Adaptive RTK positioning method and system based on Doppler velocity measurement

Abstract

The invention provides a self-adaptive RTK positioning method and system based on Doppler velocity measurement, and the method comprises the steps: extracting the pseudo-range, carrier phase, Doppler frequency shift and navigation messages of an observation satellite from a baseband chip of a satellite user machine in real time, and calculating the coordinates of the satellite at the current moment through the navigation messages; calculating a carrier three-dimensional velocity vector and a carrier velocity scalar based on Doppler frequency shift in real time; presetting a first speed judgment threshold value and a second speed judgment threshold value, and judging the motion state of the current carrier; corresponding processing strategies and parameters are adaptively selected and configured for the RTK positioning filter; and RTK positioning calculation is executed, a final positioning result is output, and adaptive RTK positioning based on Doppler velocity measurement is completed. By applying the technical scheme of the invention, the potential of convergence speed acceleration and precision improvement caused by the fact that a static state cannot be fully utilized by whole-course dynamic mode positioning in the prior art is solved; and restarting or switching the positioning mode causes the loss of lock of the satellite or the great jump of the positioning result.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation technology, and in particular to an adaptive RTK positioning method and system based on Doppler velocity measurement. Background Technology

[0002] Real-time dynamic carrier phase differential (RTK) is one of the most accurate satellite navigation and positioning technologies currently available, capable of providing positioning accuracy at the centimeter or even millimeter level. Traditional RTK positioning typically employs a single, fixed processing strategy. When the carrier is known to be stationary, the position parameters have strict equality constraints between epochs, and dynamic models such as velocity do not need to be considered, thus achieving faster convergence and higher accuracy. However, when the carrier is moving, the position changes between epochs need to be considered, and sometimes the position parameters may even need to be reset.

[0003] However, current technology has significant drawbacks: in practical applications, the motion state of the carrier is dynamically changing. For example, vehicles need to frequently switch between deceleration, stopping, driving, and acceleration; drones go through stages such as cruising, hovering, and maneuvering. To ensure navigation continuity, existing technologies mostly use a fully dynamic mode for positioning, which means that when the vehicle is stationary or the drone is hovering, the potential for faster convergence and improved accuracy cannot be fully utilized. Restarting the system or abruptly switching positioning modes may lead to satellite lock-on loss or significant jumps in positioning results, affecting continuity and reliability. Summary of the Invention

[0004] This invention provides an adaptive RTK positioning method and system based on Doppler velocity measurement, which can solve the technical problems of existing technologies that mostly use a full-process dynamic mode for positioning, which makes it impossible to fully utilize the potential for faster convergence speed and improved accuracy brought by the stationary state when the vehicle is stopped or the drone is hovering; restarting the system or forcefully switching the positioning mode may lead to satellite loss or large jumps in positioning results, affecting continuity and reliability.

[0005] According to one aspect of the present invention, an adaptive RTK positioning method based on Doppler velocity measurement is provided. The adaptive RTK positioning method based on Doppler velocity measurement includes: Step 1, extracting the pseudorange, carrier phase, Doppler frequency shift, and navigation message of the observed satellite in real time from the baseband chip of the satellite user terminal, and calculating the satellite coordinates at the current time using the navigation message; Step 2, calculating the three-dimensional velocity vector and the velocity scalar of the carrier based on the Doppler frequency shift in real time according to the pseudorange, carrier phase, Doppler frequency shift of the observed satellite and the satellite coordinates at the current time; Step 3, setting a first velocity decision threshold v. thre1 Second speed decision threshold v thre2 The carrier velocity scalar is compared with the first velocity decision threshold v.thre1 Second speed decision threshold v thre2 The process involves several steps: First, a comparison is made to determine the motion state of the current carrier. Second, based on the decision result in step three, the appropriate processing strategy and parameters are adaptively selected and configured for the RTK positioning filter. Third, using the strategy and parameters configured in step four, the pseudorange and carrier phase of the observed satellites extracted in step one, the RTK positioning calculation is performed, and the final positioning result is output, thus completing the adaptive RTK positioning based on Doppler velocimetry.

[0006] Furthermore, in step two, the three-dimensional velocity vector of the carrier... According to The carrier velocity scalar v is obtained through calculation. u According to The values ​​are calculated and obtained as follows: s is the number of observation satellites participating in the positioning, v is the observation equation residual for each satellite, (l, m, k) are the three-dimensional direction cosines for each satellite, and c is the speed of light. The velocity of the satellite user terminal is the three-dimensional velocity vector of the carrier. For receiver clock drift, the unit is seconds per second, and L is a constant term.

[0007] Furthermore, step two also includes: conducting a quality assessment of the Doppler velocity measurement results, including checking the satellite geometric distribution, the rationality of the velocity vector, and residual detection.

[0008] Furthermore, in step three, the motion state is determined based on the carrier velocity scalar calculated in step two. The specific determination strategy is as follows:

[0009] Furthermore, in step four, the position prediction process for inter-epoch filtering is as follows: in, Represents the state transition matrix. x represents the predicted value of the carrier's position and velocity at the current epoch. k This indicates the position and velocity of the carrier in the previous epoch. P represents the predicted covariance of the current epoch position and velocity. k This represents the covariance of position and velocity in the previous epoch. This indicates process noise.

[0010] Furthermore, when the carrier's motion state is quasi-stationary, the solution results from the previous epoch can be directly used, i.e., the state transition matrix is ​​the identity matrix and the process noise is zero.

[0011] Furthermore, when the carrier's motion state is in a low-speed scenario, the carrier's position is predicted based on its velocity. The filtering prediction process is as follows: Where, τ r =t k+1 -t k This represents the time interval between two epochs. Q 3×3 This represents the increase in process noise per unit time.

[0012] Furthermore, when the carrier's motion state is a typical dynamic scene, the position and velocity state of the current epoch are reinitialized using the results of pseudorange single-point positioning: Where, x spp Q represents the pseudorange single-point localization result. 3×3,pos and Q 3×3,vel These represent the initial covariances of position and velocity, respectively.

[0013] According to another aspect of the present invention, an adaptive RTK positioning system based on Doppler velocity measurement is provided, which uses the adaptive RTK positioning method based on Doppler velocity measurement described above for adaptive RTK positioning.

[0014] Furthermore, the Doppler velocimetry-based adaptive RTK positioning system includes: a satellite parameter acquisition module, which extracts the pseudorange, carrier phase, Doppler frequency shift, and navigation message of the observed satellite from the baseband chip of the satellite user terminal in real time, and calculates the satellite coordinates at the current time using the navigation message; a carrier velocity calculation module, which calculates the three-dimensional velocity vector and the carrier velocity scalar based on the Doppler frequency shift in real time according to the pseudorange, Doppler frequency shift, and satellite coordinates at the current time of the observed satellite; and a motion state decision module, which presets a first velocity decision threshold v. thre1 Second speed decision threshold v thre2 The carrier velocity scalar is compared with the first velocity decision threshold v. thre1 Second speed decision threshold v thre2 The system compares and determines the motion state of the current carrier; the strategy and parameter configuration module adaptively selects and configures the corresponding processing strategy and parameters for the RTK positioning filter based on the motion state determination result of the current carrier; the RTK positioning module uses the configured strategy and parameters, the pseudorange and carrier phase of the observed satellites to perform RTK positioning calculation, outputs the final positioning result, and completes adaptive RTK positioning based on Doppler velocimetry.

[0015] The present invention provides an adaptive RTK positioning method based on Doppler velocimetry. This method, by identifying the motion state of the carrier and adjusting process noise and filtering update parameters, dynamically switches the positioning strategy, effectively improving convergence speed and positioning accuracy, and has significant practical implications. Therefore, compared with existing technologies, the adaptive RTK positioning method based on Doppler velocimetry provided by this invention can perceive the precise instantaneous velocity of the carrier in real time and automatically and smoothly switch the most suitable positioning processing strategy accordingly, thereby maximizing convergence speed and positioning accuracy while ensuring positioning continuity. Attached Figure Description

[0016] The accompanying drawings, which form part of this specification, are provided to further illustrate embodiments of the invention and, together with the textual description, explain the principles of the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0017] Figure 1 A flowchart of an adaptive RTK positioning method based on Doppler velocimetry, according to a specific embodiment of the present invention, is shown. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0020] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0021] like Figure 1 As shown, according to a specific embodiment of the present invention, an adaptive RTK positioning method based on Doppler velocity measurement is provided. This adaptive RTK positioning method based on Doppler velocity measurement includes: Step 1, extracting the pseudorange, carrier phase, Doppler frequency shift, and navigation message of the observed satellite in real time from the baseband chip of the satellite user terminal, and calculating the satellite coordinates at the current time using the navigation message; Step 2, calculating the three-dimensional velocity vector and the velocity scalar of the carrier based on the Doppler frequency shift in real time according to the pseudorange, carrier phase, Doppler frequency shift of the observed satellite and the satellite coordinates at the current time; Step 3, setting a first velocity decision threshold v. thre1 Second speed decision threshold v thre2 The carrier velocity scalar is compared with the first velocity decision threshold v. thre1 Second speed decision threshold v thre2 The process involves several steps: First, a comparison is made to determine the motion state of the current carrier. Second, based on the decision result in step three, the appropriate processing strategy and parameters are adaptively selected and configured for the RTK positioning filter. Third, using the strategy and parameters configured in step four, the pseudorange and carrier phase of the observed satellites extracted in step one, the RTK positioning calculation is performed, and the final positioning result is output, thus completing the adaptive RTK positioning based on Doppler velocimetry.

[0022] This configuration provides an adaptive RTK positioning method based on Doppler velocimetry. This method, by identifying the carrier's motion state and adjusting process noise and filtering update parameters, dynamically switches positioning strategies, effectively improving convergence speed and positioning accuracy, thus possessing significant practical value. Therefore, compared with existing technologies, the adaptive RTK positioning method based on Doppler velocimetry provided by this invention can perceive the carrier's precise instantaneous velocity in real time and automatically and smoothly switch the most suitable positioning processing strategy accordingly, thereby maximizing convergence speed and positioning accuracy while ensuring positioning continuity.

[0023] Furthermore, in this invention, in step two, the three-dimensional velocity vector of the carrier... According to The values ​​are calculated and obtained as follows: s is the number of observation satellites participating in the positioning; v is the observation equation residual for each satellite (calculated based on Doppler frequency shift); (l, m, k) are the three-dimensional direction cosines for each satellite (calculated based on the pseudorange of the observation satellite); and c is the speed of light. The velocity of the satellite user terminal is the three-dimensional velocity vector of the carrier. For receiver clock drift, the unit is seconds per second, and L is a constant term.

[0024] In step two, the carrier velocity scalar v u According to The calculation is then performed. Step two also includes: quality assessment of the Doppler velocity measurement results, including checking the satellite geometric distribution, the rationality of the velocity vector, and residual detection (RAIM). Checking the rationality of the satellite geometric distribution and velocity vector is a well-known method in the field and will not be detailed here. Residual detection (RAIM) specifically involves: when the residual of a participating observation satellite is greater than 0.3 m / s, that satellite is removed from the positioning process and the calculation is restarted. When more than 3 satellites are removed or fewer than 5 satellites remain, the calculation is stopped, and the velocity calculation result is considered unreliable.

[0025] Furthermore, in this invention, in step three, the motion state is determined based on the carrier velocity scalar calculated in step two. The specific determination strategy is as follows:

[0026] In this invention, the position prediction process for inter-epoch filtering in step four is as follows: in, Represents the state transition matrix. x represents the predicted value of the carrier's position and velocity at the current epoch. k This indicates the position and velocity of the carrier in the previous epoch. P represents the predicted covariance of the current epoch position and velocity. k This represents the covariance of position and velocity in the previous epoch. This indicates process noise.

[0027] When the carrier's motion state is quasi-stationary, the solution results from the previous epoch can be directly used, meaning the state transition matrix is ​​the identity matrix and the process noise is zero.

[0028] When the vehicle is in a low-speed motion scenario, the vehicle position is predicted based on velocity. The filtering prediction process is as follows: Where, τ r =t k+1 -t k This represents the time interval between two epochs. Q 3×3 This represents the increase in process noise per unit time.

[0029] When the carrier's motion state is a normal dynamic scene, the position and velocity state of the current epoch are reinitialized using the results of pseudorange single-point positioning: Where, x spp Q represents the pseudorange single-point localization result. 3×3,pos and Q 3×3,vel These represent the initial covariances of position and velocity, respectively.

[0030] According to another aspect of the present invention, an adaptive RTK positioning system based on Doppler velocity measurement is provided, which uses the adaptive RTK positioning method based on Doppler velocity measurement described above for adaptive RTK positioning.

[0031] This configuration provides an adaptive RTK positioning system based on Doppler velocimetry. This method, by identifying the carrier's motion state and adjusting process noise and filtering update parameters, dynamically switches positioning strategies, effectively improving convergence speed and positioning accuracy, thus possessing significant practical value. Therefore, compared to existing technologies, the adaptive RTK positioning system based on Doppler velocimetry provided by this invention can perceive the carrier's precise instantaneous velocity in real time and automatically and smoothly switch to the most suitable positioning processing strategy accordingly, thereby maximizing convergence speed and positioning accuracy while ensuring positioning continuity.

[0032] Specifically, in this invention, the adaptive RTK positioning system based on Doppler velocimetry includes a satellite parameter acquisition module, a carrier velocity calculation module, a motion state decision module, a strategy and parameter configuration module, and an RTK positioning module. The satellite parameter acquisition module is used to extract the pseudorange, carrier phase, Doppler frequency shift, and navigation message of the observed satellite from the baseband chip of the satellite user terminal in real time, and calculate the satellite coordinates at the current time using the navigation message. The carrier velocity calculation module is used to calculate the three-dimensional velocity vector and the carrier velocity scalar based on the Doppler frequency shift in real time according to the pseudorange, Doppler frequency shift, and satellite coordinates at the current time of the observed satellite. A first velocity decision threshold v is preset. thre1 Second speed decision threshold v thre2 The carrier velocity scalar is compared with the first velocity decision threshold v. thre1 Second speed decision threshold v thre2The system compares and determines the motion state of the current carrier; the strategy and parameter configuration module is used to adaptively select and configure the corresponding processing strategy and parameters for the RTK positioning filter based on the motion state determination result of the current carrier; the RTK positioning module is used to perform RTK positioning calculation using the configured strategy and parameters, the pseudorange and carrier phase of the observed satellite, and output the final positioning result to complete the adaptive RTK positioning based on Doppler velocity measurement.

[0033] To gain a further understanding of the present invention, the following description is provided in conjunction with... Figure 1 The adaptive RTK positioning method and system based on Doppler velocity measurement provided by this invention will be described in detail.

[0034] like Figure 1 As shown in the figure, an adaptive RTK positioning method based on Doppler velocimetry is provided according to a specific embodiment of the present invention. This method can sense the precise instantaneous velocity of the carrier in real time and automatically and smoothly switch the most suitable positioning processing strategy accordingly, thereby maximizing the convergence speed and positioning accuracy while ensuring positioning continuity.

[0035] The technical solution of the present invention is as follows:

[0036] Step 1: Extract pseudorange, carrier phase, Doppler shift, and navigation message of the observed satellite in real time from the baseband chip of the satellite user terminal, and use the navigation message to calculate the satellite coordinates at the current time.

[0037] Step 2: Calculate the carrier's three-dimensional velocity vector and velocity scalar in real time based on the Doppler frequency shift. Simultaneously, perform a quality assessment of the Doppler velocimetry results, including checking the satellite's geometric distribution, the rationality of the velocity vector, and residual detection (RAIM).

[0038] Step 3: Preset two speed decision thresholds v thre1 and v thre2 The real-time rate v u The velocity scalar is compared with a threshold to classify the current motion state of the carrier into three types: normal dynamic, low-speed, and quasi-stationary.

[0039] Step 4: Based on the decision result of Step 3, adaptively select and configure the corresponding processing strategy and parameters for the RTK positioning filter. This mainly includes the position and velocity update strategy, process noise level setting, and dynamic model selection.

[0040] Step 5: Using the strategy and parameters configured in Step 4, execute RTK localization calculation and output the final localization result.

[0041] Furthermore, in step two, the Doppler calculation speed is achieved based on least squares, and the specific method is as follows:

[0042]

[0043] Where s is the number of observation satellites participating in the positioning, v is the observation equation residual for each satellite (calculated based on Doppler frequency shift), (l, m, k) are the three-dimensional direction cosines for each satellite (calculated based on the pseudorange of the observation satellite), and c is the speed of light. For satellite user terminal speed, For receiver clock drift, the unit is seconds per second, and L is a constant term.

[0044] Furthermore, simplifying equation (1) to

[0045] V=Hx+L (2)

[0046] in, The least squares solution speed result can be expressed as:

[0047] x=(H T PH) -1 H T PL (3)

[0048] The rate is calculated as follows:

[0049]

[0050] Furthermore, by substituting x obtained from equation (3) back into equation (1), the residual of the observed satellite can be obtained. When the residual of an observed satellite participating in the calculation is greater than 0.3 m / s, the satellite is set to a state of not participating in positioning, and the calculation is repeated. When the number of satellites removed is greater than 3 or the number of remaining satellites is less than 5, the calculation is stopped, and the velocity calculation result is considered unreliable.

[0051] Furthermore, in step three, the motion state is determined based on the carrier velocity calculated in step two. The specific determination strategy is as follows:

[0052]

[0053] In this method, the threshold is set to v. thre1 =0.1m / s,v thre2 =0.5m / s. When the quality assessment result of step two indicates that the velocity calculation result is unreliable, the same processing strategy as for conventional dynamics is adopted.

[0054] Furthermore, in step four, based on the judgment result of step three, a differentiated state transfer strategy is adopted for different motion states.

[0055] The position prediction process for inter-epoch filtering is as follows:

[0056]

[0057] in, Represents the state transition matrix. x represents the predicted value of the carrier's position and velocity at the current epoch. k This indicates the position and velocity of the carrier in the previous epoch. P represents the predicted covariance of the current epoch position and velocity. k This represents the covariance of position and velocity in the previous epoch. This indicates process noise.

[0058] ① For quasi-static scenarios, the solution results from the previous epoch can be directly used, i.e., the state transition matrix is ​​the identity matrix and the process noise is zero:

[0059]

[0060] ② For low-speed scenarios, the carrier position is predicted based on velocity. The filtering prediction process is as follows:

[0061]

[0062] Where, τ r =t k+1 -t k This represents the time interval between two epochs. Q 3×3 This represents the increase in process noise per unit time, which is set to Q in this method. 3×3 =diag{0.5,0.5,0.5}.

[0063] ③ For typical dynamic scenarios, the position and velocity states of the current epoch are reinitialized using the results of pseudorange single-point positioning:

[0064]

[0065] Where, x spp Q represents the pseudorange single-point localization result. 3×3,pos and Q 3×3,vel These represent the initial covariances of position and velocity, respectively, which are set to Q in this method. 3×3,pos =Q 3×3,vel =diag{100 2 100 2 100 2}

[0066] Subsequently, in step five, the standard RTK localization calculation process is executed, and the final localization result is output. The RTK localization calculation process is a standard method in this field and will not be described in detail here.

[0067] In summary, this invention provides an adaptive RTK positioning system based on Doppler velocimetry. This method, by identifying the motion state of the carrier and adjusting process noise and filtering update parameters, dynamically switches the positioning strategy, effectively improving convergence speed and positioning accuracy, and has significant practical implications. Therefore, compared with existing technologies, the adaptive RTK positioning system based on Doppler velocimetry provided by this invention can perceive the precise instantaneous velocity of the carrier in real time and automatically and smoothly switch the most suitable positioning processing strategy accordingly, thereby maximizing convergence speed and positioning accuracy while ensuring positioning continuity.

[0068] For ease of description, spatial relative terms such as "above," "on top of," "on the upper surface of," "above," etc., are used herein to describe the spatial positional relationship of a device or feature as shown in the figures to other devices or features. It should be understood that spatial relative terms are intended to encompass different orientations in use or operation beyond the orientation of the device as described in the figures. For example, if the device in the figures were inverted, a device described as "above" or "on top of" other devices or structures would subsequently be positioned as "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below." The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used herein will be interpreted accordingly.

[0069] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore should not be construed as limiting the scope of protection of this invention.

[0070] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An adaptive RTK positioning method based on Doppler velocity measurement, characterized in that, The adaptive RTK positioning method based on Doppler velocity measurement includes: Step 1: Extract pseudorange, carrier phase, Doppler shift, and navigation message of the observed satellite in real time from the baseband chip of the satellite user terminal, and use the navigation message to calculate the satellite coordinates at the current time; Step 2: Based on the pseudorange, carrier phase, Doppler shift, and current satellite coordinates of the observed satellite, calculate the three-dimensional velocity vector and velocity scalar of the carrier in real time based on the Doppler shift; Step 3: Preset the first speed decision threshold v thre1 Second speed decision threshold v thre2 The carrier velocity scalar is compared with the first velocity decision threshold v. thre1 and the second speed decision threshold v thre2 The comparison is made to determine the current motion state of the carrier. Step four: Based on the decision result in step three, adaptively select and configure the corresponding processing strategy and parameters for the RTK positioning filter; Step 5: Using the strategy and parameters configured in Step 4, and the pseudorange and carrier phase of the observed satellites extracted in Step 1, perform RTK positioning calculation, output the final positioning result, and complete the adaptive RTK positioning based on Doppler velocimetry.

2. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 1, characterized in that, In step two, the three-dimensional velocity vector of the carrier According to The velocity scalar v of the carrier is calculated and obtained. u According to The values ​​are calculated and obtained as follows: s is the number of observation satellites participating in the positioning, v is the observation equation residual for each satellite, (l, m, k) are the three-dimensional direction cosines for each satellite, and c is the speed of light. The velocity of the satellite user terminal is the three-dimensional velocity vector of the carrier. For receiver clock drift, the unit is seconds per second, and L is a constant term.

3. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 2, characterized in that, Step two also includes: performing a quality assessment on the Doppler velocity measurement results, including checking the satellite geometric distribution, the rationality of the velocity vector, and residual detection.

4. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 3, characterized in that, In step three, the motion state is determined based on the carrier velocity scalar calculated in step two. The specific determination strategy is as follows:

5. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 4, characterized in that, In step four, the position prediction process for inter-epoch filtering is as follows: in, Represents the state transition matrix. x represents the predicted value of the carrier's position and velocity at the current epoch. k This indicates the position and velocity of the carrier in the previous epoch. P represents the predicted covariance of the current epoch position and velocity. k This represents the covariance of position and velocity in the previous epoch. This indicates process noise.

6. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 5, characterized in that, When the carrier's motion state is quasi-stationary, the solution results from the previous epoch can be directly used, meaning the state transition matrix is ​​the identity matrix and the process noise is zero.

7. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 5, characterized in that, When the vehicle is in a low-speed motion scenario, the vehicle position is predicted based on velocity. The filtering prediction process is as follows: Where, τ r =t k+1 -t k This represents the time interval between two epochs. Q 3×3 This represents the increase in process noise per unit time.

8. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 5, characterized in that, When the carrier's motion state is a normal dynamic scene, the position and velocity state of the current epoch are reinitialized using the results of pseudorange single-point positioning: Where, x spp Q represents the pseudorange single-point localization result. 3×3,pos and Q 3×3,vel These represent the initial covariances of position and velocity, respectively.

9. An adaptive RTK positioning system based on Doppler velocity measurement, characterized in that, The Doppler velocimetry-based adaptive RTK positioning system uses the Doppler velocimetry-based adaptive RTK positioning method as described in claims 1 to 8 for adaptive RTK positioning.

10. The adaptive RTK positioning system based on Doppler velocimetry according to claim 9, characterized in that, The adaptive RTK positioning system based on Doppler velocity measurement includes: The satellite parameter acquisition module is used to extract the pseudorange, carrier phase, Doppler shift and navigation message of the observed satellite in real time from the baseband chip of the satellite user terminal, and to calculate the satellite coordinates at the current time using the navigation message; The carrier velocity calculation module is used to calculate the carrier's three-dimensional velocity vector and carrier velocity scalar in real time based on the pseudorange, Doppler frequency shift, and current satellite coordinates of the observed satellite. The motion state determination module has a preset first velocity determination threshold v. thre1 Second speed decision threshold v thre2 The carrier velocity scalar is compared with the first velocity decision threshold v. thre1 and the second speed decision threshold v thre2 The comparison is made to determine the current motion state of the carrier. The strategy and parameter configuration module is used to adaptively select and configure corresponding processing strategies and parameters for the RTK positioning filter based on the current motion state judgment result of the carrier. The RTK positioning module is used to perform RTK positioning calculations using the configured strategies and parameters, the pseudorange and carrier phase of the observed satellite, and output the final positioning result to complete adaptive RTK positioning based on Doppler velocimetry.

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