A method for confirming narrow-lane fixed ambiguity and a positioning method based on GNSS

Abstract

The embodiments of the present application provide a method for confirming narrow-lane fixed ambiguity and a positioning method based on GNSS, which can correctly verify the searched narrow-lane fixed ambiguity, improve the reliability of the narrow-lane fixed ambiguity, and further improve the positioning accuracy. The method for confirming the narrow-lane fixed ambiguity includes: obtaining the narrow-lane fixed ambiguity of the current epoch; determining whether the external inspection ambiguity data conforms to the external consistency with the narrow-lane fixed ambiguity, and / or determining whether the self-inspection ambiguity data conforms to the internal consistency with the narrow-lane fixed ambiguity; wherein, the external inspection ambiguity data includes the first wide-lane fixed ambiguity of the current epoch and / or the narrow-lane fixed ambiguity of the previous epoch, and the self-inspection ambiguity data includes the second wide-lane fixed ambiguity, and / or the ionosphere-free fixed ambiguity, and / or a subset of the narrow-lane fixed ambiguity; when the internal consistency and / or the external consistency is met, it is confirmed that the narrow-lane fixed ambiguity is correct.

Description

Technical Field

[0001] This application belongs to the field of wireless communication, and particularly relates to a method for confirming narrow-lane fixed ambiguity and a positioning method based on the Global Navigation Satellite System (GNSS). Background Art

[0002] In multi-frequency multi-system real-time kinematic (RTK) positioning, narrow-lane ambiguity resolution is the key to achieving high-precision positioning. Since the original carrier wavelength of the observed data is short and is easily affected by factors such as measurement noise, multipath, and atmospheric residual errors, how to quickly and accurately search for the double-difference narrow-lane ambiguity has become the core problem of RTK high-precision positioning. At the same time, in narrow-lane ambiguity resolution, it also includes the confirmation of narrow-lane fixed ambiguity to determine whether the searched narrow-lane ambiguity is accurate.

[0003] In the prior art, the Least-squares Ambiguity Decorrelation (LAMBDA) method is the most widely used search method at present due to its excellent characteristics such as strict theory and high search efficiency. At the same time, the confirmation of narrow-lane fixed ambiguity generally starts from the perspective of hypothesis testing and determines whether the searched narrow-lane ambiguity can be accepted according to different indicators.

[0004] In multi-frequency multi-system RTK positioning, the number of ambiguity dimensions that can be fixed is extremely high. If all ambiguity data are searched using LAMBDA, its search efficiency will be greatly reduced. This not only requires sufficient computing power support from the hardware, but also increases the difficulty of successful high-dimensional ambiguity search, and the search success rate is relatively low. At the same time, due to objective reasons such as the observation error not conforming to the normal distribution and the deviation of the floating-point solution filtering, it is very easy to lead to the inability to accurately check whether the narrow-lane fixed ambiguity is correct, affecting the reliability of the positioning narrow-lane fixed ambiguity, and thus reducing the positioning accuracy. Summary of the Invention

[0005] The embodiments of this application provide a method for confirming narrow-lane fixed ambiguity and a positioning method based on GNSS, which can correctly verify the searched narrow-lane fixed ambiguity, improve the reliability of the narrow-lane fixed ambiguity, and thus improve the positioning accuracy.

[0006] In a first aspect, the embodiments of this application provide a method for confirming narrow-lane fixed ambiguity, and the method includes:

[0007] Obtain the narrow-lane fixed ambiguity of the current epoch;

[0008] Determine whether the externally measured ambiguity data conforms to the external consistency with the narrow-lane fixed ambiguity, and / or determine whether the self-measured ambiguity data conforms to the internal consistency with the narrow-lane fixed ambiguity; wherein, the externally measured ambiguity data includes the first wide-lane fixed ambiguity of the current epoch and / or the narrow-lane fixed ambiguity of the previous epoch, and the self-measured ambiguity data includes the second wide-lane fixed ambiguity, and / or the ionosphere-free fixed ambiguity, and / or a subset of the narrow-lane fixed ambiguities; wherein, both the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity are obtained by transforming the narrow-lane fixed ambiguity, and the subset of the narrow-lane fixed ambiguities is a set of narrow-lane fixed ambiguities corresponding to target satellites, and the target satellites are part of the satellite set corresponding to the narrow-lane fixed ambiguity;

[0009] When the internal consistency and / or the external consistency is met, confirm that the narrow-lane fixed ambiguity is correct.

[0010] In a second aspect, an embodiment of the present application provides a positioning method based on the Global Navigation Satellite System (GNSS), and the method includes:

[0011] Determine observation data according to the satellite signals received by a multi-frequency multi-system Global Navigation Satellite System (GNSS) receiver;

[0012] Perform Kalman filtering on the observation data based on a target observation equation to determine the narrow-lane floating-point ambiguity;

[0013] Based on the Least-Squares Ambiguity Decorrelation Adjustment (LAMBDA) algorithm, search for the narrow-lane floating-point ambiguity to determine the narrow-lane fixed ambiguity of the current epoch;

[0014] Confirm the narrow-lane fixed ambiguity according to the confirmation method of the narrow-lane fixed ambiguity provided in the first aspect of the embodiment of the present application;

[0015] Perform positioning according to the confirmed narrow-lane fixed ambiguity.

[0016] In a third aspect, an embodiment of the present application provides a device for confirming a narrow-lane fixed ambiguity, and the device includes:

[0017] An acquisition unit, configured to acquire the narrow-lane fixed ambiguity of the current epoch;

[0018] A processing unit, configured to determine whether the externally detected ambiguity data conforms to the external consistency with the narrow-lane fixed ambiguity, and / or determine whether the self-detected ambiguity data conforms to the internal consistency with the narrow-lane fixed ambiguity; wherein, the externally detected ambiguity data includes the first wide-lane fixed ambiguity of the current epoch and / or the narrow-lane fixed ambiguity of the previous epoch, and the self-detected ambiguity data includes the second wide-lane fixed ambiguity, and / or the ionosphere-free fixed ambiguity, and / or a subset of the narrow-lane fixed ambiguities; wherein, both the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity are obtained by transforming the narrow-lane fixed ambiguity, and the subset of the narrow-lane fixed ambiguities is a set of the narrow-lane fixed ambiguities corresponding to the target satellites, and the target satellites are part of the satellites in the satellite set corresponding to the narrow-lane fixed ambiguity;

[0019] A determination unit, configured to confirm that the narrow-lane fixed ambiguity is correct when the internal consistency and / or the external consistency is satisfied.

[0020] In a fourth aspect, an embodiment of the present application provides a positioning device based on a Global Navigation Satellite System (GNSS), where the device includes:

[0021] A receiving unit, configured to determine observation data according to the satellite signals received by a multi-frequency multi-system Global Navigation Satellite System (GNSS) receiver;

[0022] A filtering unit, configured to perform Kalman filtering on the observation data based on a target observation equation to determine a narrow-lane floating-point ambiguity;

[0023] A searching unit, configured to search for the narrow-lane floating-point ambiguity based on the Least-Squares Ambiguity Decorrelation Adjustment (LAMBDA) algorithm to determine the narrow-lane fixed ambiguity of the current epoch;

[0024] A determination unit, configured to confirm the narrow-lane fixed ambiguity according to the method for confirming the narrow-lane fixed ambiguity provided in the first aspect of the embodiment of the present application;

[0025] A positioning unit, configured to perform positioning according to the confirmed narrow-lane fixed ambiguity.

[0026] In a fifth aspect, an embodiment of the present application provides a positioning device based on a Global Navigation Satellite System (GNSS), where the device includes:

[0027] A processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the method for confirming the narrow-lane fixed ambiguity provided in the first aspect of the embodiment of the present application and the positioning method based on a Global Navigation Satellite System (GNSS) provided in the second aspect.

[0028] Sixth aspect, an embodiment of the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method for confirming narrow-lane fixed ambiguity provided in the first aspect of the embodiment of the present application and the positioning method based on the global navigation satellite system GNSS provided in the second aspect are implemented.

[0029] The method for confirming narrow-lane fixed ambiguity and the positioning method based on GNSS provided in the embodiment of the present application determine the data consistency with the narrow-lane fixed ambiguity according to the externally detected ambiguity data and the self-detected ambiguity data, so as to confirm whether the narrow-lane fixed ambiguity is correct. By establishing multiple verification strategies based on the externally detected ambiguity data and the self-detected ambiguity data, the correctness of the narrow-lane fixed ambiguity is confirmed from multiple aspects, improving the reliability of the narrow-lane fixed ambiguity and thus improving the positioning accuracy. Description of the Drawings

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0031] Figure 1 It is a schematic flowchart of a method for confirming narrow-lane fixed ambiguity provided by an embodiment of the present application;

[0032] Figure 2 It is a schematic flowchart of a positioning method based on the global navigation satellite system GNSS provided by an embodiment of the present application;

[0033] Figure 3 It is a schematic flowchart of a method for searching narrow-lane floating-point ambiguity provided by an embodiment of the present application;

[0034] Figure 4 It is a schematic structural diagram of a device for confirming narrow-lane fixed ambiguity provided by an embodiment of the present application;

[0035] Figure 5 It is a schematic structural diagram of a positioning device based on the global navigation satellite system GNSS provided by an embodiment of the present application;

[0036] Figure 6 It is a schematic structural diagram of a positioning device based on the global navigation satellite system GNSS provided by an embodiment of the present application. Detailed Embodiments

[0037] The features and exemplary embodiments of various aspects of the present application will be described in detail below. To make the objectives, technical solutions, and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application and not to limit the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0038] It should be noted that in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0039] In the Global Navigation Satellite System (GNSS), there are the Global Positioning System (GPS), the Global Navigation Satellite System (GLONASS), the Galileo satellite navigation system, and the BeiDou Navigation Satellite System (BDS). The regional satellite navigation and positioning system also includes the quasi-zenith satellite system (QZSS) and the Indian regional navigational satellite system (IRNSS). Currently, the total number of on-orbit satellites in these navigation satellite systems has exceeded 100, and the number of observable satellites in the open environment in the Chinese region has exceeded 40. Thus, even in some occluded environments, GNSS users can observe enough satellites to achieve high-precision positioning. In addition, each satellite navigation system broadcasts observation signals on multiple frequency bands to help users achieve reliable high-precision positioning. With the construction, improvement, and modernization of various satellite navigation and positioning systems, not only professional users are widely using multi-frequency and multi-system satellite navigation and positioning, but also a large number of consumer users are gradually moving from single-frequency and single-system to multi-frequency and multi-system. In the future, the GNSS industry ecosystem will surely develop in the direction of multi-frequency and multi-system compatibility and coexistence.

[0040] In the multi-frequency and multi-system real-time kinematic (RTK) positioning technology, the double-difference carrier ambiguity resolution is the key to achieving high-precision RTK positioning. Since the original wavelength of the carrier is short and it is easily affected by factors such as measurement noise, multipath, and atmospheric residual errors, how to quickly and accurately search for the ambiguity has become the core issue of high-precision RTK positioning. Generally speaking, the ambiguity search can be divided into the code-phase combination method for searching in the observation value domain, the ambiguity function method for searching in the coordinate domain, and the least-squares ambiguity search method for searching in the ambiguity domain. Among them, the Least-squares Ambiguity Decorrelation (LAMBDA) method is currently the most widely used ambiguity search method due to its excellent characteristics such as strict theory and high search efficiency.

[0041] In an open environment, the number of ambiguity dimensions that can actually participate in fixing in multi-frequency and multi-system GNSS has exceeded 60 dimensions. For such a high-dimensional ambiguity, if all ambiguities are searched using the LAMBDA method, the search efficiency will be greatly reduced. This not only requires sufficient computing power support from the hardware, but also increases the difficulty of successfully searching for high-dimensional ambiguities. Especially when there are observation errors in the searched carrier phase observations, it is very likely that the ambiguity cannot be searched or a wrong ambiguity is searched. Therefore, the idea of fixing some ambiguities must be introduced in the ambiguity resolution of multi-frequency and multi-system GNSS. On the one hand, fixing some ambiguities can reduce the search dimension of the ambiguity, reduce the computational complexity of the algorithm, and improve the search efficiency; on the other hand, it can improve the success rate of ambiguity search and increase the ambiguity fixing rate.

[0042] In ambiguity resolution, in addition to ambiguity search, there is another key technology, namely ambiguity validation. Generally speaking, ambiguity validation starts from the perspective of hypothesis testing and determines whether the searched ambiguity can be accepted according to different criteria. At present, ambiguity validation methods can be mainly divided into two categories: one is the discriminant test method based on the statistical distinguishability between the optimal and sub-optimal ambiguity sets; the other is the decision-making method based on the success rate / failure rate index under the theoretical framework of ambiguity estimation. Both of these ambiguity validation methods are based on ideal hypothesis testing. In practical applications, due to objective reasons such as the observation errors not conforming to the normal distribution and the deviation in float solution filtering, it is very easy to lead to the inability to accurately check whether the ambiguity is fixed correctly. Once the ambiguity is fixed incorrectly, errors of decimeter or even meter level will be generated, which is unacceptable for high-precision positioning users. Therefore, a complete set of ambiguity validation methods and systems must be available, which requires proposing some more reliable and accurate ambiguity validation methods based on the existing ambiguity validation.

[0043] For the resolution of fixed ambiguities, the following several solutions are provided in the existing technology:

[0044] Solution 1: Ambiguity Fixing Method, Device and Storage Medium

[0045] Based on the double-difference observation equations of the observation value groups of the reference station and the rover station, and using the Kalman filter to calculate the double-difference float ambiguity and variance-covariance information; judging whether the initialization is successful according to information such as the ambiguity dilution of precision ADOP, the filtering time, and the rounding error of the float solution; when the initialization is successful, directly rounding to obtain the fixed ambiguity, and when the initialization is not successful, using the LAMBDA algorithm to search for the fixed ambiguity; when the ambiguity is fixed, calculating the fixed solution using integer least squares.

[0046] The core of this technical solution lies in judging whether the current filtering ambiguity is successfully initialized according to some indicators. This solution is only applicable to the case of good observables, but has a poor effect in an occluded environment. At the same time, it does not elaborate in depth on how to select the ambiguity when fixing the rapid ambiguity and searching for the ambiguity through the LAMBDA algorithm, nor on how to confirm whether the ambiguity is correct.

[0047] Solution 2: A method for resolving GNSS dual-frequency carrier phase integer ambiguity

[0048] Calculate the floating-point solution of the wide-lane ambiguity through the MW combination, and calculate its variance through the error propagation law. The wide-lane ambiguity is fixed by rounding or LAMBDA search; use the Kalman filter to resolve the ionosphere-free floating-point ambiguity; transform the narrow-lane floating-point ambiguity through the fixed wide-lane ambiguity and the filtered ionosphere-free ambiguity, and use the LAMBDA search to fix the narrow-lane ambiguity; finally, calculate the position fixed solution according to the fixed narrow-lane ambiguity.

[0049] This technical solution focuses on the ambiguity resolution steps, does not clarify how to select some ambiguities for LAMBDA search, nor does it mention how to judge whether the ambiguity is correctly searched after the ambiguity search.

[0050] Solution 3: A method and device for delaying the partial ambiguity fixing of residuals

[0051] Establish a basic double-difference equation for Kalman filtering and calculate the a posteriori residuals after filtering; select excellent observables according to the a posteriori residuals, establish an excellent double-difference equation set based on the excellent observables, and update the filter; perform partial ambiguity fixing on the ambiguities of the selected excellent observables; use the fixed partial ambiguities to constrain the filter to obtain partially fixed ambiguities.

[0052] This technical solution proposes a method for partial ambiguity fixing, which can solve the problem of ambiguity search to a certain extent, but the method is still relatively single, has limited environmental adaptability, and does not discuss ambiguity confirmation either.

[0053] Solution 4: A method and device for fixing carrier phase ambiguity, and a satellite navigation receiver

[0054] Establish an inter-receiver inter-satellite double-difference observation equation, and the unknowns of the inter-receiver inter-satellite double-difference observation equation need to include a single-frequency ambiguity and at least one wide-lane ambiguity; perform Kalman filtering to resolve the floating-point solutions of the wide-lane ambiguity and the single-frequency ambiguity; fix the integer ambiguities of the floating-point solutions of the wide-lane ambiguity and the single-frequency ambiguity.

[0055] This technical solution mainly addresses the impact of ionospheric residuals on ambiguity fixation. It has a mediocre effect on solving high-dimensional ambiguity search and ambiguity search in complex environments. At the same time, the issue of ambiguity confirmation and verification is not discussed.

[0056] Solution Five: A Multi-Constellation GNSS Fusion High-Precision Dynamic Positioning Method under Complex Environmental Conditions

[0057] This technical solution uses the error ratio ratio value and the distance between the floating-point ambiguity and the optimal integer ambiguity as the judgment indicators to select the optimal ambiguity subset, and then performs ambiguity fixation only based on the optimal subset. This solution only focuses on the selection of the ambiguity subset and does not consider combining the two parts of ambiguity search and ambiguity confirmation.

[0058] Solution Six: A Method and Device for Fixing Partial Ambiguities

[0059] This technical solution mainly emphasizes constructing certain rule strategies, that is, using the elevation angle to select the strategy in the selection of the partial ambiguity fixation subset. According to the order of this strategy, the ambiguities are eliminated to ensure that the selected subset is optimal, and the partial ambiguities of the subset are fixed. This single strategy idea cannot guarantee the success rate and correctness of ambiguity search.

[0060] In summary, there are the following problems in various ambiguity resolution schemes in the prior art:

[0061] 1. Traditional ambiguity search methods directly search all ambiguities or only select some partial ambiguities for fixation through some empirical indicators. These single ambiguity search strategies are difficult to adapt to various user scenarios. For example, in an open environment, the ambiguity dimension of multi-frequency and multi-system has exceeded 60 dimensions, and the search efficiency is extremely low; in a complex and severely occluded environment, due to the influence of multipath on some satellites, the double-difference ambiguity integer characteristics are poor, and it is difficult for traditional methods to search for the correct ambiguity at this time.

[0062] 2. Due to poor observation quality in a harsh environment and the loss of some covariance information in the fixation of partial ambiguities, the ambiguities searched are very likely to be fixed incorrectly. The existing public technologies verify the ambiguity fixation based on some single indicators and do not have a relatively perfect systematic verification method, so the risk of incorrect ambiguity fixation is relatively high.

[0063] In view of the above-mentioned disadvantages of the prior art, the embodiments of the present application provide a method for confirming the narrow-lane fixed ambiguity, which adopts an adaptive partial ambiguity fixing strategy from easy to difficult, comprehensively considers information such as satellite elevation angle, carrier-to-noise ratio, cycle slip ratio, carrier tracking time, filtering residuals, multipath flag, etc., selects various ambiguity subsets from multiple dimensions to participate in the narrow-lane ambiguity search and fixation, and improves the search success rate of the narrow-lane ambiguity. At the same time, a variety of ambiguity verification strategies are comprehensively adopted to confirm the searched ambiguity, including a set of verification strategies constructed by some strongly correlated empirical parameters, the consistency verification of the narrow-lane and wide-lane searched ambiguities, the consistency verification of the currently searched and previously maintained ambiguities, the verification of the back-calculated wide-lane and ionosphere-free combination equations, and the positioning distance verification of satellite-by-satellite rejection.

[0064] The following will combine the accompanying drawings to provide a detailed description of the method for confirming the narrow-lane fixed ambiguity provided by the embodiments of the present application.

[0065] As Figure 1 shown, the embodiments of the present application provide a method for confirming the narrow-lane fixed ambiguity, and the method includes:

[0066] S101, obtain the narrow-lane fixed ambiguity of the current epoch.

[0067] It should be noted that the narrow-lane fixed ambiguity is determined based on the search of the narrow-lane floating-point ambiguity. Among them, the floating-point ambiguity is a plurality of floating-point ambiguity subsets selected from loose to tight based on multiple dimensions by comprehensively considering information such as satellite elevation angle, carrier-to-noise ratio, cycle slip ratio, carrier tracking time, filtering residuals, multipath flag, etc. The specific search process of the narrow-lane floating-point ambiguity can be specifically described below Figure 3 and will not be elaborated here.

[0068] S102, determine whether the external verification ambiguity data is in line with the external consistency with the narrow-lane fixed ambiguity, and / or determine whether the self-verification ambiguity data is in line with the internal consistency with the narrow-lane fixed ambiguity.

[0069] Among them, the external verification ambiguity data includes the first wide-lane fixed ambiguity of the current epoch and / or the narrow-lane fixed ambiguity of the previous epoch, and the self-verification ambiguity data includes the second wide-lane fixed ambiguity, and / or the ionosphere-free fixed ambiguity, and / or the narrow-lane fixed ambiguity subset; among them, both the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity are obtained by transforming the narrow-lane fixed ambiguity, and the narrow-lane fixed ambiguity subset is a set of narrow-lane fixed ambiguities corresponding to the target satellites, and the target satellites are part of the satellite set corresponding to the narrow-lane fixed ambiguity.

[0070] It should be noted that the externally detected ambiguity data is the ambiguity data directly obtained through other channels, such as: the first wide-lane fixed ambiguity of the current epoch, the narrow-lane fixed ambiguity of the previous epoch. The self-detected ambiguity data is the ambiguity data obtained through relevant calculation and transformation based on the narrow-lane fixed ambiguity of the current epoch, such as: the narrow-lane fixed ambiguity subset, the ionosphere-free fixed ambiguity, the second wide-lane fixed ambiguity.

[0071] S103. When the internal consistency and / or external consistency is met, confirm that the narrow-lane fixed ambiguity is correct.

[0072] The method for confirming the narrow-lane fixed ambiguity provided by the embodiment of the present application first obtains the narrow-lane fixed ambiguity of the current epoch, then based on the externally detected ambiguity data and / or the self-detected ambiguity data, establishes multiple ambiguity verification detections to confirm the above narrow-lane fixed ambiguity, and finally when the externally detected ambiguity data and the narrow-lane fixed ambiguity meet the external consistency, and / or, when the self-detected ambiguity data and the narrow-lane fixed ambiguity meet the internal consistency, confirm that the above narrow-lane fixed ambiguity is correct. Compared with the prior art, by checking the data consistency between the externally detected ambiguity data and the self-detected ambiguity data and the narrow-lane fixed ambiguity respectively, and using multiple methods to confirm the accuracy of the narrow-lane fixed ambiguity, the error risk of the narrow-lane fixed ambiguity is reduced, and thus the positioning accuracy is improved.

[0073] In some embodiments, when the externally detected ambiguity data includes the first wide-lane fixed ambiguity of the current epoch, determining whether the externally detected ambiguity data and the narrow-lane fixed ambiguity meet the external consistency may include:

[0074] Determine the third wide-lane fixed ambiguity according to the narrow-lane fixed ambiguity;

[0075] Check whether the first difference between the first wide-lane fixed ambiguity and the third wide-lane fixed ambiguity is less than the first preset difference threshold;

[0076] Check whether the first distance between the position determined by the first wide-lane fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than the first preset distance threshold;

[0077] When the first difference is less than the first preset difference threshold and the first distance is less than the first preset distance threshold, confirm that the external consistency is met.

[0078] Specifically, when the external inspection ambiguity data includes the first wide-lane fixed ambiguity of the current epoch, the verification of external compliance consistency can be determined from two aspects: numerical consistency and position consistency. Among them, the numerical value is the comparison between the two wide-lane fixed ambiguity values, which are respectively the wide-lane fixed ambiguity obtained by searching in the current epoch and the wide-lane fixed ambiguity calculated based on the narrow-lane fixed ambiguity; the two positions for determining the distance are respectively the position determined according to the wide-lane fixed ambiguity and the position determined according to the narrow-lane fixed ambiguity.

[0079] In some embodiments, when the external inspection ambiguity data includes the narrow-lane fixed ambiguity of the previous epoch, determining whether the external inspection ambiguity data and the narrow-lane fixed ambiguity meet the external compliance consistency includes:

[0080] Checking whether the second difference between the narrow-lane fixed ambiguity of the previous epoch and the narrow-lane fixed ambiguity of the current epoch is less than the second preset difference threshold;

[0081] Checking whether the second distance between the position determined by the narrow-lane fixed ambiguity of the previous epoch and the position determined by the narrow-lane fixed ambiguity of the current epoch is less than the second preset distance threshold;

[0082] When the second difference is less than the second preset difference threshold and the second distance is less than the second preset distance threshold, it is confirmed that the external compliance consistency is met.

[0083] Specifically, when the external inspection ambiguity data includes the narrow-lane fixed ambiguity of the previous epoch, the verification of external compliance consistency can still be determined from two aspects: numerical consistency and position consistency. Among them, the numerical value is the comparison between the two narrow-lane fixed ambiguity values, which are respectively the narrow-lane fixed ambiguity of the current epoch and the narrow-lane fixed ambiguity of the previous epoch; the two positions for determining the distance are the positions determined according to the above two narrow-lane fixed ambiguities respectively.

[0084] In some embodiments, when the self-inspection ambiguity data includes the second wide-lane fixed ambiguity, determining whether the self-inspection ambiguity data and the narrow-lane fixed ambiguity meet the internal compliance consistency may include:

[0085] Checking whether the third distance between the position determined by the second wide-lane fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than the third preset distance threshold;

[0086] When the third distance is less than the third preset distance threshold, it is confirmed that the internal compliance consistency is met.

[0087] In some embodiments, when the self-check ambiguity data includes the ionosphere-free fixed ambiguity, determining whether there is internal consistency between the self-check ambiguity data and the narrow-lane fixed ambiguity may include:

[0088] Checking whether a fourth distance between the position determined by the ionosphere-free fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than a fourth preset distance threshold;

[0089] When the fourth distance is less than the fourth preset distance threshold, it is confirmed that there is internal consistency.

[0090] It should be noted that the second wide-lane fixed ambiguity, the ionosphere-free fixed ambiguity, and the narrow-lane fixed ambiguity subset included in the self-check ambiguity data are all obtained by transforming the narrow-lane fixed ambiguity.

[0091] In some embodiments, when the self-check ambiguity data includes the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity, determining whether there is internal consistency between the self-check ambiguity data and the narrow-lane fixed ambiguity includes:

[0092] Checking whether the posterior mean square error of unit weight between the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity is less than a preset error threshold;

[0093] Checking whether the distance difference between a sixth distance and a seventh distance is less than a sixth preset distance threshold, where the sixth distance is the distance between the position determined by the second wide-lane fixed ambiguity and the position determined by the narrow-lane fixed ambiguity, and the seventh distance is the distance between the position determined by the ionosphere-free fixed ambiguity and the position determined by the narrow-lane fixed ambiguity;

[0094] When the posterior mean square error of unit weight is less than the preset error threshold and the distance difference between the sixth distance and the seventh distance is less than the sixth preset distance threshold, it is confirmed that there is internal consistency.

[0095] In some embodiments, when the self-check ambiguity data includes a narrow-lane fixed ambiguity subset, determining whether there is internal consistency between the self-check ambiguity data and the narrow-lane fixed ambiguity may include:

[0096] Checking whether a fifth distance between the position determined by the narrow-lane fixed ambiguity subset and the position determined by the narrow-lane fixed ambiguity is less than a fifth preset distance threshold;

[0097] When the fifth distance is less than the fifth preset distance threshold, it is confirmed that there is internal consistency.

[0098] In some embodiments, when there are multiple narrow-lane fixed ambiguity subsets, determining the internal consistency between the self-check ambiguity data and the narrow-lane fixed ambiguity may include:

[0099] Calculating multiple determined positions respectively according to the multiple narrow-lane fixed ambiguity subsets;

[0100] Calculating the reference statistical data between the multiple determined positions, and when the reference statistical data meets the preset threshold, confirming compliance with the internal consistency, where the reference statistical data includes at least one of the maximum value, mean value, and standard deviation.

[0101] It should be noted that the multiple narrow-lane fixed ambiguity subsets and the multiple determined positions are in one-to-one correspondence.

[0102] In some embodiments, the set of narrow-lane fixed ambiguities at the current epoch is composed of the narrow-lane fixed ambiguities corresponding to M satellites. Arbitrarily selecting N satellites from the above M satellites, the narrow-lane fixed ambiguities corresponding to the above N satellites constitute a narrow-lane fixed ambiguity subset, where both M and N are positive integers, and M is greater than N.

[0103] In some embodiments, when there are multiple narrow-lane fixed ambiguity subsets, determining the internal consistency between the self-check ambiguity data and the narrow-lane fixed ambiguity may include:

[0104] Determining multiple position corrections respectively corresponding to the multiple target positions according to the multiple target positions, where the position correction is the distance difference between the target position and the position determined by the narrow-lane fixed ambiguity at the current epoch;

[0105] Calculating the reference statistical data between the multiple position corrections, and when the reference statistical data meets the preset data requirements, the data verification of the internal consistency passes, where the reference statistical data includes at least one of the maximum value, mean value, and standard deviation.

[0106] When the self-check ambiguity data includes the second wide-lane fixed ambiguity, the ionosphere-free fixed ambiguity, and a subset of narrow-lane fixed ambiguities, the internal consistency check can be determined by position consistency, that is, two positions are respectively determined according to the self-check ambiguity data and the narrow-lane fixed ambiguity, and it is judged whether the distance difference between the two positions is less than a preset distance threshold. If so, it is confirmed that the internal consistency is met. When the self-check ambiguity data is multiple subsets of narrow-lane fixed ambiguities, the internal consistency check is still determined by position consistency. At this time, what needs to be judged is the reference statistical data between the multiple positions determined by the multiple subsets of narrow-lane fixed ambiguities. When the above reference statistical data meets the preset threshold, it is confirmed that the internal consistency is met.

[0107] In some embodiments, the method for confirming the narrow-lane fixed ambiguity can also be judged by multiple empirical indicators. Specifically, based on a large amount of sample data, the optimal ambiguity group and the sub-optimal ambiguity group are selected, and multiple empirical indicators of the optimal ambiguity group and the sub-optimal ambiguity group are respectively obtained. Based on the preset empirical threshold, it is judged whether the ambiguity is abnormal through the above empirical indicators.

[0108] It should be noted that the empirical indicators can at least include information such as the Ratio value, the ambiguity dilution of precision, the number of fixed satellites, the number of fixed ambiguities, the a posteriori residual of the fixed ambiguity pseudorange, the a posteriori residual of the filtered solution, and the geometric configuration of the fixed ambiguity.

[0109] The method for confirming the narrow-lane fixed ambiguity provided by the embodiments of the present application determines the data consistency with the narrow-lane fixed ambiguity according to the external check ambiguity data and the self-check ambiguity data, so as to confirm whether the narrow-lane fixed ambiguity is correct. By establishing multiple check strategies based on the external check ambiguity data and the self-check ambiguity data, the correctness of the narrow-lane fixed ambiguity is confirmed from multiple aspects, and the reliability of the narrow-lane fixed ambiguity is improved.

[0110] In GNSS, the narrow-lane fixed ambiguity can be used for precise positioning. The method for positioning in GNSS according to the narrow-lane fixed ambiguity will be described in detail below.

[0111] As Figure 2 shown, the embodiments of the present application provide a positioning method based on the Global Navigation Satellite System (GNSS), and the method includes:

[0112] S201, determine the observation data according to the satellite signals received by the multi-frequency and multi-system Global Navigation Satellite System (GNSS) receiver.

[0113] S202, perform Kalman filtering on the observation data based on the target observation equation to determine the narrow-lane float ambiguity.

[0114] Specifically, Kalman filtering is performed on the observation data based on the target observation equation to determine the single-difference narrow-lane floating-point ambiguity, and the single-difference narrow-lane floating-point ambiguity is transformed into a double-difference narrow-lane floating-point ambiguity;

[0115] Among them, the target observation equation is determined according to the search result of the double-difference wide-lane floating-point ambiguity, and the double-difference wide-lane floating-point ambiguity is obtained by linearly transforming the reference single-difference narrow-lane floating-point ambiguity determined according to the observation data.

[0116] S203. Based on the least squares ambiguity decorrelation LAMBDA algorithm, search for the narrow-lane floating-point ambiguity to determine the narrow-lane fixed ambiguity of the current epoch.

[0117] It should be noted that the narrow-lane floating-point ambiguity searched by applying the LAMBDA algorithm is the double-difference narrow-lane floating-point ambiguity.

[0118] In some embodiments, based on the least squares ambiguity decorrelation LAMBDA algorithm, searching for the narrow-lane floating-point ambiguity includes:

[0119] Based on the least squares ambiguity decorrelation LAMBDA algorithm, sequentially use multiple search rules as the target search rule according to the preset priority, and search for the narrow-lane floating-point ambiguity according to the target search rule until the target narrow-lane floating-point ambiguity whose test parameters meet the preset requirements is found;

[0120] Among them, the multiple search rules include:

[0121] The first search rule, which is to search only for the narrow-lane floating-point ambiguity of the first frequency point;

[0122] The second search rule, which is to sequentially narrow the search range according to a preset ratio based on the elevation angle of the satellite corresponding to the narrow-lane floating-point ambiguity and the carrier-to-noise ratio of the observation data to form multiple ranked ambiguity subsets;

[0123] The third search rule, which is to sequentially eliminate satellites according to the rule of increasing elevation angle of the satellite corresponding to the narrow-lane floating-point ambiguity to form multiple ranked ambiguity subsets;

[0124] Among them, the priority of the first search rule is greater than that of the second search rule, and the priority of the second search rule is greater than that of the third search rule.

[0125] S204. Confirm the narrow-lane fixed ambiguity according to the method for confirming the narrow-lane fixed ambiguity provided in the embodiments of the present application.

[0126] S205. Perform positioning according to the confirmed narrow-lane fixed ambiguity.

[0127] The positioning method based on the Global Navigation Satellite System (GNSS) provided by the embodiments of the present application comprehensively considers information such as satellite elevation angle and carrier-to-noise ratio of observation data, and adopts an adaptive partial ambiguity fixing strategy. The floating-point ambiguity is searched by selecting subsets of ambiguities with different criteria from multiple dimensions, which improves the success rate of floating-point ambiguity search. Further, the narrow-lane floating-point ambiguity obtained by the search is fixed to determine the narrow-lane fixed ambiguity. Based on the confirmation method of the narrow-lane fixed ambiguity provided by the embodiments of the present application, it is confirmed whether the above narrow-lane fixed ambiguity is correct, which improves the reliability of the narrow-lane fixed ambiguity. Finally, positioning is performed according to the confirmed correct narrow-lane fixed ambiguity to improve the positioning accuracy.

[0128] The following specifically describes the search process of the narrow-lane floating-point ambiguity in steps 201 to 203 above with reference to specific embodiments.

[0129] As Figure 3 shown, in S301, according to the signals transmitted by satellites received by a multi-frequency and multi-system GNSS receiver, ephemeris, pseudorange observations, and carrier observations are obtained. At the same time, pseudorange and carrier differential data broadcast by a reference station are received.

[0130] In S302, according to the various data obtained in the above steps, for each frequency point and each system, an inter-satellite - inter-station double-difference observation equation of the reference satellite group is selected and Kalman filtering is performed to obtain the narrow-lane single-difference floating-point ambiguity and its variance-covariance matrix.

[0131] In S303, a linear transformation is performed on the narrow-lane single-difference floating-point ambiguity and its variance-covariance matrix to obtain the wide-lane double-difference floating-point ambiguity and its variance-covariance matrix.

[0132] In some embodiments, after the floating-point solution of the state vector is calculated by Kalman filtering, in order to further improve the positioning accuracy, the ambiguity needs to be fixed. Since the ambiguity parameter in the state vector is the inter-station single-difference ambiguity, which does not have an integer property, it needs to be transformed into a double-difference ambiguity. The transformation strategy is as shown in Formula 1:

[0133]

[0134]

[0135] In Formula 1, D represents the conversion operator for transforming the single-difference ambiguity to the double-difference ambiguity.

[0136] In S304, based on the LAMBDA algorithm, the wide-lane double-difference floating-point ambiguity is searched. If the wide-lane fixed ambiguity is found, S305 is executed; otherwise, the narrow-lane floating-point ambiguity determined in S302 is output to S306.

[0137] In some embodiments, after obtaining the double-difference ambiguity and the variance-covariance matrix, the LAMBDA search algorithm is used to fix the double-difference ambiguity. After the ambiguity to be searched passes the relevant ambiguity confirmation strategy, the ambiguity is considered reliable. At this time, the fixed ambiguity is used as a constraint and brought into the integer least squares to obtain an accurate fixed solution.

[0138] When the Kalman filter calculates the double-difference floating-point ambiguity ▽△D and the variance-covariance matrix Q, the integer least squares problem can be represented by Equation 2:

[0139]

[0140] Equation 2 is a quadratic optimal problem that requires very complex search calculations. The LAMBDA algorithm improves the search efficiency of the cycle ambiguity through ambiguity de-correlation and sequential conditional least squares integer search, and is currently recognized as the most effective ambiguity search algorithm.

[0141] After the ambiguity search, it is also necessary to verify and confirm the searched ambiguity. For the ambiguity verification and confirmation, it is usually judged whether the searched ambiguity is accurate and reliable through the Ratio value. The Ratio value represents the ratio between the sub-optimal ambiguity group and the optimal ambiguity group, and it can be represented by Equation 3:

[0142]

[0143] In Equation 3, represents the optimal ambiguity alternative group, represents the sub-optimal ambiguity alternative group. When the Ratio value is greater than a certain threshold, the optimal ambiguity alternative group is considered to be the correct ambiguity. Generally, the Ratio value is taken as 2.5.

[0144] S305. Input the wide-lane fixed ambiguity as a constraint condition into the filter, and constrain the single-difference narrow-lane floating-point ambiguity determined in S302 to determine some single-difference narrow-lane floating-point ambiguities that meet the preset requirements.

[0145] In some embodiments, due to problems such as computational complexity or environmental occlusion, if all satellites participate in the LAMBDA ambiguity search, it may lead to relatively low search efficiency or the ambiguity cannot be successfully searched. Therefore, a partial ambiguity fixing strategy needs to be adopted. When fixing partial ambiguities, it is necessary to improve D in the above process, and only select some single-difference ambiguities that meet the requirements after filtering and transform them into double-difference ambiguities.

[0146] There are a very large number of multi-frequency and multi-system fixed ambiguities. On the one hand, the LAMBDA ambiguity search efficiency is very low. On the other hand, there may also be a problem of not being able to search for the correct ambiguity. Considering that the wide-lane wavelength is much longer than the original wavelength, the dimension of the ambiguity search after forming the wide-lane is also reduced, and it is easier to be searched by LAMBDA. Therefore, the most common method for multi-frequency is to first fix the wide-lane ambiguity. Therefore, in the embodiment of the present application, the wide-lane ambiguity is first fixed, and the wide-lane ambiguity and its variance-covariance matrix can be directly transformed from the filtered single-difference ambiguity and its variance-covariance matrix through Formula 4:

[0147]

[0148]

[0149] If the wide-lane ambiguity search is successful, the wide-lane ambiguity will be used to constrain the filter, and the subsequent narrow-lane ambiguity search will be performed based on the constrained single-difference narrow-lane ambiguity and its variance-covariance matrix.

[0150] S306, perform a linear transformation on the single-difference narrow-lane floating-point ambiguity directly output in S302, or the partial single-difference narrow-lane floating-point ambiguity that meets the preset requirements output in S305, to determine the double-difference narrow-lane floating-point ambiguity.

[0151] S307, search the double-difference floating-point narrow-lane ambiguity according to the first search rule. If a double-difference narrow-lane fixed ambiguity with a Ratio greater than 2.5 is searched, execute S310; otherwise, execute S308.

[0152] S308, search the double-difference floating-point narrow-lane ambiguity according to the second search rule. If a double-difference narrow-lane fixed ambiguity with a Ratio greater than 2.5 is searched, execute S310; otherwise, execute S309.

[0153] S309, search the double-difference floating-point narrow-lane ambiguity according to the third search rule until a double-difference narrow-lane fixed ambiguity with a Ratio greater than 2.5 is searched, execute S310; otherwise, execute S311.

[0154] It should be noted that the first search rule is to only search for the narrow-lane floating-point ambiguity of the first frequency point;

[0155] The second search rule is to gradually narrow the search range according to a preset ratio based on the elevation angle of the satellite corresponding to the narrow-lane floating-point ambiguity and the carrier-to-noise ratio of the observation data to form multiple ranked ambiguity subsets;

[0156] The third search rule is to gradually eliminate satellites according to the rule of increasing elevation angle of the satellite corresponding to the narrow-lane floating-point ambiguity to form multiple ranked ambiguity subsets.

[0157] In some embodiments, for narrow-lane ambiguity search, first, some relatively optimal double-difference ambiguities are selected and fixed. These single-difference ambiguities are transformed into double-difference ambiguities, and then the LAMBDA ambiguity search is adopted.

[0158] If the Ratio of the ambiguity search is greater than 2.5, it indicates that the ambiguity search is successful; otherwise, it indicates that the ambiguity search fails.

[0159] When the ambiguity search for only fixing the double-difference ambiguity of the first frequency point L1 fails, the ambiguity search will adaptively enter another partial ambiguity fixing mode and select all fixable ambiguities according to a certain ratio. First, the elevation angle and carrier-to-noise ratio thresholds are respectively set for the first 80% of the ambiguities. At the same time, in order to ensure that the number of fixed partial ambiguities reaches 80% of all fixable ambiguities, the elevation angle and carrier-to-noise ratio will be gradually reduced step by step to meet this requirement. Similarly, after constructing the D PAR matrix, the double-difference ambiguities and variance-covariance matrix for partial ambiguity fixing are transformed, and then the LAMBDA ambiguity search is adopted. If the Ratio of the ambiguity search is greater than 2.5, it indicates that the ambiguity search is successful; otherwise, it indicates that the ambiguity search fails.

[0160] If the previous ambiguity search steps still fail, a method of excluding satellites one by one will be adopted at this time. According to the satellite elevation angle from low to high, satellites are excluded one by one in a cyclic search manner until a Ratio greater than 2.5 is searched or all satellites are excluded in the cycle.

[0161] S310. The search is successful, and double-difference narrow-lane fixed ambiguities meeting the requirements are searched.

[0162] S311. The search fails, and double-difference narrow-lane fixed ambiguities meeting the requirements are not searched.

[0163] In the process of receiving observation data in GNSS and finally determining the narrow-lane float ambiguities as described above, the algorithm principle applied is as follows:

[0164] For the pseudorange and carrier original observation equations of a certain frequency point observed by any receiver r, they can be expressed as Equation 5:

[0165]

[0166] Where, represents the pseudorange observation value of receiver r for satellite M j , represents the geometric distance from receiver r to satellite M j , c represents the speed of light, dT r represents the clock error of receiver r, represents satellite Mj clock error represents the ionospheric delay represents the tropospheric delay represents the satellite orbit error represents the hardware delay of the pseudorange of receiver r for the M satellite system represents satellite M j the pseudorange hardware delay at the satellite end represents satellite M j the carrier wavelength of the signal represents receiver r for satellite M j the carrier phase observation value in meters represents receiver r for satellite M j the integer ambiguity represents receiver r for satellite M j the hardware delay of the carrier phase represents the initial phase deviation of receiver r for satellite M at the receiver end j represents satellite M j the carrier phase hardware delay at the satellite end represents satellite M j the initial carrier phase deviation at the satellite end, ε represents the observation noise and other errors

[0167] Select reference satellites within each system respectively, and then form double-difference equations. Taking GPS as an example, assuming that the first satellite of the GPS system is selected as the reference satellite, the double-difference observation equation of a certain frequency point of the GPS system can be expressed as Equation 6:

[0168]

[0169] The observation equations of multi-frequency and multi-system are linearly represented as Equation 7:

[0170] Z = HX + v Equation 7

[0171] In Equation 7, Z represents the observation value, H represents the coefficient matrix of the observation value, v represents the error term, and X represents the state parameters of the Kalman filter. The parameters to be estimated include position, velocity, and the single-difference ambiguity between stations. The parameters to be estimated are estimated by the extended Kalman filter algorithm, and its state equation can be expressed as Equation 8:

[0172] X k = F k|k-1 X k-1 + W k-1 Equation 8

[0173] In Equation 8, X k and X k-1 ​Denote the state vectors of the k-th and (k - 1)-th epochs respectively, F k|k-1 Denote the state transition matrix from (k - 1) to k, W k-1 Denote the process noise. The predicted solution can be obtained from the extended Kalman filter algorithm as Equation 9:

[0174]

[0175] In Equation 9, P k-1|k-1 Denote the variance-covariance matrix of the (k - 1)-th epoch state vector, Q k-1 Denote the variance-covariance matrix of the process noise. The state vector of the k-th epoch solved by the extended Kalman filter algorithm can be represented by Equation 10:

[0176]

[0177] In Equation 10, J k Denote the gain matrix of the Kalman filter, I denote the identity matrix, R k Denote the variance-covariance matrix of the observation value.

[0178] The search method for narrow-lane floating-point ambiguity provided by the embodiments of the present application adopts an adaptive partial ambiguity fixing strategy from easy to difficult, comprehensively considers information such as satellite elevation angle, carrier-to-noise ratio of observation data, cycle slip ratio, carrier tracking time, filtering residual, multipath flag, etc., and selects various ambiguity subsets from multiple dimensions to participate in the search for narrow-lane floating-point ambiguity, improving the search success rate of narrow-lane floating-point ambiguity.

[0179] Based on the same inventive concept, the embodiments of the present application also provide a confirmation device for narrow-lane fixed ambiguity.

[0180] As Figure 4 shown, the embodiments of the present application provide a confirmation device for narrow-lane fixed ambiguity. The device includes:

[0181] An acquisition unit 401, configured to acquire the narrow-lane fixed ambiguity of the current epoch;

[0182] A processing unit 402 is configured to determine whether the externally detected ambiguity data is in external consistency with the narrow-lane fixed ambiguity, and / or determine whether the self-detected ambiguity data is in internal consistency with the narrow-lane fixed ambiguity; wherein, the externally detected ambiguity data includes the first wide-lane fixed ambiguity of the current epoch and / or the narrow-lane fixed ambiguity of the previous epoch, and the self-detected ambiguity data includes the second wide-lane fixed ambiguity, and / or the ionosphere-free fixed ambiguity, and / or a subset of the narrow-lane fixed ambiguities; wherein, both the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity are obtained by transforming the narrow-lane fixed ambiguity, and the subset of the narrow-lane fixed ambiguities is a set of the narrow-lane fixed ambiguities corresponding to target satellites, and the target satellites are some satellites in the set of satellites corresponding to the narrow-lane fixed ambiguity;

[0183] A determination unit 403 is configured to confirm that the narrow-lane fixed ambiguity is correct when the internal consistency and / or the external consistency is met.

[0184] In some embodiments, the processing unit 402 is specifically configured to:

[0185] Determine a third wide-lane fixed ambiguity according to the narrow-lane fixed ambiguity;

[0186] Check whether a first difference between the first wide-lane fixed ambiguity and the third wide-lane fixed ambiguity is less than a first preset difference threshold;

[0187] Check whether a first distance between the position determined by the first wide-lane fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than a first preset distance threshold;

[0188] When the first difference is less than the first preset difference threshold and the first distance is less than the first preset distance threshold, confirm that the external consistency is met.

[0189] In some embodiments, the processing unit 402 is specifically configured to:

[0190] Check whether a second difference between the narrow-lane fixed ambiguity of the previous epoch and the narrow-lane fixed ambiguity of the current epoch is less than a second preset difference threshold;

[0191] Check whether a second distance between the position determined by the narrow-lane fixed ambiguity of the previous epoch and the position determined by the narrow-lane fixed ambiguity of the current epoch is less than a second preset distance threshold;

[0192] When the second difference is less than the second preset difference threshold and the second distance is less than the second preset distance threshold, confirm that the external consistency is met.

[0193] In some embodiments, the processing unit 402 is specifically configured to:

[0194] Determine whether the self-check ambiguity data and the narrow-lane fixed ambiguity meet the internal consistency, including:

[0195] Check whether the third distance between the position determined by the second wide-lane fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than the third preset distance threshold;

[0196] When the third distance is less than the third preset distance threshold, confirm that the internal consistency is met.

[0197] In some embodiments, the processing unit 402 is specifically configured to:

[0198] Check whether the fourth distance between the position determined by the ionosphere-free fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than the fourth preset distance threshold;

[0199] When the fourth distance is less than the fourth preset distance threshold, confirm that the internal consistency is met.

[0200] In some embodiments, the processing unit 402 is specifically configured to:

[0201] Check whether the fifth distance between the position determined by the narrow-lane fixed ambiguity subset and the position determined by the narrow-lane fixed ambiguity is less than the fifth preset distance threshold;

[0202] When the fifth distance is less than the fifth preset distance threshold, confirm that the internal consistency is met.

[0203] In some embodiments, the processing unit 402 is specifically configured to:

[0204] Calculate multiple determined positions respectively according to multiple narrow-lane fixed ambiguity subsets;

[0205] Calculate the reference statistical data between the multiple determined positions. When the reference statistical data meets the preset threshold, confirm that the internal consistency is met, where the reference statistical data includes at least one of the maximum value, the mean value, and the standard deviation.

[0206] As Figure 5 shown, the embodiment of the present application further provides a positioning device based on the Global Navigation Satellite System (GNSS). The device includes:

[0207] A receiving unit 501, configured to determine observation data according to the satellite signals received by a multi-frequency multi-system Global Navigation Satellite System (GNSS) receiver;

[0208] A filtering unit 502, configured to perform Kalman filtering on the observation data based on a target observation equation to determine the narrow-lane floating-point ambiguity;

[0209] A search unit 503, configured to search for the narrow-lane floating-point ambiguity based on the least-squares ambiguity decorrelation LAMBDA algorithm, and determine the narrow-lane fixed ambiguity of the current epoch;

[0210] A determination unit 504, configured to confirm the narrow-lane fixed ambiguity according to the narrow-lane fixed ambiguity confirmation method provided in the embodiments of the present application;

[0211] A positioning unit 505, configured to perform positioning according to the confirmed narrow-lane fixed ambiguity.

[0212] In some embodiments, the search unit 503 is specifically configured to:

[0213] Based on the least-squares ambiguity decorrelation LAMBDA algorithm, sequentially use multiple search rules as target search rules according to a preset priority, and search for the double-difference narrow-lane floating-point ambiguity according to the target search rule until a target double-difference narrow-lane floating-point ambiguity whose test parameters meet the preset requirements is found;

[0214] Among them, the multiple search rules include:

[0215] The first search rule, which is to only search for the narrow-lane floating-point ambiguity of the first frequency point;

[0216] The second search rule, which is to sequentially narrow the search range according to a preset ratio based on the elevation angle of the satellite corresponding to the narrow-lane floating-point ambiguity and the carrier-to-noise ratio of the observation data, and form multiple ranked ambiguity subsets;

[0217] The third search rule, which is to sequentially exclude satellites according to the rule of increasing elevation angle of the satellite corresponding to the narrow-lane floating-point ambiguity from low to high, and form multiple ranked ambiguity subsets;

[0218] Among them, the priority of the first search rule is greater than that of the second search rule, and the priority of the second search rule is greater than that of the third search rule.

[0219] For other details of the narrow-lane fixed ambiguity confirmation device provided in the embodiments of the present application and the positioning device based on the global navigation satellite system GNSS, they are similar to the narrow-lane fixed ambiguity confirmation method provided in the embodiments of the present application and the positioning method based on the global navigation satellite system GNSS described above, and will not be elaborated here. Figures 1 - 3

[0220] Figure 6 Fig. shows a schematic hardware structure diagram of positioning based on the global navigation satellite system GNSS provided in the embodiments of the present application.

[0221] Figures 1 - 5 Combined with Figures 1 - 5The method and apparatus for confirming narrow-lane fixed ambiguity, and the positioning method and apparatus based on the Global Navigation Satellite System (GNSS) provided according to the embodiments of the present application can be implemented by a positioning device based on the Global Navigation Satellite System (GNSS). Figure 6 FIG. 600 is a schematic diagram of the hardware structure of a positioning device based on the Global Navigation Satellite System (GNSS) according to an embodiment of the invention.

[0222] In a positioning device based on the Global Navigation Satellite System (GNSS), a processor 601 and a memory 602 storing computer program instructions may be included.

[0223] Specifically, the above-mentioned processor 601 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured as one or more integrated circuits for implementing the embodiments of the present application.

[0224] The memory 602 may include a mass storage for data or instructions. By way of example and not limitation, the memory 602 may include a Hard Disk Drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. In one example, the memory 602 may include removable or non-removable (or fixed) media, or the memory 602 is a non-volatile solid-state memory. The memory 602 may be inside or outside the integrated gateway disaster recovery device.

[0225] In one example, the memory 602 may be a Read Only Memory (ROM). In one example, the ROM may be a mask-programmed ROM, a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), an Electrically Alterable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0226] The processor 601 reads and executes the computer program instructions stored in the memory 602 to implement Figure 1 the methods / steps S101 to S103 in the illustrated embodiment, and achieves Figure 1 the corresponding technical effects achieved by the method / step execution in the illustrated example. For the sake of brevity, it will not be described in detail here.

[0227] In one example, the positioning device based on the Global Navigation Satellite System (GNSS) may further include a communication interface 603 and a bus 610. Among them, as Figure 6 shown, the processor 601, the memory 602, and the communication interface 603 are connected through the bus 610 to complete communication with each other.

[0228] The communication interface 603 is mainly used to implement communication between various modules, devices, units, and / or devices in the embodiments of the present application.

[0229] The bus 610 includes hardware, software, or both, and couples the components of the online data flow meter charging device together. By way of example and not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses or a combination of two or more of these. In a suitable case, the bus 610 may include one or more buses. Although the embodiments of the present application describe and illustrate specific buses, the present application contemplates any suitable bus or interconnect.

[0230] The positioning device based on the Global Navigation Satellite System (GNSS) provided by the embodiments of the present application comprehensively considers information such as the satellite elevation angle and the carrier-to-noise ratio of the observation data, and adopts an adaptive partial ambiguity fixing strategy. Different standard ambiguity subsets are selected from multiple dimensions for the search of floating-point ambiguities, which improves the search success rate of floating-point ambiguities. Further, the narrow-lane floating-point ambiguities found are fixed to determine the narrow-lane fixed ambiguities. Based on the confirmation method of the narrow-lane fixed ambiguities provided by the embodiments of the present application, it is confirmed whether the above narrow-lane fixed ambiguities are correct, which improves the reliability of the narrow-lane fixed ambiguities. Finally, positioning is performed according to the confirmed correct narrow-lane fixed ambiguities to improve the positioning accuracy.

[0231] In addition, in combination with the positioning method based on the Global Navigation Satellite System (GNSS) and the positioning method based on the Global Navigation Satellite System (GNSS) in the above embodiments, an embodiment of the present application can provide a computer storage medium to implement. Computer program instructions are stored on the computer storage medium; when the computer program instructions are executed by a processor, any one of the methods for confirming narrow-lane fixed ambiguity and the positioning method based on the Global Navigation Satellite System (GNSS) in the above embodiments is implemented.

[0232] It should be clear that the present application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present application.

[0233] The functional blocks shown in the above structural block diagrams can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), appropriate firmware, a plug-in, a function card, and so on. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted via a data signal carried in a carrier wave on a transmission medium or a communication link. A "machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical discs, hard disks, fiber optic media, Radio Frequency (RF) links, and so on. The code segment can be downloaded via a computer network such as the Internet or an intranet.

[0234] It should also be noted that the exemplary embodiments mentioned in the present application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above steps. That is, the steps can be executed in the order mentioned in the embodiments, or different from the order in the embodiments, or several steps can be executed simultaneously.

[0235] Aspects of the present disclosure have been described above with reference to the flowchart and / or block diagram of a method, apparatus (system), and computer program product according to an embodiment of the present disclosure. It should be understood that each block in the flowchart and / or block diagram, and the combination of blocks 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, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more blocks of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It is also understood that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can also be implemented by dedicated hardware that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0236] The above is only a specific implementation manner of the present application. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, modules, and units can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again. It should be understood that the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and these modifications or substitutions should all be covered by the protection scope of the present application.

Claims

1. A method for confirming the ambiguity of a narrow lane, characterized in that The method includes: Obtaining the narrow-lane fixed ambiguity of the current epoch; Determining whether the external inspection ambiguity data conforms to the external consistency with the narrow-lane fixed ambiguity, and / or determining whether the self-inspection ambiguity data conforms to the internal consistency with the narrow-lane fixed ambiguity; wherein, the external inspection ambiguity data includes the first wide-lane fixed ambiguity of the current epoch and / or the narrow-lane fixed ambiguity of the previous epoch, and the self-inspection ambiguity data includes the second wide-lane fixed ambiguity, and / or the ionosphere-free fixed ambiguity, and / or a subset of the narrow-lane fixed ambiguities; wherein, both the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity are obtained by transforming the narrow-lane fixed ambiguity, and the subset of the narrow-lane fixed ambiguities is a set of narrow-lane fixed ambiguities corresponding to target satellites, and the target satellites are some of the satellites in the satellite set corresponding to the narrow-lane fixed ambiguity; When the internal consistency and / or the external consistency is met, confirming that the narrow-lane fixed ambiguity is correct.

2. The method according to claim 1, wherein When the external inspection ambiguity data includes the first wide-lane fixed ambiguity of the current epoch, Determining whether the external inspection ambiguity data conforms to the external consistency with the narrow-lane fixed ambiguity includes: Determining a third wide-lane fixed ambiguity according to the narrow-lane fixed ambiguity; Checking whether a first difference between the first wide-lane fixed ambiguity and the third wide-lane fixed ambiguity is less than a first preset difference threshold; Checking whether a first distance between the position determined by the first wide-lane fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than a first preset distance threshold; When the first difference is less than the first preset difference threshold and the first distance is less than the first preset distance threshold, confirming that the external consistency is met.

3. The method according to claim 1, characterized in that When the external inspection ambiguity data includes the narrow-lane fixed ambiguity of the previous epoch, Determining whether the external inspection ambiguity data conforms to the external consistency with the narrow-lane fixed ambiguity includes: Checking whether a second difference between the narrow-lane fixed ambiguity of the previous epoch and the narrow-lane fixed ambiguity of the current epoch is less than a second preset difference threshold; Checking whether a second distance between the position determined by the narrow-lane fixed ambiguity of the previous epoch and the position determined by the narrow-lane fixed ambiguity of the current epoch is less than a second preset distance threshold; When the second difference is less than the second preset difference threshold and the second distance is less than the second preset distance threshold, confirming that the external consistency is met.

4. The method according to claim 1, characterized in that, When the self-inspection ambiguity data includes the second wide-lane fixed ambiguity, Determining whether the self-inspection ambiguity data conforms to the internal consistency with the narrow-lane fixed ambiguity includes: Checking whether a third distance between the position determined by the second wide-lane fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than a third preset distance threshold; When the third distance is less than the third preset distance threshold, confirming that the internal consistency is met.

5. The method according to claim 1, wherein When the self-inspection ambiguity data includes the ionosphere-free fixed ambiguity, Determine whether the self-check ambiguity data and the narrow-lane fixed ambiguity meet the internal consistency, including: Check whether the fourth distance between the position determined by the ionosphere-free fixed ambiguity and the position determined by the narrow-lane fixed ambiguity is less than the fourth preset distance threshold; When the fourth distance is less than the fourth preset distance threshold, confirm that the internal consistency is met.

6. The method according to claim 1, wherein When the self-check ambiguity data includes the narrow-lane fixed ambiguity subset, Determine whether the self-check ambiguity data and the narrow-lane fixed ambiguity meet the internal consistency, including: Check whether the fifth distance between the position determined by the narrow-lane fixed ambiguity subset and the position determined by the narrow-lane fixed ambiguity is less than the fifth preset distance threshold; When the fifth distance is less than the fifth preset distance threshold, confirm that the internal consistency is met.

7. The method according to claim 6, wherein When there are multiple narrow-lane fixed ambiguity subsets, determine the internal consistency between the self-check ambiguity data and the narrow-lane fixed ambiguity, including: Calculate multiple determined positions respectively according to the multiple narrow-lane fixed ambiguity subsets; Calculate the reference statistical data between the multiple determined positions. When the reference statistical data meets the preset threshold, confirm that the internal consistency is met, where the reference statistical data includes at least one of the maximum value, mean value, and standard deviation.

8. A positioning method based on the Global Navigation Satellite System (GNSS), characterized in that, The method includes: Determine the observation data according to the satellite signals received by the multi-frequency multi-system global navigation satellite system (GNSS) receiver; Perform Kalman filtering on the observation data based on the target observation equation to determine the narrow-lane floating-point ambiguity; Search for the narrow-lane floating-point ambiguity based on the least squares ambiguity decorrelation (LAMBDA) algorithm to determine the narrow-lane fixed ambiguity of the current epoch; Confirm the narrow-lane fixed ambiguity according to the method according to any one of claims 1-7; Perform positioning according to the confirmed narrow-lane fixed ambiguity.

9. The method according to claim 8, wherein Search for the narrow-lane floating-point ambiguity based on the least squares ambiguity decorrelation (LAMBDA) algorithm, including: Based on the least squares ambiguity decorrelation (LAMBDA) algorithm, sequentially use multiple search rules as the target search rules according to the preset priority, and search for the narrow-lane floating-point ambiguity according to the target search rules until the target narrow-lane floating-point ambiguity with the test parameters meeting the preset requirements is found; Among them, the multiple search rules include: The first search rule, which is to only search for the narrow-lane floating-point ambiguity of the first frequency point; The second search rule, which is to sequentially narrow the search range according to a preset ratio based on the elevation angle of the satellite corresponding to the narrow-lane floating-point ambiguity and the carrier-to-noise ratio of the observation data to form multiple ranked ambiguity subsets; The third search rule, which is to sequentially exclude the satellites according to the rule of increasing elevation angle of the satellites corresponding to the narrow-lane floating-point ambiguity to form multiple ranked ambiguity subsets; Among them, the priority of the first search rule is greater than that of the second search rule, and the priority of the second search rule is greater than that of the third search rule.

10. A confirmation device for narrow-lane fixed ambiguity, characterized in that The device includes: an acquisition unit, configured to acquire the narrow-lane fixed ambiguity of the current epoch; a processing unit, configured to determine whether the external inspection ambiguity data is in line with the external consistency with the narrow-lane fixed ambiguity, and / or determine whether the self-inspection ambiguity data is in line with the internal consistency with the narrow-lane fixed ambiguity; wherein, the external inspection ambiguity data includes the first wide-lane fixed ambiguity of the current epoch and / or the narrow-lane fixed ambiguity of the previous epoch, and the self-inspection ambiguity data includes the second wide-lane fixed ambiguity, and / or the ionosphere-free fixed ambiguity, and / or a subset of the narrow-lane fixed ambiguities; wherein, the second wide-lane fixed ambiguity and the ionosphere-free fixed ambiguity are both transformed from the narrow-lane fixed ambiguity, and the subset of the narrow-lane fixed ambiguities is a set of the narrow-lane fixed ambiguities corresponding to target satellites, and the target satellites are some satellites in the set of satellites corresponding to the narrow-lane fixed ambiguity; a determination unit, configured to confirm that the narrow-lane fixed ambiguity is correct when the internal consistency and / or the external consistency is met.

11. A positioning device based on the Global Navigation Satellite System (GNSS), characterized in that, The device includes: a receiving unit, configured to determine observation data according to satellite signals received by a multi-frequency multi-system global navigation satellite system (GNSS) receiver; a filtering unit, configured to perform Kalman filtering on the observation data based on a target observation equation to determine the narrow-lane floating-point ambiguity; a searching unit, configured to search for the narrow-lane floating-point ambiguity based on the least-squares ambiguity decorrelation adjustment (LAMBDA) algorithm to determine the narrow-lane fixed ambiguity of the current epoch; a determination unit, configured to confirm the narrow-lane fixed ambiguity according to the method according to any one of claims 1-7; a positioning unit, configured to perform positioning according to the confirmed narrow-lane fixed ambiguity.

12. A positioning device based on the Global Navigation Satellite System (GNSS), characterized in that, The device includes: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the GNSS-based positioning method according to any one of claims 8-9.

13. A computer storage medium, characterized in that, Computer program instructions are stored on the computer storage medium, and when the computer program instructions are executed by a processor, the GNSS-based positioning method according to any one of claims 8-9 is implemented.

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