GNSS multidimensional gross error detection method, device, electronic device and storage medium

Abstract

The present invention relates to a multi-dimensional gross error detection method, device, electronic device and storage medium of GNSS, and the method comprises: obtaining observation data of each group of satellites, and constructing an inter-satellite single difference observation equation based on the observation data; obtaining the steady motion characteristics of the carrier, and constructing a state equation based on the steady motion characteristics; constructing a velocity measurement model using the inter-satellite single difference observation equation and the state equation, and constructing a pre-test residual error test quantity of the observation value derived Doppler observation value for each group of satellites based on the prediction information in the velocity measurement model; detecting the gross error result of the derived Doppler observation value according to the obedience relationship between the pre-test residual error test quantity of the observation value and a preset distribution or the size of the pre-test residual error test quantity of the observation value. The present invention can detect gross errors less than one week, and improve the accuracy and reliability of GNSS velocity measurement.

Description

Technical Field

[0001] The present invention relates to the field of satellite geodetic technology, and in particular to a multi-dimensional gross error detection method, device, electronic equipment and storage medium for GNSS. Background Art

[0002] In recent years, the global satellite navigation and positioning system (GNSS) has developed rapidly. Especially with the completion of the global networking of the Beidou satellite system and its successful commissioning, my country's satellite navigation industry has also entered a period of rapid development. Compared with traditional speed measurement methods such as laser, sound waves, and radar, GNSS speed measurement has the characteristics of all-weather, global coverage, and high precision, and has been widely used in transportation, unmanned driving and other fields.

[0003] Speed ​​is an important parameter in navigation, and obtaining the speed of the carrier is a prerequisite for solving a series of problems such as navigation and path planning. Traditional GNSS speed measurement is mainly based on the position difference method, which obtains the carrier speed by numerically differentiating the position sequence. However, it has very high requirements on position accuracy, and the ambiguity is often difficult to fix in the case of a dynamic long baseline. With the advancement of GNSS speed measurement technology, a speed solution method that uses carrier phase construction to derive Doppler observations has been developed. It mainly adopts the idea of ​​epoch-to-epoch difference, eliminates the ambiguity parameters and the errors that change slowly between epochs, and can obtain high-precision carrier speed information in real time, while having low dependence on carrier positioning accuracy.

[0004] However, due to the influence of the measurement environment, the carrier phase observations inevitably have gross errors. Especially in the speed measurement mode using multiple frequencies and multiple systems, the number of observations increases exponentially, and the probability of multiple measurement gross errors in the same epoch also gradually increases. Centimeter-level observation gross errors can even cause decimeter to meter-level speed errors. Therefore, how to accurately detect multi-dimensional gross errors is an urgent problem to be solved. Summary of the invention

[0005] In view of this, it is necessary to provide a multi-dimensional gross error detection method, device, electronic device and storage medium to solve the problem of not being able to obtain high-precision carrier velocity information due to inaccurate gross error detection.

[0006] In order to solve the above problems, in a first aspect, the present invention provides a multi-dimensional gross error detection method for GNSS, comprising:

[0007] Acquire observation data of each group of satellites in GNSS, and construct an inter-satellite single-difference observation equation based on the observation data;

[0008] Acquiring a steady motion characteristic of the carrier, and constructing a state equation based on the steady motion characteristic;

[0009] A velocity measurement model is constructed by using the inter-satellite single-difference observation equation and the state equation, and a pre-test residual error test quantity of an observation value for deriving a Doppler observation value is constructed for each group of satellites based on the prediction information in the velocity measurement model;

[0010] The gross error result of the derived Doppler observation value is detected according to the compliance relationship between the pre-test residual check amount of the observation value and the preset distribution or the size of the pre-test residual check amount of the observation value.

[0011] Furthermore, constructing an inter-satellite single-difference observation equation based on the observation data includes:

[0012] Performing a preprocessing operation on the observation data to obtain a preprocessed carrier phase observation value;

[0013] The preprocessed satellite carrier phase observations are used to construct the first inter-satellite single-difference observation equation: Where Δ represents the single difference operator, λ is the wavelength, is the carrier phase observation value, r is the receiver, p, q are the observation satellites, is the difference between the carrier phase observations between satellites, ρ is the distance between the receiver and the observation satellite, is the distance difference between the receiver and the two observation satellites, c is the speed of light, dt is the clock error, Δdt p,q is the clock difference of the observed satellites p and q, N is the integer ambiguity, is the difference in the integer ambiguity of the observed satellites p and q, is the tropospheric delay, is the carrier phase observation noise;

[0014] Constructing derived Doppler observations based on the preprocessed carrier phase observations;

[0015] The second inter-satellite single-difference observation equation is constructed based on the derived Doppler observations: in, is the difference in Doppler observations derived between satellites at time t, is the direction cosine between the station and the first observation satellite p, is the direction cosine between the observation station and the second observation satellite q, is the velocity of the first observing satellite p at time t, is the speed of the second observation satellite q at time t, is the velocity of the carrier rover at time t, is the difference in the tropospheric slant delay change rate between the observation satellites p and q at time t, is the carrier phase observation noise, is the difference in the clock error change rate of the observed satellites p and q.

[0016] Furthermore, the constructing a velocity measurement model using the inter-satellite single-difference observation equation and the state equation includes:

[0017] The velocity measurement model is constructed using the second inter-satellite single-difference observation equation and the state equation: in, is the predicted speed of the carrier at time t, is the observation error including the tropospheric error, is the carrier velocity prediction error at time t, is the velocity error of the first observed satellite p at time t, is the velocity error of the second observation satellite q at time t, is the residual of the difference in the rate of change of the clock errors of the observed satellites p and q;

[0018] The prediction information in the speed measurement model includes the predicted carrier speed, and the observation value pre-test residual error test quantity for constructing the derived Doppler observation value for each group of satellites based on the prediction information in the speed measurement model includes:

[0019] Based on the carrier velocity prediction value, a pre-test residual error test quantity of the Doppler observation value derived from each group of satellites is constructed.

[0020] Further, according to the obedience relationship between the residual error test amount of the observation value before verification and the preset distribution, detecting the gross error result of the derived Doppler observation value includes:

[0021] The observed value pre-test residual test quantity is standardized to obtain a standardized test quantity

[0022] If the standardized test quantity The derived Doppler observations are subject to normal distribution and do not include gross errors;

[0023] If the standardized test quantity The derived Doppler observations do not obey a normal distribution and include gross errors.

[0024] Further, detecting the gross error result of the derived Doppler observation value according to the size of the residual error test amount before the observation value verification includes:

[0025] The observed value pre-test residual test quantity is standardized to obtain a standardized test quantity

[0026] If the standardized test quantity If the absolute value of is within a first preset threshold range, the derived Doppler observation value includes a gross error.

[0027] Furthermore, the observed value pre-test residual test quantity is standardized to obtain a standardized test quantity include:

[0028] Obtaining prior information of various errors in the residual test quantity of the observed value before the test;

[0029] According to the prior information of the errors, the mean error of the residual test quantity of the observation value before the test is calculated based on the error statistical characteristics

[0030] The standardized test quantity is obtained by standardizing the residual test quantity of the observed value before the test based on the mean error Where μ is the sample mean.

[0031] Furthermore, the above method also includes:

[0032] According to the standardized test The absolute value is adjusted by using the weight function of IGGⅢ to adjust the weight of the derived Doppler observation value;

[0033] The weight adjustment formula is: Among them, R i is the original weight of the ith observation, is the equivalent weight factor, k0 and k1 are model parameters and have no actual physical meaning.

[0034] In a second aspect, the present invention further provides a multi-dimensional gross error detection device, comprising:

[0035] An observation equation construction module, used to obtain observation data of each group of satellites and construct an inter-satellite single-difference observation equation based on the observation data;

[0036] A state equation construction module, used for obtaining the smooth motion characteristics of the carrier and constructing the state equation based on the smooth motion characteristics;

[0037] A test quantity construction module is used to construct a velocity measurement model using the inter-satellite single-difference observation equation and the state equation, and to construct an observation value pre-test residual test quantity for deriving Doppler observation values ​​for each group of satellites based on the prediction information in the velocity measurement model;

[0038] The gross error detection module is used to detect the gross error result of the derived Doppler observation value according to the obedience relationship between the pre-test residual error check amount of the observation value and the preset distribution or the size of the pre-test residual error check amount of the observation value.

[0039] In a third aspect, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above-mentioned multidimensional gross error detection method when executing the computer program.

[0040] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the multi-dimensional gross error detection method as described above are implemented.

[0041] The beneficial effects of adopting the above-mentioned embodiment are as follows: the method provided by the present invention realizes the observation of multiple groups of satellites by acquiring the observation data of each group of satellites, thereby realizing multi-dimensional gross errors, and constructs the inter-satellite single-difference observation equation through the observation data, thereby avoiding errors; and constructs the state equation according to the smooth motion characteristics of the carrier to reduce the prediction error of the speed measurement model; finally, the speed measurement model is constructed through the observation equation and the state equation, and the gross error result of the observation value is detected according to the obedience relationship between the residual test amount of the observation value before verification and the preset distribution, so as to detect gross errors less than one week.

[0042] In addition, by adopting the IGGⅢ anti-error scheme to downweight the derived Doppler observation value weights, the reliability and accuracy of the speed measurement results are greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of a flow chart of an embodiment of a multi-dimensional gross error detection method provided by the present invention;

[0044] Figure 2 A schematic structural diagram of an embodiment of a multi-dimensional gross error detection device 200 provided by the present invention;

[0045] Figure 3 A schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0046] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the present invention and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0047] In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically limited. Reference to "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0048] A gross error refers to a measurement deviation whose absolute value exceeds the tolerance limit when making a series of observations under the same observation conditions. Measurement data containing gross errors must never be used, so it is necessary to detect the gross errors.

[0049] The present invention provides a multi-dimensional gross error detection method, device, electronic device and storage medium, which are respectively described below.

[0050] See also Figure 1 , Figure 1 A flowchart of an embodiment of a multidimensional gross error detection method provided by the present invention is provided. A specific embodiment of the present invention discloses a multidimensional gross error detection method, including:

[0051] Step S101: Obtain observation data of each group of satellites, and construct an inter-satellite single-difference observation equation based on the observation data;

[0052] The observation data include satellite carrier phase observation values, satellite altitude angles, satellite broadcast ephemeris and other data. The present invention acquires observation data of multiple groups of satellites to detect gross errors from a multi-dimensional perspective.

[0053] By constructing a single-difference observation equation between observation satellites based on observation data, it is easy to detect gross errors. It can be understood that single difference refers to directly subtracting the observation values, and the result obtained is the single difference of the carrier phase observation value, which includes finding a single difference between observation satellites, finding a single difference between receivers, and finding a single difference between different epochs. By finding a single difference between receivers, the satellite clock error can be eliminated, the number of receiver clock error parameters is reduced, and the influence of satellite ephemeris error, ionospheric error and tropospheric delay can also be weakened.

[0054] In one embodiment of the present invention, constructing an inter-satellite single-difference observation equation based on observation data includes:

[0055] Performing preprocessing operations on the observed data to obtain preprocessed carrier phase observation values;

[0056] It is understandable that, in general, the initially acquired observation data is rather messy, and therefore it is necessary to perform preprocessing operations on the observation data, specifically, to perform quality inspection on the acquired observation data, and to remove observation data with a low signal-to-noise ratio and observation data containing cycle slips.

[0057] The first inter-satellite single-difference observation equation is constructed using the preprocessed satellite carrier phase observations: Where Δ represents the single difference operator, λ is the wavelength, is the carrier phase observation value, r is the receiver, p, q are the observation satellites, is the difference between the carrier phase observations between satellites, ρ is the distance between the receiver and the observation satellite, is the distance difference between the receiver and the two observation satellites, c is the speed of light, dt is the clock error, Δdt p,q is the clock difference of the observed satellites p and q, N is the integer ambiguity, is the difference in the integer ambiguity of the observed satellites p and q, T, are all tropospheric delays, ε, All are carrier phase observation noise;

[0058] Constructing derived Doppler observations based on preprocessed carrier phase observations;

[0059] The second inter-satellite single-difference observation equation is constructed based on the derived Doppler observations: in, is the difference in Doppler observations derived between satellites at time t, is the direction cosine between the station and the first observation satellite p, is the direction cosine between the observation station and the second observation satellite q, is the velocity of the first observing satellite p at time t, is the speed of the second observation satellite q at time t, is the velocity of the carrier rover at time t, is the tropospheric wet delay variation rate, is the difference in the tropospheric slant delay change rate between the observation satellites p and q at time t, is the carrier phase observation noise, is the difference in the clock error change rate of the observed satellites p and q.

[0060] It is understandable that after the observation equation is constructed, in order to make the observation equation further serve the velocity measurement model and to further enhance the effect of single difference, the observation equation can be error corrected. In one embodiment of the present invention, it specifically includes: satellite position and velocity can be obtained by broadcast ephemeris calculation, receiver coordinates can be obtained by standard single point positioning, tropospheric delay can be corrected by Saastamoinen model, tropospheric delay includes tropospheric dry delay and tropospheric wet delay, phase observation noise is in millimeter order, its influence can be ignored, and satellite clock speed is corrected by broadcast ephemeris.

[0061] Step S102: obtaining the steady motion characteristics of the carrier, and constructing a state equation based on the steady motion characteristics;

[0062] Wherein, the state equation includes a constant acceleration state equation, and the present invention assumes that the motion characteristics of the carrier are stable.

[0063] Step S103: constructing a velocity measurement model using the inter-satellite single-difference observation equation and the state equation, and constructing a pre-test residual error test quantity for deriving Doppler observation values ​​for each group of satellites based on the prediction information in the velocity measurement model;

[0064] Among them, using the inter-satellite single-difference observation equation and the state equation to construct the speed measurement model includes using the first inter-satellite single-difference observation equation and the state equation to construct the speed measurement model or using the second inter-satellite single-difference observation equation and the state equation to construct the speed measurement model.

[0065] In one embodiment of the present invention, constructing a velocity measurement model using an inter-satellite single-difference observation equation and a state equation includes:

[0066] The velocity measurement model is constructed using the second inter-satellite single-difference observation equation and the state equation: in, is the predicted speed of the carrier at time t, is the observation error including the tropospheric error, is the carrier velocity prediction error at time t, is the velocity error of the first observed satellite p at time t, is the velocity error of the second observation satellite q at time t, is the residual of the difference in the rates of change of the clock errors of the observed satellites p and q.

[0067] In the above velocity measurement model, for ease of processing, the tropospheric error is included in

[0068] In addition, the prediction information in the speed measurement model includes the carrier prediction speed. The pre-test residual error test quantity of the Doppler observation value derived from each group of satellites based on the prediction information in the speed measurement model includes:

[0069] Based on the carrier velocity prediction value, the observation value residual test quantity of the derived Doppler observation value is constructed for each group of satellites

[0070] Step S104: Detect and derive the gross error result of the Doppler observation value according to the compliance relationship between the pre-test residual error test amount of the observation value and the preset distribution or the size of the pre-test residual error test amount of the observation value.

[0071] Among them, the residual test quantity before the observation value includes the prior information of various errors. After the errors are processed, the corresponding residuals can be obtained. The prior information refers to the errors and error residual information after processing a large amount of observation information.

[0072] The preset distribution may be a normal distribution. In one embodiment of the present invention, based on the obedience relationship between the residual error test amount before the observation value and the preset distribution, the gross error result of the Doppler observation value is detected and derived, including:

[0073] The standardized test quantity is obtained by standardizing the residual test quantity before the observation value test

[0074] Specifically, the observed value pre-test residual test quantity is standardized to obtain the standardized test quantity include:

[0075] Obtain the prior information of various errors in the residual test quantity before the observation value test;

[0076] Among them, prior information refers to the error and error residual information after processing a large amount of observation information.

[0077] According to the prior information of each error, the mean error of the residual test quantity of the observed value is calculated based on the statistical characteristics of the error.

[0078] The standardized test quantity is obtained by standardizing the residual test quantity of the observed value before the test based on the mean error Where μ is the sample mean.

[0079] If the standardized test It obeys normal distribution, and the derived Doppler observations do not include gross errors;

[0080] If the standardized test It does not follow a normal distribution and the derived Doppler observations include gross errors.

[0081] It can be understood that if the observed value pre-test residual test amount sequence does not contain gross errors, it should obey the normal distribution. In order to detect the minimum gross error, in one embodiment of the present invention, according to the size of the observed value pre-test residual test amount, the gross error result of the Doppler observation value is detected and derived, including:

[0082] The standardized test quantity is obtained by standardizing the residual test quantity before the observation value test

[0083] If the standardized test The absolute value of is within a first preset threshold range, and the derived Doppler observation value includes a gross error.

[0084] Among them, it can be divided into three sections according to the size of the standardized test volume. The first is the normal section with a very small standardized test volume. The absolute value of is within the third preset threshold range, that is, The value range of k0 is 1 to 1.5. The second is the suspicious segment with a large standardized test volume. The absolute value of is within the second preset threshold range, that is The value range of k1 is 2.5~8; the third is the elimination stage with large standardized test volume. The absolute value of is within the first preset threshold range, that is

[0085] It is understandable that standardized test volume When it is in the elimination stage, it means that there are gross errors in the derived Doppler observations at this time. In order to avoid affecting the velocity accuracy, it can be deleted directly.

[0086] In addition, the derived Doppler observations of the suspicious segment can be downgraded. Specifically, the weight function of IGG III can be used to adjust the weight of the derived Doppler observations, where the weight adjustment formula is: R i is the original weight of the ith observation, is the equivalent weight factor, k0 and k1 are model parameters and have no actual physical meaning.

[0087] Among them, by adopting the IGGⅢ anti-error scheme to detect gross errors and adjusting the weights of the derived Doppler observation values ​​at the same time, gross errors less than one week can be detected and the speed measurement accuracy can be indicated.

[0088] Compared with the prior art, the method provided in this embodiment realizes the observation of multiple groups of satellites by acquiring the observation data of each group of satellites, thereby realizing multi-dimensional gross errors, and constructing the inter-satellite single-difference observation equation through the observation data, which can avoid errors; and constructing the state equation according to the smooth motion characteristics of the carrier to reduce the prediction error of the speed measurement model; finally, the speed measurement model is constructed through the observation equation and the state equation, and the gross error result of the observation value is detected according to the relationship between the pre-test residual test amount of the observation value and the preset distribution, so as to detect errors less than one week.

[0089] In addition, by adopting the IGGⅢ anti-error scheme to downweight the derived Doppler observation value weights, the reliability and accuracy of the speed measurement results are greatly improved.

[0090] In order to better implement the multidimensional gross error detection method in the embodiment of the present invention, based on the multidimensional gross error detection method, correspondingly, please refer to Figure 2 , Figure 2 This is a structural schematic diagram of an embodiment of a multidimensional gross error detection device provided by the present invention. The embodiment of the present invention provides a multidimensional gross error detection device 200, including: an observation equation construction module 201, a state equation construction module 202, a verification quantity construction module 203 and a gross error detection module 204.

[0091] An observation equation construction module 201 is used to obtain observation data of each group of satellites and construct an inter-satellite single-difference observation equation based on the observation data;

[0092] A state equation construction module 202 is used to obtain the steady motion characteristics of the carrier and construct a state equation based on the steady motion characteristics;

[0093] The test quantity construction module 203 is used to construct a velocity measurement model using the inter-satellite single difference observation equation and the state equation, and construct an observation value pre-test residual test quantity for deriving Doppler observation values ​​for each group of satellites based on the prediction information in the velocity measurement model;

[0094] The gross error detection module 204 is used to detect and derive the gross error result of the Doppler observation value according to the obedience relationship between the pre-test residual error check amount of the observation value and the preset distribution or the size of the pre-test residual error check amount of the observation value.

[0095] It should be noted here that: the device 200 provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above method embodiments, which will not be repeated here.

[0096] Based on the above-mentioned multidimensional gross error detection method, an embodiment of the present invention also provides an electronic device accordingly, including: a processor and a memory, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the steps in the multidimensional gross error detection method in the above-mentioned embodiments are implemented.

[0097] Figure 3 3 shows a schematic diagram of the structure of an electronic device 300 suitable for implementing the embodiment of the present invention. The electronic device in the embodiment of the present invention may include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0098] The electronic device includes: a memory and a processor, wherein the processor here may be referred to as a processing device 301 hereinafter, and the memory may include at least one of a read-only memory (ROM) 302, a random access memory (RAM) 303, and a storage device 308 hereinafter, as shown below:

[0099] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0100] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0101] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of the embodiment of the present invention are executed.

[0102] Based on the above-mentioned multidimensional gross error detection method, an embodiment of the present invention also provides a computer-readable storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps in the multidimensional gross error detection method in the above-mentioned embodiments.

[0103] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0104] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A multi-dimensional gross error detection method for GNSS, characterized in that: include: Acquire observation data of each group of satellites in GNSS, and construct an inter-satellite single-difference observation equation based on the observation data; Performing a preprocessing operation on the observation data to obtain a preprocessed carrier phase observation value; The first inter-satellite single-difference observation equation is constructed using the preprocessed carrier phase observation value: ； Constructing derived Doppler observations based on the preprocessed carrier phase observations; The second inter-satellite single-difference observation equation is constructed based on the derived Doppler observations: ； Acquiring a steady motion characteristic of the carrier, and constructing a state equation based on the steady motion characteristic; A velocity measurement model is constructed by using the inter-satellite single-difference observation equation and the state equation, and a pre-test residual error test quantity of an observation value for deriving a Doppler observation value is constructed for each group of satellites based on the prediction information in the velocity measurement model; The gross error result of the derived Doppler observation value is detected according to the compliance relationship between the pre-test residual check amount of the observation value and the preset distribution or the size of the pre-test residual check amount of the observation value.

2. The method according to claim 1, characterized in that The first intersatellite single-difference observation equation represents the single difference operator, is the wavelength, is the carrier phase observation value, For the receiver, For observation satellites, is the difference in carrier phase observations between satellites, is the distance between the receiver and the observation satellite, is the distance difference between the receiver and the two observed satellites, is the speed of light, For the clock error, For observation satellite The clock difference is is the integer ambiguity, For observation satellite The difference in the integer ambiguity of is the tropospheric delay, is the carrier phase observation noise; The second intersatellite single-difference observation equation for The difference in Doppler observations derived between satellites at time, For the station and the first observation satellite The direction cosines between For the station and the second observation satellite The direction cosines between for First observation satellite speed, Second observation satellite speed, for The carrier rover speed at the moment, for Observe satellites all the time The difference in the rate of change of tropospheric slant delay, is the carrier phase observation noise, For observation satellite The difference in the rate of change of the clock error.

3. The method according to claim 1, characterized in that The constructing of the velocity measurement model by using the inter-satellite single-difference observation equation and the state equation comprises: The velocity measurement model is constructed using the second inter-satellite single-difference observation equation and the state equation: ,in, for The predicted speed of the carrier at the moment, is the observation error including the tropospheric error, for The prediction error of carrier speed at time is the first observation satellite at time t Speed ​​error, for Second observation satellite Speed ​​error, For observation satellite The residual of the difference in the rates of change of the clock errors; The prediction information in the speed measurement model includes the predicted carrier speed, and the observation value pre-test residual error test quantity for constructing the derived Doppler observation value for each group of satellites based on the prediction information in the speed measurement model includes: Based on the carrier velocity prediction value, a pre-test residual error test quantity of the Doppler observation value derived from each group of satellites is constructed. : 。 4. The method according to claim 3, characterized in that Detecting the gross error result of the derived Doppler observation value according to the obedience relationship between the residual error test amount of the observation value before verification and the preset distribution includes: The observed value pre-test residual test quantity is standardized to obtain a standardized test quantity ; If the standardized test quantity The derived Doppler observations are subject to normal distribution and do not include gross errors; If the standardized test quantity The derived Doppler observations do not obey a normal distribution and include gross errors.

5. The method according to any one of claims 3 or 4, characterized in that: Detecting the gross error result of the derived Doppler observation value according to the size of the residual error test amount before the observation value verification includes: The observed value pre-test residual test quantity is standardized to obtain a standardized test quantity ; If the standardized test quantity If the absolute value of is within a first preset threshold range, the derived Doppler observation value includes a gross error.

6. The method according to claim 5, characterized in that The standardized test quantity is obtained by standardizing the residual test quantity before the observation value test ,include: Obtaining prior information of various errors in the residual test quantity of the observed value before the test; According to the prior information of the errors, the mean error of the residual test quantity of the observation value before the test is calculated based on the error statistical characteristics : ； The standardized test quantity is obtained by standardizing the residual test quantity of the observed value before the test based on the mean error : ,in, is the sample mean.

7. The method according to claim 6, characterized in that The method further comprises: According to the standardized test The absolute value is adjusted by using the weight function of IGG III to adjust the weight of the derived Doppler observation value; The weight adjustment formula is: ,in, For the The original weights of the observations, is the equivalent weight factor, , It is a model parameter and has no actual physical meaning.

8. A multi-dimensional gross error detection device, characterized in that: include: An observation equation construction module, used to obtain observation data of each group of satellites in GNSS, and construct an inter-satellite single-difference observation equation based on the observation data; wherein, the observation data is preprocessed to obtain a preprocessed carrier phase observation value; The first inter-satellite single-difference observation equation is constructed using the preprocessed carrier phase observation value: ； Constructing derived Doppler observations based on the preprocessed carrier phase observations; The second inter-satellite single-difference observation equation is constructed based on the derived Doppler observations: ； A state equation construction module, used for obtaining the smooth motion characteristics of the carrier and constructing the state equation based on the smooth motion characteristics; A test quantity construction module is used to construct a velocity measurement model using the inter-satellite single-difference observation equation and the state equation, and to construct an observation value pre-test residual test quantity for deriving Doppler observation values ​​for each group of satellites based on the prediction information in the velocity measurement model; The gross error detection module is used to detect the gross error result of the derived Doppler observation value according to the obedience relationship between the pre-test residual error check amount of the observation value and the preset distribution or the size of the pre-test residual error check amount of the observation value.

9. An electronic device, characterized in that: It includes a memory and a processor, wherein the memory is used to store programs; the processor is coupled to the memory and is used to execute the programs stored in the memory to implement the steps in the multidimensional gross error detection method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the multi-dimensional gross error detection method described in any one of claims 1 to 7.

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