A positioning method and device based on a static and dynamic adaptive single-point positioning model

Abstract

The embodiment of the application discloses a positioning method and device based on a static and dynamic adaptive single-point positioning model, comprising: obtaining a to-be-positioned object and epoch inter-carrier phase difference TDCP observation value of the to-be-positioned object; determining the motion state and position initial value of the to-be-positioned object at the current epoch according to the TDCP observation value, and determining a parameter time evolution model according to the motion state; constructing a state equation according to the parameter time evolution model and the position initial value, and constructing an observation equation according to the position initial value; correcting the position initial value according to the state equation and the observation equation, and obtaining the actual position of the to-be-positioned object at the current epoch, thereby improving the positioning precision and efficiency of the to-be-positioned object.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation and positioning technology, and in particular to a positioning method and apparatus based on a static and dynamic adaptive single-point positioning model. Background Technology

[0002] The BeiDou-3 satellite navigation system officially began providing navigation and positioning services in 2020. One of its core features is the Precise Point Positioning (PPP) enhancement signal based on the B2b frequency band, which provides real-time, decimeter-level service to various regions. Furthermore, the satellite-based Precise Point Positioning (PPP) service offered by this system completely eliminates reliance on terrestrial communication networks and reference stations.

[0003] Based on the aforementioned satellite-based PPP service, navigation and positioning terminals only need a single receiver to achieve precise positioning services at any location. This advantage can effectively expand the BeiDou high-precision positioning service methods and make up for the limited coverage of ground-based real-time kinematic (RTK) related services, providing new technical means for achieving precise navigation and positioning.

[0004] However, although satellite-based B2b-PPP positioning has significant advantages in positioning modes, the initial position value of the object to be positioned is usually calculated through single point positioning (SPP) technology, which results in low accuracy of the determined initial position value, thus affecting the accuracy and efficiency of precise positioning of the object to be positioned. Summary of the Invention

[0005] This invention provides a positioning method and apparatus based on a static and dynamic adaptive single-point positioning model, which solves the problem that the initial position value calculated by SPP technology has poor accuracy, thus affecting the accuracy and efficiency of positioning the object to be positioned, and improves the accuracy and efficiency of positioning the object to be positioned.

[0006] In a first aspect, embodiments of the present invention provide a positioning method based on a static-dynamic adaptive single-point positioning model, comprising: acquiring the object to be positioned and the epoch-time differential carrier phase (TDCP) observations of the object to be positioned; determining the motion state and initial position of the object to be positioned at the current epoch based on the TDCP observations, and determining a parametric time evolution model based on the motion state; constructing a state equation based on the parametric time evolution model and the initial position, and constructing an observation equation based on the initial position; and correcting the initial position based on the state equation and the observation equation to obtain the actual position of the object to be positioned at the current epoch.

[0007] Secondly, embodiments of the present invention also provide a positioning device based on a static-dynamic adaptive single-point positioning model, comprising: an observation value acquisition module for acquiring the object to be positioned and its TDCP observation values; an evolution model determination module for determining the motion state and initial position value of the object to be positioned in the current epoch based on the TDCP observation values, and determining a parametric time evolution model based on the motion state; a solution equation construction module for constructing a state equation based on the parametric time evolution model and the initial position value, and constructing an observation equation based on the initial position value; and an actual position determination module for correcting the initial position value based on the state equation and the observation equation to obtain the actual position of the object to be positioned in the current epoch.

[0008] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to execute the positioning method based on the static and dynamic adaptive single-point positioning model provided in any embodiment of the present invention.

[0009] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute and implement the positioning method based on a static and dynamic adaptive single-point positioning model provided in any embodiment of the present invention.

[0010] Fifthly, embodiments of the present invention also provide a computer program product, which includes a computer program that, when executed by a processor, implements the positioning method based on a static and dynamic adaptive single-point positioning model provided in any embodiment of the present invention.

[0011] The technical solution of this invention determines the motion state and initial position of the object to be located in the current epoch by using TDCP observations, and determines the parametric time evolution model based on the motion state; constructs a state equation based on the parametric time evolution model and the initial position, and constructs an observation equation based on the initial position; and corrects the initial position based on the state equation and the observation equation to obtain the actual position of the object to be located in the current epoch. This solves the problem that the initial position value calculated by SPP technology has poor accuracy, which affects the accuracy and efficiency of locating the object to be located, and improves the accuracy and efficiency of locating the object to be located.

[0012] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart of a positioning method based on a static and dynamic adaptive single-point positioning model provided in Embodiment 1 of the present invention.

[0015] Figure 2 This is a flowchart of another positioning method based on a static and dynamic adaptive single-point positioning model provided in Embodiment 2 of the present invention.

[0016] Figure 3 This is a flowchart of a preferred positioning method based on a static and dynamic adaptive single-point positioning model provided by an embodiment of the present invention.

[0017] Figure 4 This is a schematic diagram of a positioning device based on a static and dynamic adaptive single-point positioning model according to Embodiment 3 of the present invention.

[0018] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention.

[0019] Reference numerals: Electronic device 10; Processor 11; Read-only memory 12; Random access memory 13; Bus 14; Input / output interface 15; Input unit 16; Output unit 17; Storage unit 18; Communication unit 19. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] Example 1

[0023] Figure 1 This is a flowchart of a positioning method based on a static-dynamic adaptive single-point positioning model according to Embodiment 1 of the present invention. This embodiment is applicable to the situation of positioning an object to be positioned. The method can be executed by a positioning device based on a static-dynamic adaptive single-point positioning model. The positioning device based on a static-dynamic adaptive single-point positioning model can be implemented in hardware and / or software and can be configured in an electronic device.

[0024] like Figure 1 As shown, this embodiment discloses a positioning method based on a static and dynamic adaptive single-point positioning model, including steps S110-S140.

[0025] S110. Obtain the object to be located, and the TDCP observation value of the object to be located.

[0026] In this embodiment, the object to be located can be understood as an object that needs to be located using satellite positioning technology, such as ships and vehicles.

[0027] In this step, specifically, you can either acquire only the current TDCP observations of the object to be located, or you can acquire both the current and historical TDCP observations simultaneously. The current TDCP observation can be understood as the value obtained by performing a difference operation on the carrier phase observations of the current epoch and the target historical epoch. The historical TDCP observation can be understood as the value obtained by performing a difference operation on the carrier phase observations of the target historical epoch and the preceding historical epoch. The target historical epoch is the historical epoch that is earlier than the current epoch and has the smallest time interval between them. The preceding historical epoch is the historical epoch that is earlier than the target historical epoch and has the smallest time interval between them.

[0028] S120. Based on the TDCP observations, determine the motion state and initial position of the object to be located in the current epoch, and determine the parameter time evolution model based on the motion state.

[0029] In this embodiment, the motion state can include both motion and stillness. The parametric time evolution model can include a white noise model and a constant model.

[0030] In this step, specifically, the initial position of the object to be located in the current epoch can be determined based on the current TDCP observation value and the time interval between adjacent epochs corresponding to the current TDCP observation value.

[0031] Based on at least one TDCP observation, the instantaneous velocity of the object to be located is determined at multiple consecutive epochs, and the motion state of the object at the current epoch is determined based on each instantaneous velocity. Then, a predefined white noise model or a constant model can be used as the parametric time evolution model according to the motion state.

[0032] S130. Based on the parameter time evolution model and the initial position value, construct the state equation and the observation equation based on the initial position value.

[0033] In this step, specifically, an initial state equation can be constructed based on the parametric time evolution model, and the initial position values ​​can be substituted into the initial state equation for validity verification. Then, based on the verification results, the state transition matrix and / or process noise covariance matrix in the initial state equation can be corrected to obtain the final state equation.

[0034] The initial position value can be used as a linearization reference point, and an observation equation can be constructed by combining the satellite observation data and satellite ephemeris information corresponding to the object to be located.

[0035] For example, based on the parametric time evolution model and the initial position values, the following state equation can be constructed:

[0036] .

[0037] in, Represents satellite observation data, This represents the preset design matrix. Indicates the actual location. Represents the observation noise vector. This represents the covariance matrix of the observed values.

[0038] Based on the initial position values, the following observation equation is constructed:

[0039] .

[0040] in, Indicates the actual location. Indicates the initial position value. Represents the state transition matrix. Represents a dynamic noise vector. This represents the process noise covariance matrix.

[0041] S140. Based on the state equation and observation equation, the initial position value is corrected to obtain the actual position of the object to be located in the current epoch.

[0042] In this step, specifically, the initial position value can be used as the starting point for the solution, and substituted into the state equation and observation equation for iterative solution to obtain the actual position of the object to be located in the current epoch.

[0043] The technical solution of this embodiment obtains the object to be located and the inter-epoch carrier phase differential (TDCP) observation values ​​of the object; determines the motion state and initial position of the object in the current epoch based on the TDCP observation values, and determines the parametric time evolution model based on the motion state; constructs a state equation based on the parametric time evolution model and the initial position value, and constructs an observation equation based on the initial position value; and corrects the initial position value based on the state equation and the observation equation to obtain the actual position of the object in the current epoch. This solves the problem that the initial position value calculated by SPP technology has poor accuracy, which affects the accuracy and efficiency of locating the object, and improves the accuracy and efficiency of locating the object.

[0044] Example 2

[0045] Figure 2 This is a flowchart of another positioning method based on a static and dynamic adaptive single-point positioning model according to Embodiment 2 of the present invention. This embodiment is a further optimization and extension of the above embodiments and can be combined with various optional technical solutions in the above embodiments.

[0046] like Figure 2As shown in the figure, this embodiment discloses a positioning method based on a static and dynamic adaptive single-point positioning model, including steps S210-S260.

[0047] S210. Obtain the object to be located, as well as the current TDCP observation and historical TDCP observation of the object to be located.

[0048] S220. Based on the current TDCP observations and historical TDCP observations, determine the instantaneous motion velocity of the object to be located in multiple consecutive epochs, and based on each instantaneous motion velocity, determine the motion state of the object to be located in the current epoch.

[0049] In this step, specifically, the instantaneous velocity of the object to be located at multiple consecutive epochs can be determined based on the current TDCP observation, historical TDCP observation, the first time interval between adjacent epochs corresponding to the current TDCP observation, and the second time interval between adjacent epochs corresponding to historical TDCP observation. Then, the motion state of the object to be located at the current epoch can be determined based on the comparison results of each instantaneous velocity with a set velocity threshold.

[0050] Optionally, based on the current TDCP observation, historical TDCP observation, a first time interval between adjacent epochs corresponding to the current TDCP observation, and a second time interval between adjacent epochs corresponding to the historical TDCP observation, the instantaneous motion velocity of the object to be located at multiple consecutive epochs is determined, including: acquiring the current epoch and the target historical epoch corresponding to the current TDCP observation, and determining the first time interval between the current epoch and the target historical epoch; wherein, the target historical epoch is the historical epoch earlier than the current epoch and with the smallest time interval between the current epoch; determining the instantaneous motion velocity of the object to be located at the current epoch and the target historical epoch based on the current TDCP observation and the first time interval; acquiring the target historical epoch and the preceding historical epoch corresponding to the historical TDCP observation, and determining the second time interval between the target historical epoch and the preceding historical epoch; wherein, the preceding historical epoch is the historical epoch earlier than the target historical epoch and with the smallest time interval between the target historical epoch; and determining the instantaneous motion velocity of the object to be located at the preceding historical epoch based on the historical TDCP observation and the second time interval.

[0051] Specifically, the current distance change corresponding to the current TDCP observation can be determined, and the instantaneous velocity of the object to be located at the current epoch and the target historical epoch can be obtained by dividing the current distance change by the first time interval. Similarly, the historical distance change corresponding to the historical TDCP observation can be determined, and the historical distance change by the second time interval can be obtained by dividing the historical distance change by the second time interval to obtain the instantaneous velocity of the object to be located at the previous historical epoch.

[0052] Optionally, based on the comparison results between each instantaneous motion velocity and the set velocity threshold, the motion state of the object to be located in the current epoch is determined, including: determining whether each instantaneous motion velocity is greater than the set velocity threshold; if so, the motion state of the object to be located in the current epoch is determined to be motion; if not, the motion state of the object to be located in the current epoch is determined to be stationary.

[0053] The speed threshold can be set based on historical experience and user needs. For example, the speed threshold can be set to 0.3 meters per second.

[0054] Specifically, when the instantaneous velocity of the object to be located is greater than a set velocity threshold, the motion state of the object in the current epoch is determined to be moving. When the instantaneous velocity is less than or equal to the set velocity threshold, the motion state of the object in the current epoch is determined to be stationary.

[0055] By using the above settings, we can avoid the situation where the motion state of the object to be located is determined based solely on the instantaneous motion velocity in a single epoch, which would lead to inaccurate determination of the motion state. This improves the accuracy of motion state determination and thus optimizes the positioning accuracy of the object to be located.

[0056] S230. Based on the current TDCP observations, determine the initial position of the object to be located in the current epoch.

[0057] Optionally, based on the current TDCP observations, determine the initial position of the object to be located at the current epoch, including: determining the change in position of the object to be located between the current epoch and the target historical epoch based on the current TDCP observations; wherein, the target historical epoch is the historical epoch earlier than the current epoch and with the smallest time interval between the two epochs; and determining the initial position of the object to be located at the current epoch based on the change in position and the historical position value of the object to be located at the target historical epoch.

[0058] Specifically, the position change of the target object between the current epoch and the target's historical epochs can be determined based on the unit direction vector from the positioning satellite to the target object, the epoch-time variation of the target object's clock bias, the observation noise after epoch-time differentiation, and the current TDCP observation value. Then, the historical position value and the position change can be added together to obtain the initial position value of the target object at the current epoch.

[0059] For example, the following raw phase observation equations for a Global Navigation Satellite System (GNSS) can be obtained:

[0060] .

[0061] in, This represents the current TDCP observation value. This represents the unit direction vector from the positioning satellite to the object to be positioned. Represents the position vector of the object to be located. Indicates the clock difference of the object to be located. Indicates the clock bias of positioning satellites, This indicates the hardware latency of the object to be located. This indicates the hardware latency of the positioning satellite. Indicates the ionospheric tilt factor. Indicates zenith tropospheric delay, Indicates ionospheric delay, Indicates carrier phase integer ambiguity. This represents carrier phase observation noise.

[0062] Then, since the atmospheric error is less than 5 seconds between epochs, the atmospheric error is also... , and and ambiguity, that is The changes in positioning satellite clock bias and hardware delay are negligible over short periods. Therefore, if atmospheric disturbances, cycle slips, and gross errors are disregarded, the original GNSS phase observation equation can be optimized into the following TDCP observation equation:

[0063] .

[0064] in, This represents the current TDCP observation value. This represents the unit direction vector from the positioning satellite to the object to be positioned. This represents the change in position of the object to be located between the current epoch and the target historical epoch. This represents the epochal change in the clock bias of the object to be located. This represents the observation noise after interepochal differencing.

[0065] Then, the least squares algorithm can be used to solve the above TDCP observation equations to obtain the positional change of the target object between the current epoch and the target historical epoch. .

[0066] Finally, the initial position of the object to be located in the current epoch can be determined using the following specific calculation formula:

[0067] .

[0068] in, This represents the initial position of the object to be located in the current epoch. This represents the historical position value of the object to be located within the target historical epoch. This represents the change in position.

[0069] The advantage of this setup is that, compared to existing technologies that calculate initial position values ​​using SPP technology, the solution in this embodiment determines the position change based on current TDCP observations and calculates the initial position value based on the position change and historical position values, resulting in a more accurate initial position value. Furthermore, since a more accurate initial position value leads to higher convergence speed and calculation accuracy in dynamic calculations, this embodiment achieves higher efficiency and accuracy in locating the target object.

[0070] S240. Determine the parameter time evolution model based on the motion state.

[0071] Specifically, in this step, when the motion state is in motion, a predefined white noise model can be used as the parametric time evolution model to maintain sensitivity to the motion trajectory and tracking capability. When the motion state is stationary, a predefined constant model can be used as the parametric time evolution model to reduce unnecessary state changes, accelerate the localization convergence speed in static scenes, and improve stability.

[0072] Among them, the white noise model, by setting a large process noise variance, characterizes the independent variation characteristics between parameter epochs, adapting to the evolution law of dynamic parameters. It is often used to estimate dynamic parameters such as dynamic coordinates and clock errors. The constant model, by assigning a large initial noise in the first epoch and setting the noise to tend to 0 from the second epoch, characterizes the strong correlation and numerical stability between parameter epochs, adapting to the estimation needs of static parameters.

[0073] S250. Based on the parameter time evolution model and the initial position value, construct the state equation and the observation equation based on the initial position value.

[0074] S260. Based on the state equation and observation equation, the initial position value is corrected to obtain the actual position of the object to be located in the current epoch.

[0075] The technical solution of this embodiment obtains the current and historical TDCP observation values ​​of the object to be located; determines the instantaneous motion velocity of the object at multiple consecutive epochs based on the current and historical TDCP observation values, and determines the motion state of the object at the current epoch based on each instantaneous motion velocity; determines the initial position value of the object at the current epoch based on the current TDCP observation value; determines the parameter time evolution model based on the motion state; constructs a state equation based on the parameter time evolution model and the initial position value; constructs an observation equation based on the initial position value; and corrects the initial position value based on the state equation and the observation equation to obtain the actual position of the object at the current epoch. This technical means allows different solution equations to be used to solve the initial position value when the object is in different motion states, thereby improving the positioning accuracy in moving scenes and the positioning efficiency in stationary scenes.

[0076] It should be noted that during the location positioning process, the execution order of the above operations S220, S230 and S240 can be interchanged. For example, the motion state, initial position value and parameter time evolution model can be determined in sequence, or the motion state, parameter time evolution model and initial position value can be determined in sequence, or the initial position value, motion state and parameter time evolution model can be determined in sequence. This embodiment does not impose any restrictions on this.

[0077] In a preferred embodiment, such as Figure 3 As shown, the object to be located, along with its current and historical TDCP observations, can be obtained. Then, based on the current TDCP observations, the initial position of the object in the current epoch can be determined. Based on the current and historical TDCP observations, the instantaneous velocity of the object in multiple consecutive epochs can be determined. Afterward, it can be determined whether each instantaneous velocity is greater than a set velocity threshold. If so, the object's motion state in the current epoch is determined to be moving; otherwise, it is determined to be stationary.

[0078] Finally, when the motion state is in motion, a predefined white noise model can be used as the parametric time evolution model. Then, based on the white noise model and initial position values, state equations can be constructed, and observation equations can be constructed based on the initial position values. When the motion state is stationary, a predefined constant model can be used as the parametric time evolution model. Then, based on the constant model and initial position values, state equations can be constructed, and observation equations can be constructed based on the initial position values.

[0079] After constructing the state equation and observation equation, the initial position value can be corrected based on the state equation and observation equation to obtain the actual position of the object to be located in the current epoch.

[0080] The advantages of this setup are twofold: First, determining the initial position value using TDCP observations improves the accuracy of this determination, thereby enhancing the efficiency and accuracy of precise positioning of the object. Second, determining the motion state using TDCP observations and constructing solution equations based on this motion state allows for flexible adjustments to the position estimation method, thus improving positioning efficiency and accuracy in different scenarios.

[0081] Example 3

[0082] Figure 4 This is a schematic diagram of a positioning device based on a static and dynamic adaptive single-point positioning model according to Embodiment 3 of the present invention. This embodiment can be applied to the situation of positioning an object to be positioned. The positioning device based on the static and dynamic adaptive single-point positioning model can be implemented in hardware and / or software and can be configured in an electronic device.

[0083] like Figure 4 As shown, the positioning device based on the static and dynamic adaptive single-point positioning model disclosed in this embodiment includes: an observation value acquisition module 41, an evolution model determination module 42, a solution equation construction module 43, and an actual position determination module 44.

[0084] Among them, the observation acquisition module 41 is used to acquire the object to be located and the TDCP observations of the object to be located.

[0085] The evolution model determination module 42 is used to determine the motion state and initial position of the object to be located in the current epoch based on the TDCP observations, and to determine the parameter time evolution model based on the motion state.

[0086] The equation construction module 43 is used to construct the state equation based on the parameter time evolution model and the initial position value, and to construct the observation equation based on the initial position value.

[0087] The actual position determination module 44 is used to correct the initial position value according to the state equation and the observation equation to obtain the actual position of the object to be located in the current epoch.

[0088] The technical solution in this embodiment, through the cooperation of the observation value acquisition module 41, the evolution model determination module 42, the equation construction module 43, and the actual position determination module 44, solves the problem that the initial position value calculated by SPP technology has poor accuracy, which affects the accuracy and efficiency of positioning the object to be located, and improves the accuracy and efficiency of positioning the object to be located.

[0089] Optionally, the observation acquisition module 41 is specifically used to: acquire the current TDCP observations and historical TDCP observations of the object to be located.

[0090] Correspondingly, the evolution model determination module 42 includes: an instantaneous velocity determination unit, used to determine the instantaneous motion velocity of the object to be located in multiple consecutive epochs based on the current TDCP observations and historical TDCP observations; a motion state determination unit, used to determine the motion state of the object to be located in the current epoch based on each instantaneous motion velocity; a position initial value determination unit, used to determine the initial position value of the object to be located in the current epoch based on the current TDCP observations; and an evolution model determination unit, used to use a predefined white noise model as the parametric time evolution model when the motion state is in motion, and a predefined constant model as the parametric time evolution model when the motion state is stationary.

[0091] Optionally, the instantaneous velocity determination unit is specifically used for: acquiring the current epoch and target historical epoch corresponding to the current TDCP observation value, and determining the first time interval between the current epoch and the target historical epoch; wherein, the target historical epoch is the historical epoch that is earlier than the current epoch and has the smallest time interval with the current epoch; determining the instantaneous velocity of the object to be located at the current epoch and the target historical epoch based on the current TDCP observation value and the first time interval; acquiring the target historical epoch and the preceding historical epoch corresponding to the historical TDCP observation value, and determining the second time interval between the target historical epoch and the preceding historical epoch; wherein, the preceding historical epoch is the historical epoch that is earlier than the target historical epoch and has the smallest time interval with the target historical epoch; and determining the instantaneous velocity of the object to be located at the preceding historical epoch based on the historical TDCP observation value and the second time interval.

[0092] Optionally, the motion state determination unit is specifically used to: determine whether the instantaneous motion speed is greater than a set speed threshold; if so, determine that the motion state of the object to be located in the current epoch is motion; if not, determine that the motion state of the object to be located in the current epoch is stationary.

[0093] Optionally, the initial position determination unit is specifically used to: determine the position change of the object to be located between the current epoch and the target historical epoch based on the current TDCP observation value; wherein, the target historical epoch is the historical epoch that is earlier than the current epoch and has the smallest time interval with the current epoch; and determine the initial position value of the object to be located in the current epoch based on the position change and the historical position value of the object to be located in the target historical epoch.

[0094] The positioning device based on the static-dynamic adaptive single-point positioning model provided in this embodiment of the invention can execute the positioning method based on the static-dynamic adaptive single-point positioning model provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution. Content not described in detail in this embodiment can be referred to the description in any method embodiment of this application.

[0095] Example 4

[0096] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement embodiments of the present invention is shown. For example... Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory 12 or a random access memory 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the read-only memory 12 or loaded from storage unit 18 into the random access memory 13. The random access memory 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, read-only memory 12, and random access memory 13 are interconnected via a bus 14. An input / output interface 15 is also connected to the bus 14.

[0097] Multiple components in electronic device 10 are connected to input / output interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0098] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a localization method based on a static-dynamic adaptive single-point localization model.

[0099] In some embodiments, the positioning method based on the static-dynamic adaptive single-point positioning model can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via read-only memory 12 and / or communication unit 19. When the computer program is loaded into random access memory 13 and executed by processor 11, one or more steps of the positioning method based on the static-dynamic adaptive single-point positioning model described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the positioning method based on the static-dynamic adaptive single-point positioning model by any other suitable means (e.g., by means of firmware).

[0100] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0101] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0102] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0103] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0104] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0105] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0106] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0107] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A positioning method based on a static-dynamic adaptive single-point positioning model, characterized in that, The positioning method based on the static and dynamic adaptive single-point positioning model includes: Obtain the object to be located, and the interepoch carrier phase differential TDCP observation values ​​of the object to be located; Based on the TDCP observations, the motion state and initial position of the object to be located in the current epoch are determined, and a parameter time evolution model is determined based on the motion state; wherein, the motion state is either running or stationary; Based on the parameter time evolution model and the initial position value, a state equation is constructed, and an observation equation is constructed based on the initial position value; Based on the state equation and the observation equation, the initial position value is corrected to obtain the actual position of the object to be located in the current epoch. The parameter time evolution model determined based on the motion state includes: When the motion state is motion, a predefined white noise model is used as the parameter time evolution model; the white noise model is a model adapted to the dynamic parameter evolution law; When the motion state is stationary, a predefined constant model is used as the parameter time evolution model; the constant model is a model adapted to the needs of static parameter estimation.

2. The positioning method based on a static-dynamic adaptive single-point positioning model according to claim 1, characterized in that, Obtaining the TDCP observations of the object to be located includes: Obtain the current TDCP observation value and historical TDCP observation value of the object to be located; Accordingly, based on the TDCP observations, the motion state and initial position of the object to be located in the current epoch are determined, including: Based on the current TDCP observations and the historical TDCP observations, the instantaneous velocity of the object to be located at multiple consecutive epochs is determined; Based on the instantaneous motion velocity, determine the motion state of the object to be located in the current epoch; Based on the current TDCP observations, determine the initial position of the object to be located in the current epoch.

3. The positioning method based on the static and dynamic adaptive single-point positioning model according to claim 2, characterized in that, Based on the current TDCP observations and the historical TDCP observations, the instantaneous velocity of the object to be located at multiple consecutive epochs is determined, including: Obtain the current epoch and target historical epoch corresponding to the current TDCP observation, and determine the first time interval between the current epoch and the target historical epoch; Wherein, the target historical epoch is a historical epoch that is earlier than the current epoch and has the smallest time interval with the current epoch; Based on the current TDCP observation and the first time interval, determine the instantaneous velocity of the object to be located at the current epoch and the target historical epoch; Obtain the target historical epoch and the preceding historical epoch corresponding to the historical TDCP observation, and determine the second time interval between the target historical epoch and the preceding historical epoch. Wherein, the preceding historical epoch is a historical epoch that is earlier than the target historical epoch and has the smallest time interval with the target historical epoch; Based on the historical TDCP observations and the second time interval, the instantaneous velocity of the object to be located at the preceding historical epoch is determined.

4. The positioning method based on the static and dynamic adaptive single-point positioning model according to claim 2, characterized in that, Based on the instantaneous motion velocities described above, the motion state of the object to be located in the current epoch is determined, including: Determine whether each instantaneous motion velocity is greater than a set velocity threshold; If so, then the motion state of the object to be located in the current epoch is determined to be motion; If not, then the motion state of the object to be located in the current epoch is determined to be stationary.

5. The positioning method based on the static-dynamic adaptive single-point positioning model according to claim 2, characterized in that, Based on the current TDCP observations, determine the initial position of the object to be located in the current epoch, including: Based on the current TDCP observations, determine the change in position of the object to be located between the current epoch and the target historical epoch; Wherein, the target historical epoch is a historical epoch that is earlier than the current epoch and has the smallest time interval with the current epoch; Based on the change in position and the historical position value of the object to be located in the target historical epoch, the initial position value of the object to be located in the current epoch is determined.

6. A positioning device based on a static-dynamic adaptive single-point positioning model, characterized in that, The positioning device based on the static and dynamic adaptive single-point positioning model includes: The observation acquisition module is used to acquire the object to be located, and the interepoch carrier phase differential TDCP observations of the object to be located; The evolution model determination module is used to determine the motion state and initial position of the object to be located in the current epoch based on the TDCP observations, and to determine the parametric time evolution model based on the motion state; wherein the motion state is running or stationary; The equation construction module is used to construct state equations based on the parameter time evolution model and the initial position values, and to construct observation equations based on the initial position values. The actual position determination module is used to correct the initial position value according to the state equation and the observation equation to obtain the actual position of the object to be located in the current epoch. The evolution model determination module includes: An evolution model determination unit is used to use a predefined white noise model as a parametric time evolution model when the motion state is motion; the white noise model is a model adapted to the dynamic parameter evolution law; When the motion state is stationary, a predefined constant model is used as the parameter time evolution model; the constant model is a model adapted to the needs of static parameter estimation.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the positioning method based on the static-dynamic adaptive single-point positioning model according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the positioning method based on the static-dynamic adaptive single-point positioning model as described in any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the positioning method based on the static-dynamic adaptive single-point positioning model according to any one of claims 1-5.

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