients corresponding to the first-order adjustment coefficient and each multi-order adjustment coefficient are updated respectively; the temperature influence parameter is determined based on the difference between the current temperature and the reference temperature.

6. The method according to claim 3, characterized in that When the environmental impact parameter includes a signal switching parameter, and the signal switching parameter represents the influence of the signal mutation amount on the nonlinear characteristic, the updating of the adjustment coefficient of the initial response model based on the preset environmental impact parameter further includes: Based on the signal switching parameter, the first-order adjustment coefficient and the signal part coefficients corresponding to each of the multi-order adjustment coefficients are updated respectively; the signal switching parameter is determined based on the signal mutation amount generated during the signal switching process.

7. The method according to claim 1, characterized in that After outputting the correction signal, the method further includes: Adaptively updating the adjustment coefficient based on an error between a preset ideal signal and the correction signal; The target correction model is updated based on the updated adjustment coefficient.

8. A navigation signal correction device, comprising: Apparatus for carrying out the method according to any one of claims 1-7.

9. A computer device, characterized in that: include: at least one processor; as well as At least one memory storing instructions thereon, which, when executed individually or collectively by the at least one processor, cause the computer device to perform the method according to any one of claims 1 to 7.

10. A computer storage medium storing instructions, characterized in that: When the instructions are executed individually or collectively by at least one processor of a computer device, the computer device is caused to perform the method according to any one of claims 1 to 7.

11. A computer program product comprising instructions, characterized in that When the instructions are executed individually or collectively by at least one processor of a computer device, the computer device is caused to perform the method according to any one of claims 1 to 7.

12. A chip system for a computer device, characterized in that: The chip system includes at least one processor, and the at least one processor is configured to execute instructions stored in at least one memory of the computer device individually or collectively, so that the computer device performs the method according to any one of claims 1 to 7.

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