GNSS observation value weighting method, positioning method, device, terminal and medium

Abstract

The present invention discloses a GNSS observation value weighting method, positioning method, device, terminal and medium, wherein the method comprises acquiring GNSS observation values ​​and processing them to obtain PLD and carrier phase single difference residual sequence of all epochs of each satellite; using carrier phase single difference residual sequence to characterize carrier phase accuracy, constructing observation value accuracy estimation formula according to the relationship between PLD and carrier phase accuracy, and then constructing weighting function based on PLD; weighting GNSS observation values ​​by weighting function based on PLD. PLD is not affected by atmospheric delay error and station environment, but is only related to satellite tracking state, has no time delay phenomenon, can effectively indicate cycle slip, can effectively make up for the shortcomings of current observation value quality evaluation index, and is very necessary and advantageous for data processing with high reliability and accuracy requirements nowadays.

Description

Technical Field

[0001] The present invention relates to the field of positioning technology, and in particular to a GNSS observation value weighting method based on PLD, a positioning method, a device, a terminal and a medium. Background Art

[0002] In many industries such as surveying and mapping, smart agriculture and autonomous driving, the current GNSS (Global Navigation Satellite System) positioning accuracy still cannot effectively meet their high-precision and high-reliability positioning needs. From the current status of high-precision GNSS positioning technology, GNSS is easily affected by objective conditions, which makes it difficult to meet application requirements in terms of stability, reliability, safety, cost, etc. For example, in shaded or strong multi-path environments such as buildings, glass curtain walls and elevated roads, GNSS signals are prone to loss of lock or frequent cycle slips, and positioning accuracy and reliability also decrease. The quality of GNSS observations and whether the impact of abnormal observations can be effectively detected, weakened or eliminated will directly determine the reliability and accuracy of the positioning results. Therefore, when performing high-precision positioning, it is necessary to reliably detect the quality of GNSS observations and determine the weight of observations.

[0003] In response to the above problems, a large number of scholars have carried out relevant research. Currently, there are mainly the following methods:

[0004] (1) Random model based on altitude angle. This random model refers to a random model determined by the satellite altitude angle. The satellite altitude angle itself has no effect on the observation value, but the influence of the atmospheric delay error on the signal propagation path on the observation value quality decreases with the increase of the altitude angle. Secondly, the influence of multipath error is also related to the satellite altitude angle.

[0005] (2) Random model based on carrier-to-noise ratio. This random model is to estimate the variance of the observation value using a random model determined by the carrier-to-noise ratio. This random model can effectively weaken the impact of multipath effect and diffraction error.

[0006] (3) Random model of altitude angle combined with carrier-to-noise ratio. In some environments, positioning accuracy may not be ideal when using a single random model. Therefore, some scholars have established a comprehensive weighting model based on satellite altitude angle and carrier-to-noise ratio.

[0007] The above methods have the following problems:

[0008] ① In an open environment, the higher the altitude angle, the better the observation quality. However, in a complex environment, the quality of GNSS observations is affected by factors such as occlusion, reflection and diffraction, and the positive correlation between the altitude angle and the quality of observations does not hold. In this case, this indicator cannot accurately indicate the quality of observations.

[0009] ② The output of the carrier-to-noise ratio has a certain delay, and its estimated smoothing period may reach 1 second; some receiver manufacturers also filter the output value of the carrier-to-noise ratio, so the carrier-to-noise ratio cannot fully and accurately reflect the quality of real-time observations; and when the carrier-to-noise ratio is low, it may be because the altitude angle is low rather than a cycle slip. It can be seen that there is a certain amount of misjudgment in the quality assessment of observations based on the carrier-to-noise ratio.

[0010] ③ The random model of altitude angle combined with carrier-to-noise ratio uses the actual satellite signal strength to constrain the weighted model based on satellite altitude angle. However, in some cases, neither altitude angle nor carrier-to-noise ratio can effectively indicate the quality of observations. Moreover, if the weights of each indicator are not determined correctly, the reliability and accuracy of the positioning results will also be affected. Summary of the invention

[0011] In view of the shortcomings of the above-mentioned prior art, the present invention provides a GNSS observation value weighting method, positioning method, device, terminal and medium. The PLD is not affected by atmospheric delay error and station environment, is only related to the satellite tracking status, does not have time delay phenomenon, and can effectively indicate cycle slips.

[0012] In a first aspect, a GNSS observation value weighting method is provided, comprising:

[0013] Obtain GNSS observations and process them to obtain the PLD and carrier phase single-difference residual sequence of all epochs of each satellite; PLD refers to the phase lock indication value;

[0014] The standard deviation of the carrier phase single-difference residual sequence is used to characterize the carrier phase accuracy. The observation value accuracy estimation formula is constructed based on the relationship between PLD and carrier phase accuracy, and then the weighting function based on PLD is constructed.

[0015] The GNSS observations are weighted using a PLD-based weighting function.

[0016] Furthermore, the phase lock indication value PLD is calculated by the following formula:

[0017]

[0018]

[0019]

[0020] Where k is the kth coherent integration, M is the time length of a coherent integration, i is the i-th moment in a coherent integration, and I i (t) = aD(t)cos(ω e t+θ e ),Q i (t) = aD(t)sin(ωe t+θ e ), I i is the in-phase signal at time i; Q i is the orthogonal signal at time i; a is the signal amplitude; D(t) is the data code modulated on the carrier; ω e is the carrier frequency difference between the input signal and the local replica signal; θ e is the initial phase difference between the input signal and the local replica signal, t is the corresponding moment of a coherent integration, and the time length of a coherent integration (i.e., M i moments) is coherently integrated to obtain the result corresponding to moment t.

[0021] Furthermore, the carrier phase single-difference residual sequence of each satellite is obtained by the following method:

[0022] The single-difference residual sequence of the carrier phase of a single satellite is calculated by the following formula:

[0023]

[0024] Where L is the carrier phase observation value; subscripts i and j represent the two receivers; a represents the common view satellite of the two receivers at a certain epoch; c is the speed of light in vacuum, and λ is the carrier wavelength; is the integer ambiguity; dT is the receiver clock error; is the single difference of the carrier phase noise of the two receivers for the current satellite a;

[0025] For m common-view satellites in one epoch, m-1 carrier phase double-difference residual sequences are obtained based on the corresponding m carrier phase single-difference residual sequences:

[0026]

[0027] In the formula, the superscripts DD and SD represent double difference and single difference, respectively. Represents the carrier phase double difference residual sequence of the 1st and mth satellite observation values, Represents the carrier phase single-difference residual sequence of the m-th satellite observation value;

[0028] In order to recover the carrier phase single difference residual sequence from the carrier phase double difference residual sequence, it is assumed that the mean of the carrier phase single difference residual sequence is 0, thus obtaining the following result:

[0029]

[0030] By solving the above formula, the carrier phase single-difference residual sequence of each satellite is obtained.

[0031] Furthermore, the standard deviation of the carrier phase single-difference residual sequence of each satellite is used to characterize its carrier phase accuracy, and the relationship between PLD and carrier phase accuracy is linearly fitted to obtain the observation value accuracy estimation formula, and then the PLD-based weight function is obtained. The PLD-based weight function is a relationship function with the observation value variance as the dependent variable and PLD as the independent variable.

[0032] In a second aspect, a navigation and positioning method is provided, comprising:

[0033] The weighting function based on PLD is obtained by using the GNSS observation value weighting method as described above;

[0034] GNSS navigation and positioning is realized using PLD-based weighting function.

[0035] In a third aspect, a GNSS observation value weighting device based on PLD is provided, comprising:

[0036] The data acquisition module is used to acquire and process GNSS observation values ​​to obtain the PLD and carrier phase single-difference residual sequence of all epochs of each satellite; PLD refers to the phase lock indication value;

[0037] A weighting function construction module is used to construct an observation value accuracy estimation formula based on the relationship between PLD and carrier phase accuracy, and then construct a weighting function based on PLD, where the carrier phase accuracy is represented by the standard deviation calculated by the carrier phase single-difference residual sequence;

[0038] The weighting module is used to weight the GNSS observation values ​​through a PLD-based weighting function.

[0039] In a fourth aspect, an electronic terminal is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the GNSS observation value weighting method or the navigation positioning method as described above are implemented.

[0040] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the GNSS observation value weighting method or the navigation positioning method as described above are implemented.

[0041] Beneficial Effects

[0042] The present invention proposes a GNSS observation value weighting method, positioning method, device, terminal and medium, and introduces PLD as an observation value quality evaluation index for the first time, which makes up for the shortcomings of the current use of altitude angle and carrier-to-noise ratio for observation value quality evaluation; it proposes a priori weighting random model based on PLD for the first time, which makes up for the shortcomings of the current random model based on altitude angle and carrier-to-noise ratio that cannot accurately indicate the quality of observation values ​​in real time. PLD is not affected by atmospheric delay errors and station environment, and is only related to the satellite tracking state. There is no time delay phenomenon, and it can effectively indicate cycle slips, and there is a correlation between PLD and the periodic change part of the carrier phase double difference residual. The scheme proposed by the present invention can effectively make up for the shortcomings of the current observation value quality evaluation index, which is very necessary and beneficial for today's data processing with high reliability and accuracy requirements, and is particularly suitable for high-precision positioning in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 is a flow chart of a GNSS observation value weighting method provided by an embodiment of the present invention;

[0045] Figure 2 (a) and (b) are the trend diagrams of the carrier phase accuracy of GPS L1 and BDS B1 frequency points with the change of PLD provided by the embodiment of the present invention.

[0046] Figure 3 Schematic diagrams of four typical environments provided by embodiments of the present invention, wherein (a) is an open environment, (b) is a tree shaded environment, (c) is a building shaded environment, and (d) is a glass curtain wall shaded environment. DETAILED DESCRIPTION

[0047] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0048] The altitude angle and carrier-to-noise ratio random models are widely used. However, the altitude angle is only related to the atmospheric delay error and cannot reflect the influence of the observation environment on the observation value. The carrier-to-noise ratio can reflect the multipath error and diffraction error to a certain extent, but its output has a certain delay. In view of the shortcomings of the prior art, the present invention proposes a GNSS observation value weighting method, positioning method, device, terminal and medium based on PLD (Phase Lock Detector). PLD is not affected by the atmospheric delay error and the station environment, but is only related to the satellite tracking state. There is no delay phenomenon, and it can effectively indicate the cycle slip. There is a correlation between PLD and the periodic change part of the carrier phase double difference residual. The scheme proposed by the present invention can effectively make up for the shortcomings of the current observation value quality evaluation index.

[0049] First, the PLD is explained. The phase lock indication value PLD is a numerical indicator used to indicate the signal tracking status. It is calculated from the output signals of the instantaneous branches of the in-phase branch (I branch) and the orthogonal branch (Q branch) of the phase-locked loop.

[0050] I i (t) = aD(t)cos(ω e t+θ e )

[0051] Q i (t) = aD(t)sin(ω e t+θ e )

[0052] Among them, I i is the in-phase signal at time i; Q i is the orthogonal signal at time i; a is the signal amplitude; D(t) is the data code modulated on the carrier; ω e is the carrier frequency difference between the input signal and the local replica signal; θ e is the initial phase difference between the input signal and the local replica signal. M refers to the time length of a coherent integration, i is the i-th moment in a coherent integration, t is the corresponding moment of a coherent integration, and the time length of a coherent integration (i.e., M i moments) is coherently integrated to obtain the result corresponding to moment t.

[0053]

[0054]

[0055]

[0056] Where k is the kth coherent integration.

[0057] Secondly, through in-depth analysis of the correlation between PLD and carrier phase accuracy, a weighted function is established later.

[0058] Specifically, in order to obtain the residual sequence reflecting a single satellite, the same satellite that is co-viewed by two receivers at a certain epoch is firstly subjected to inter-station single difference, thereby obtaining the single-difference residual sequence of the carrier phase of a single satellite:

[0059]

[0060] Where L is the carrier phase observation value; subscripts i and j represent the two receivers; a represents the common view satellite of the two receivers at a certain epoch; c is the speed of light in vacuum, and λ is the carrier wavelength; is the integer ambiguity; dT is the receiver clock error; is the single difference of the carrier phase noise of the two receivers for the current satellite a.

[0061] From the above formula, we can see that only the internal noise of the receiver is eliminated in the single difference residual sequence. Therefore, in order to obtain a single difference residual sequence that eliminates other errors, it is necessary to continue to use the above carrier phase single difference residual sequence for difference. Assuming that there are m common-view satellites in a certain epoch, the corresponding m carrier phase single difference residual sequences are subtracted to obtain m-1 carrier phase double difference residual sequences:

[0062]

[0063] In the formula, the superscripts DD and SD represent double difference and single difference, respectively. Represents the carrier phase double difference residual sequence of the 1st and mth satellite observation values, Represents the carrier phase single-difference residual sequence of the m-th satellite observation value.

[0064] In order to recover the carrier phase single difference residual sequence from the carrier phase double difference residual sequence, it is assumed that the mean of the carrier phase single difference residual sequence is 0, thus obtaining the following result:

[0065]

[0066] By solving the above equation, we can obtain the single-difference residual sequence of the carrier phase of each satellite. The single-difference residual only eliminates the internal noise of the receiver, but also contains other errors. The double-difference residual contains the combined effect of the two satellites, but eliminates other errors. The single-difference residual recovered from the double-difference residual only contains the residual of a single satellite and eliminates other errors. The standard deviation calculated by the carrier phase single-difference residual sequence is used to characterize the carrier phase accuracy, so that the carrier phase accuracy analysis of a single satellite can be realized.

[0067] Figure 2As shown in the figure, the carrier phase accuracy of GPS L1 and BDS B1 frequency points changes with PLD. It can be seen from the figure that the carrier phase accuracy of GPS L1 and BDS B1 frequency points gradually decreases with the increase of PLD, but their change trends are not completely consistent. Therefore, it is impossible to use the same function model for GPS L1 and BDS B1 frequency points. It is necessary to establish a random model of each GPS frequency point based on PLD (i.e., a fixed weight function) and a random model of each BDS frequency point in turn.

[0068] Based on the above in-depth analysis of the correlation between PLD and carrier phase accuracy, an embodiment of the present invention provides a GNSS observation value weighting method, such as Figure 1 As shown, including:

[0069] S1: Obtain GNSS observations and process them to obtain the PLD and carrier phase single-difference residual sequence of all epochs of each satellite; PLD refers to the phase lock indication value;

[0070] S2: The standard deviation of the carrier phase single-difference residual sequence is used to characterize the carrier phase accuracy. The observation value accuracy estimation formula is constructed based on the relationship between PLD and carrier phase accuracy, and then the PLD-based weighting function is constructed.

[0071] S3: Weight the GNSS observations using a PLD-based weighting function.

[0072] In this embodiment, the GPS L1 frequency point and the BDS B1 frequency point are taken as examples for explanation. Figure 2 The figure shows the trend of carrier phase accuracy of GPS L1 and BDSB1 frequency points as a function of PLD. By linear fitting and converting the standard deviation into variance, the weighting function of GPS L1 frequency point and BDS B1 frequency point can be obtained:

[0073] σ G =0.001224×PLD 0.5031

[0074] σ C =-0.04731×PLD -0.1916 +0.03482

[0075] Among them, σ G , σ C are the variances of GPS and BDS observations respectively. When determining the weight, the weight is the inverse of the variance of the observation.

[0076] The embodiment of the present invention also provides a navigation and positioning method, including:

[0077] The weighting function based on PLD is obtained by using the GNSS observation value weighting method as described above;

[0078] GNSS navigation and positioning is realized using PLD-based weighting function.

[0079] The specific process of realizing GNSS navigation positioning when the weight function (and the random model) is determined can adopt the existing method, which is not the focus of the present invention and will not be further described here.

[0080] An embodiment of the present invention provides a GNSS observation value weighting device based on PLD, comprising:

[0081] The data acquisition module is used to acquire and process GNSS observation values ​​to obtain the PLD and carrier phase single-difference residual sequence of all epochs of each satellite; PLD refers to the phase lock indication value;

[0082] A weighting function construction module is used to construct an observation value accuracy estimation formula based on the relationship between PLD and carrier phase accuracy, and then construct a weighting function based on PLD, where the carrier phase accuracy is represented by the standard deviation calculated by the carrier phase single-difference residual sequence;

[0083] The weighting module is used to weight the GNSS observation values ​​through a PLD-based weighting function.

[0084] It should be understood that the functional unit modules in this embodiment can be concentrated in one processing unit, or each unit module can exist physically separately, or two or more unit modules can be integrated in one unit module, and can be implemented in the form of hardware or software.

[0085] An embodiment of the present invention provides an electronic terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the GNSS observation value weighting method or the navigation positioning method as described above when executing the computer program.

[0086] The electronic terminal also includes: a communication interface for communicating with external equipment and performing data interactive transmission.

[0087] The memory may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0088] If the memory, processor and communication interface are implemented independently, the memory, processor and communication interface can be connected to each other through a bus and communicate with each other. The bus can be an industrial standard architecture bus, a peripheral device interconnection bus or an extended industrial standard architecture bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc.

[0089] Optionally, in a specific implementation, if the memory, processor and communication interface are integrated on a chip, the memory, processor and communication interface can communicate with each other through an internal interface.

[0090] For the specific implementation process of each step, please refer to the description of the above method.

[0091] It should be understood that in the embodiments of the present invention, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the type of device.

[0092] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the GNSS observation value weighting method or the navigation positioning method as described above.

[0093] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0094] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0095] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0096] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0097] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0098] In order to verify the feasibility of the solution provided by the present invention, firstly, the GNSS antenna is placed as follows: Figure 3 In the typical environments shown in the figure, GNSS observation data is collected at a frequency of 1Hz in open space, shaded by trees, blocked by buildings, and blocked by glass curtain walls. Then, the PLD, elevation angle, and carrier-to-noise ratio random model are used to perform dual-system single-frequency point (GPS L1, BDS B1) relative positioning solution. The experimental results in different environments are shown in the following table.

[0099]

[0100]

[0101] The experimental results show that the fixed solution ratio of the random model weight determination method based on PLD is 15% to 19.4% higher than that of the other two random models. The STD (Standard Deviation) and RMS (Root Mean Square) in three directions are the best overall, generally 0.06 to 0.20 cm higher than other random models, and only the STD in the N direction is 0.01 to 0.06 cm higher than that of the other two random models. It can be seen that the random model proposed by the present invention effectively improves the reliability and accuracy of the positioning results.

[0102] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for determining weights of GNSS observation values, characterized in that: include: Obtain GNSS observations and process them to obtain the PLD and carrier phase single-difference residual sequence of all epochs of each satellite; PLD refers to the phase lock indication value; The standard deviation of the carrier phase single-difference residual sequence is used to characterize the carrier phase accuracy. The observation value accuracy estimation formula is constructed based on the relationship between PLD and carrier phase accuracy, and then the weighting function based on PLD is constructed. The GNSS observations are weighted by a PLD-based weighting function; The carrier phase single-difference residual sequence of each satellite is obtained by the following method: The single-difference residual sequence of the carrier phase of a single satellite is calculated by the following formula: Where L is the carrier phase observation value; subscripts i and j represent the two receivers; a represents the common view satellite of the two receivers at a certain epoch; c is the speed of light in vacuum, and λ is the carrier wavelength; is the integer ambiguity; dT is the receiver clock error; is the single difference of the carrier phase noise of the two receivers for the current satellite a; For m common-view satellites in one epoch, m-1 carrier phase double-difference residual sequences are obtained based on the corresponding m carrier phase single-difference residual sequences: In the formula, the superscripts DD and SD represent double difference and single difference, respectively. Represents the carrier phase double difference residual sequence of the 1st and mth satellite observation values, Represents the carrier phase single-difference residual sequence of the m-th satellite observation value; In order to recover the carrier phase single difference residual sequence from the carrier phase double difference residual sequence, it is assumed that the mean of the carrier phase single difference residual sequence is 0, thus obtaining the following result: By solving the above formula, the carrier phase single-difference residual sequence of each satellite is obtained.

2. The GNSS observation value weighting method according to claim 1, characterized in that: The phase lock indication value PLD is calculated by the following formula: Where k is the kth coherent integration, M is the time length of a coherent integration, i is the i-th moment in a coherent integration, and I i (t) = aD(t)cos(ω e t+θ e ),Q i (t) = aD(t)sin(ω e t+θ e ), I i is the in-phase signal at time i; Q i is the orthogonal signal at time i; a is the signal amplitude; D(t) is the data code modulated on the carrier; ω e is the carrier frequency difference between the input signal and the local replica signal; θ e is the initial phase difference between the input signal and the local replica signal, and t is the corresponding time of a coherent integration.

3. The GNSS observation value weighting method according to claim 1, characterized in that: The standard deviation of the carrier phase single-difference residual sequence of each satellite is used to characterize its carrier phase accuracy. The relationship between PLD and carrier phase accuracy is linearly fitted to obtain the observation value accuracy estimation formula, and then the weight function based on PLD is obtained.

4. A navigation positioning method, characterized in that: include: A weighting function based on PLD is obtained by adopting the GNSS observation value weighting method as described in any one of claims 1 to 3; GNSS navigation and positioning is realized using PLD-based weighting function.

5. A GNSS observation value weighting device, characterized in that: include: The data acquisition module is used to acquire and process GNSS observation values ​​to obtain the PLD and carrier phase single-difference residual sequence of all epochs of each satellite; PLD refers to the phase lock indication value; A weighting function construction module is used to construct an observation value accuracy estimation formula based on the relationship between PLD and carrier phase accuracy, and then construct a weighting function based on PLD, where the carrier phase accuracy is represented by the standard deviation calculated by the carrier phase single-difference residual sequence; A weighting module, used to weight GNSS observations using a PLD-based weighting function; The carrier phase single-difference residual sequence of each satellite is obtained by the following method: The single-difference residual sequence of the carrier phase of a single satellite is calculated by the following formula: Where L is the carrier phase observation value; subscripts i and j represent the two receivers; a represents the common view satellite of the two receivers at a certain epoch; c is the speed of light in vacuum, and λ is the carrier wavelength; is the integer ambiguity; dT is the receiver clock error; is the single difference of the carrier phase noise of the two receivers for the current satellite a; For m common-view satellites in one epoch, m-1 carrier phase double-difference residual sequences are obtained based on the corresponding m carrier phase single-difference residual sequences: In the formula, the superscripts DD and SD represent double difference and single difference, respectively. Represents the carrier phase double difference residual sequence of the 1st and mth satellite observation values, Represents the carrier phase single-difference residual sequence of the m-th satellite observation value; In order to recover the carrier phase single difference residual sequence from the carrier phase double difference residual sequence, it is assumed that the mean of the carrier phase single difference residual sequence is 0, thus obtaining the following result: By solving the above formula, the carrier phase single-difference residual sequence of each satellite is obtained.

6. An electronic terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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