Method and device for fixing non-difference ambiguity and electronic equipment

Abstract

The application discloses a non-difference ambiguity fixing method, device and electronic equipment. The non-difference ambiguity fixing method comprises the following steps: obtaining original observation data; establishing an observation equation according to the original observation data, performing floating point calculation, and obtaining a floating point solution, wherein the floating point solution comprises floating point ambiguity; based on the original observation data and the floating point ambiguity, UPD is calculated to obtain fixed non-difference ambiguity; based on the original observation data and the floating point ambiguity, double-difference observation values are formed to obtain fixed double-difference ambiguity; each fixed double-difference ambiguity is used to check the corresponding fixed non-difference ambiguity; and the floating point solution is constrained according to the fixed non-difference ambiguity that passes the check, so that a non-difference fixed solution is obtained. According to the embodiment of the application, the problem that the accuracy of the fixing method directly using non-difference ambiguity or double-difference ambiguity is low in the related art is solved.

Description

Technical Field

[0001] This application belongs to the field of satellite observation data processing technology, and in particular relates to a method, device and electronic equipment for fixing non-differential ambiguity. Background Technology

[0002] Currently, in related technologies, after obtaining a floating-point solution through floating-point arithmetic, a fixed unequal ambiguity can be obtained through UPD arithmetic. This fixed unequal ambiguity is typically used directly to fix the observation equation. Alternatively, a fixed double-difference ambiguity is obtained based on the original observation data and the floating-point ambiguity, and this fixed double-difference ambiguity is then used directly to fix the observation equation. However, fixed unequal ambiguities may contain some erroneous ambiguities, while fixed double-difference ambiguities may suffer some precision loss. Therefore, methods that directly use unequal or double-difference ambiguities for fixation have relatively low accuracy. Summary of the Invention

[0003] This application provides a method, apparatus, and electronic device for fixing unequal ambiguities, which can solve the problem of low accuracy in related technologies that directly use unequal or double-difference ambiguities for fixing.

[0004] In a first aspect, embodiments of this application provide a method for fixing non-differential ambiguities, the method comprising:

[0005] Obtain raw observation data;

[0006] An observation equation is established based on the original observation data, and a floating-point solution is obtained by performing floating-point calculations. The floating-point solution includes floating-point ambiguity.

[0007] Based on the original observation data and floating-point ambiguity, the UPD is solved to obtain a fixed non-difference ambiguity;

[0008] Based on the original observation data and floating-point ambiguity, double-difference observations are formed, and fixed double-difference ambiguity is obtained;

[0009] The corresponding fixed non-difference ambiguity is verified based on each fixed double-difference ambiguity.

[0010] Based on the verified fixed non-difference fuzzy constraint floating-point solution, the non-difference fixed solution is obtained.

[0011] Optionally, a fixed non-difference ambiguity is verified based on each fixed double-difference ambiguity, including:

[0012] For a fixed first double-difference ambiguity, determine the four fixed non-difference ambiguities corresponding to the first double-difference ambiguity;

[0013] The second double-difference ambiguity corresponding to the first double-difference ambiguity is obtained by linearly combining four fixed non-difference ambiguities.

[0014] Determine whether the first double-difference ambiguity and the second double-difference ambiguity are consistent; if they are consistent, determine that the four fixed non-difference ambiguities have passed the verification; otherwise, if they are inconsistent, determine that the four fixed non-difference ambiguities have failed the verification.

[0015] Optionally, four fixed non-differenced ambiguities corresponding to the first double-difference ambiguity are determined, including:

[0016] Based on the satellite and station corresponding to the first double-difference ambiguity, four fixed non-difference ambiguities corresponding to the first double-difference ambiguity are determined;

[0017] The satellites and stations corresponding to the first double-difference ambiguity include the first satellite, the second satellite, the first station, and the second station. The four fixed non-difference ambiguities include: the non-difference ambiguities observed by the first station for the first satellite and the second satellite respectively, and the non-difference ambiguities observed by the second station for the first satellite and the second satellite respectively.

[0018] Optionally, a second double-difference ambiguity corresponding to the first double-difference ambiguity is obtained by linearly combining four fixed non-difference ambiguities, including:

[0019] The difference between the non-differential ambiguities observed by the first station for the first satellite and the second satellite is calculated to obtain the first difference value;

[0020] The difference between the non-difference ambiguities observed by the second station from the first and second satellites is calculated to obtain the second difference value;

[0021] The difference between the first difference and the second difference is calculated to obtain the second double-difference ambiguity.

[0022] Secondly, embodiments of this application provide a device for fixing non-differential ambiguities, the device comprising:

[0023] The acquisition unit is used to acquire raw observation data;

[0024] The execution unit is used to establish observation equations based on the original observation data, perform floating-point calculations, and obtain floating-point solutions, which include floating-point ambiguities.

[0025] The solution unit is used to solve the UPD to obtain a fixed non-difference ambiguity based on the original observation data and floating-point ambiguity.

[0026] The calculation unit is used to compose double-difference observations based on the original observation data and floating-point ambiguity, and obtain fixed double-difference ambiguity.

[0027] The verification unit is used to verify the corresponding fixed non-difference ambiguity based on each fixed double-difference ambiguity;

[0028] The constraint unit is used to obtain the non-differential fixed solution based on the verified fixed non-differential fuzzy constraint floating-point solution.

[0029] Optionally, the verification unit includes:

[0030] The first determining subunit is used to determine four fixed non-difference ambiguities corresponding to the fixed first double-difference ambiguity.

[0031] The first calculation subunit is used to obtain the second double-difference ambiguity corresponding to the first double-difference ambiguity based on a linear combination of four fixed non-difference ambiguities;

[0032] The judgment subunit is used to determine whether the first double-difference ambiguity and the second double-difference ambiguity are consistent; if they are consistent, the four fixed non-difference ambiguities are determined to pass the verification; otherwise, if they are inconsistent, the four fixed non-difference ambiguities are determined to fail the verification.

[0033] Optionally, the first determined subunit includes:

[0034] The second determining subunit is used to determine four fixed non-difference ambiguities corresponding to the first double-difference ambiguity based on the satellite and station corresponding to the first double-difference ambiguity;

[0035] The satellites and stations corresponding to the first double-difference ambiguity include the first satellite, the second satellite, the first station, and the second station. The four fixed non-difference ambiguities include: the non-difference ambiguities observed by the first station for the first satellite and the second satellite respectively, and the non-difference ambiguities observed by the second station for the first satellite and the second satellite respectively.

[0036] Optionally, the first computational subunit includes:

[0037] The second calculation subunit is used to calculate the difference in non-differential ambiguity between the observations of the first satellite and the second satellite by the first station, and to obtain the first difference value;

[0038] The third calculation subunit is used to calculate the difference in non-difference ambiguity between the observations of the first satellite and the second satellite by the second station, and to obtain the second difference value;

[0039] The fourth calculation subunit is used to calculate the difference between the first difference and the second difference to obtain the second double-difference ambiguity.

[0040] Thirdly, embodiments of this application provide an electronic device, which includes: a processor and a memory storing program instructions; when the processor executes the program instructions, it implements the non-difference ambiguity fixing method as described in the first aspect.

[0041] Fourthly, embodiments of this application provide a readable storage medium storing program instructions that, when executed by a processor, implement the method for fixing non-difference ambiguity as described in the first aspect.

[0042] Fifthly, embodiments of this application provide a program product in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the non-difference ambiguity fixing method as described in the first aspect.

[0043] The method, apparatus, electronic device, readable storage medium, and program product for fixing unequal ambiguities according to embodiments of this application acquire raw observation data, establish observation equations based on the raw observation data, perform floating-point calculations to obtain floating-point solutions, wherein the floating-point solutions include floating-point ambiguities. Then, based on the raw observation data and the floating-point ambiguities, the UPD is calculated to obtain fixed unequal ambiguities, and double-difference observations are formed based on the raw observation data and the floating-point ambiguities to obtain fixed double-difference ambiguities. Furthermore, the corresponding fixed unequal ambiguities are verified based on each fixed double-difference ambiguity, thereby constraining the floating-point solutions with the verified fixed unequal ambiguities to obtain an unequal fixed solution. According to embodiments of this application, the problem of low accuracy in related technologies where methods directly using unequal ambiguities or double-difference ambiguities for fixing ambiguities are employed is solved. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a flowchart illustrating a method for fixing non-differential ambiguity provided in one embodiment of this application;

[0046] Figure 2 This is a flowchart illustrating a method for fixing non-differential ambiguity provided in another embodiment of this application;

[0047] Figure 3 This is a schematic diagram of the structure of a non-differential ambiguity fixing device provided in another embodiment of this application;

[0048] Figure 4 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application. Detailed Implementation

[0049] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0050] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0051] To address the problems of the prior art, embodiments of this application provide a method, apparatus, device, and readable storage medium for fixing unequal ambiguities. The method for fixing unequal ambiguities provided in this application will be described first below.

[0052] The terminology appearing in the embodiments of this application is explained below:

[0053] Ambiguity: The integer portion of the phase in a phase observation.

[0054] Floating-point ambiguity: The ambiguity obtained by floating-point calculation, which includes both integer and fractional parts.

[0055] Undifferentiated ambiguity: The ambiguity contained in undifferentiated observations.

[0056] Double-difference ambiguity: The ambiguity contained in double-difference observations.

[0057] Independent baselines: In a set of baselines, the baselines are independent of each other, that is, one baseline cannot be represented by other baselines.

[0058] Fixed ambiguity: Fix the ambiguity to an integer.

[0059] Uncalibrated Phase Delays (UPD) solution: This solution calculates the deviation of the fractional part of the phase in the phase observations.

[0060] Figure 1 A flowchart illustrating a method for fixing non-differential ambiguities according to an embodiment of this application is shown. Figure 1 As shown, the method may include the following steps:

[0061] Step 101: Obtain the raw observation data.

[0062] Raw observation data can be provided by satellite navigation systems, such as GNSS (Global Navigation Satellite System). GNSS uses observations such as pseudorange, ephemeris, and satellite launch time from a set of satellites as raw observation data, providing users with all-weather 3D coordinates, velocity, and time information from any location on the Earth's surface or in near-Earth space. Examples include the US GPS, Russia's GLONASS, Europe's Galileo, China's BeiDou Navigation Satellite System, and related augmentation systems. GNSS raw observation data can include raw code pseudorange observations R and raw carrier phase observations L.

[0063] Step 102: Establish observation equations based on the original observation data, perform floating-point calculations, and obtain floating-point solutions.

[0064] The observation equation describes the relationship between observed values ​​and actual distances (navigation satellites and receivers). Floating-point solutions to the observation equation can be performed using calculation methods found in related technologies, which will not be elaborated upon here. After floating-point solution processing, a floating-point solution is obtained. The floating-point solution includes floating-point ambiguity.

[0065] Step 103: Based on the original observation data and floating-point ambiguity, calculate UPD to obtain fixed non-difference ambiguity.

[0066] After obtaining the floating-point ambiguity in the floating-point solution, a fixed non-difference ambiguity can be obtained by solving the UPD based on the original observation data and the floating-point ambiguity. Specifically, processing methods from related technologies can be used.

[0067] In one example, a GNSS receiver can simultaneously receive navigation satellite signals at two carrier frequencies, L1 and L2. The combined observation with a longer wavelength obtained from L1+L2 is the wide-lane observation, and the combined observation with less observation noise than both L1 and L2 obtained from L1+L2 is the narrow-lane observation. Based on the wide-lane observation and the narrow-lane observation, respectively, the non-differential wide-lane ambiguity stubbornness and the non-differential narrow-lane ambiguity estimate can be obtained.

[0068] Then, during the UPD estimation process, iterative least squares can be used to uniformly process the input ambiguity parameters of all stations. For any continuous observation arc segment, the floating-point ambiguities of the wide lane and narrow lane can be expressed in the following form:

[0069]

[0070] in, This represents the fractional part of the floating-point ambiguity of the s-th satellite observed from the r-th observation station. This represents the non-differential floating-point ambiguity of the s-th satellite observed by the r-th observation station. express The integer part, d r Let d be the receiver terminal UPD of the r-th observation station. s Let UPD be the satellite-side UPD of the s-th satellite.

[0071] Assuming that the observation network formed by n stations observes a total of m satellites, the floating-point ambiguities of the continuous arc segments between each station and the satellite can be combined into the following system of equations:

[0072]

[0073] In the above equations, the receiver-side UPD and the satellite-side UPD are linearly correlated one-to-one, and the rank deficiency of the equation system is 1. Therefore, we can select the UPD of the satellite with the most observations (let's assume it is the satellite) as the benchmark and fix it at 0. That is, we can add an additional constraint to the equation system: 0 = d s W makes the parameters to be estimated solvable.

[0074] The observation equations are weighted based on the variance of the floating-point ambiguity. The variance of the wide-lane ambiguity is the variance of the observation sequence of the continuous arc segment MW combination (Melbourne-Wubeena combination), while the variance of the narrow-lane ambiguity can be calculated from the variance, variance, covariance, and propagation rate of the ionosphere-free combination ambiguity.

[0075] The least squares method is used to estimate the inter-satellite single difference (UPD) of all other satellites relative to the reference satellite. To improve the robustness of the adjustment solution, observations with an absolute residual value greater than 0.4 weeks or more than 4 times the RMS of the residuals after the previous adjustment can be weighted and iterated again until no observations need to be weighted.

[0076] The above is an example of a process for solving UPD to obtain a fixed non-difference ambiguity. Of course, other methods can be used to improve or optimize the above process to perform UPD solving, and this application embodiment does not limit this.

[0077] Step 104: Based on the original observation data and floating-point ambiguity, double-difference observations are formed to obtain fixed double-difference ambiguity.

[0078] After obtaining the floating-point ambiguity in the floating-point solution, double-difference observations can be constructed based on the original observation data and the floating-point ambiguity. Double-difference observations are a linear combination of the observations, representing the difference between the single-difference phase observations made by two observation stations for two satellites. Specifically, by calculating the difference between the two observation stations and between the two satellites, errors between observation stations can be eliminated, and ionospheric and tropospheric errors can be reduced. A fixed double-difference ambiguity can be calculated based on the double-difference observations. Algorithms from relevant technologies can be used in this process.

[0079] A double-difference observation consists of the difference between four non-difference observations from two stations and two satellites that observe simultaneously. The corresponding double-difference ambiguity is a linear combination of these four non-difference ambiguities.

[0080] One double-difference ambiguity corresponds to one baseline, and one baseline includes multiple double-difference ambiguities.

[0081] With double difference ambiguity The corresponding stations are a and b, and the satellites are i and j, which can be represented by 4 non-difference ambiguities. Linear composition, expressed as the following formula:

[0082]

[0083] Assuming a baseline has n unequal ambiguities, all unequal ambiguities are numbered from 1 to n. A double-difference ambiguity corresponds to a vector with n dimensions. For example, a double-difference ambiguity... The resulting vector design is as follows: Non-difference ambiguity The vector element corresponding to the sequence number is set to 1, and the non-difference ambiguity is... The vector element corresponding to the index is set to -1, and the rest are 0. All double-difference ambiguity vectors are constructed in this way, and the vector dot product is 4.

[0084] The baseline's double-difference ambiguities are sorted by weight based on the probability of effective synchronous observation time or the probability that the double-difference ambiguity can be fixed as an integer. The vector corresponding to the first double-difference ambiguity is directly selected into the independent double-difference ambiguity set and normalized. Then, each double-difference ambiguity is judged according to the orthogonalization algorithm to obtain the optimal independent double-difference ambiguity of the baseline.

[0085] The selection of independent double-difference ambiguities for the entire GNSS network can be achieved by first selecting independent double-difference ambiguities for each baseline, and then judging the independence of these selected double-difference ambiguities to obtain the independent double-difference ambiguities for the entire network.

[0086] Alternatively, you can first select independent baselines, and then select independent double-difference ambiguities for each independent baseline in the non-difference ambiguity method. All the selected double-difference ambiguities constitute the independent double-difference ambiguities of the entire network.

[0087] In selecting independent baselines, the construction method of the baseline vector can draw on the design of the correlation matrix. Assuming there are n stations, all stations are ordered from 1 to n, one baseline corresponds to one vector, and the baseline vector has n dimensions. If the starting point is the i-th station and the ending point is the j-th station, then the i-th element of the corresponding baseline vector is 1, the j-th element is -1, and the remaining elements are 0. This process is repeated to construct all baseline vectors. By the definition of a baseline vector, the dot product of the vectors is 2.

[0088] The baselines are sorted according to their side lengths. The first baseline vector is directly selected into the independent baseline set and normalized. Then, each baseline vector is determined by the Gram-Schmidt orthogonalization algorithm to obtain the shortest (longest) independent baseline set.

[0089] The above is an example of a fixed method for resolving double-difference ambiguity. Of course, other methods that improve or optimize the above process can also be used for the calculation, and this application does not limit this.

[0090] It should be noted that steps 103 and 104 are executed independently of each other, and can be executed after step 102. This application embodiment does not limit the order of steps 103 and 104.

[0091] Step 105: Verify the corresponding fixed non-difference ambiguity based on each fixed double-difference ambiguity.

[0092] When verifying the corresponding fixed non-difference ambiguity through a fixed double-difference ambiguity, it is necessary to traverse all fixed double-difference ambiguities.

[0093] Taking a fixed first double-difference ambiguity as an example, the fixed first double-difference ambiguity involves four fixed non-difference ambiguities. These four fixed non-difference ambiguities are linearly combined to obtain a calculated double-difference ambiguity (i.e., the second double-difference ambiguity). The second double-difference ambiguity is compared with the fixed first double-difference ambiguity. If the comparison results are consistent, the four fixed non-difference ambiguities are considered to have passed the verification. Otherwise, if the comparison results are inconsistent, the four fixed non-difference ambiguities are considered to have failed the verification and can be marked as failing the verification.

[0094] Optionally, when determining the four fixed non-differential ambiguities corresponding to the first double-difference ambiguity, the four fixed non-differential ambiguities can be determined based on the satellite and station corresponding to the first double-difference ambiguity. Assuming that the satellite and station corresponding to the first double-difference ambiguity include the first satellite, the second satellite, the first station, and the second station, then the four fixed non-differential ambiguities include: the non-differential ambiguities observed by the first station for both the first and second satellites, and the non-differential ambiguities observed by the second station for both the first and second satellites.

[0095] When obtaining the second double-difference ambiguity corresponding to the first double-difference ambiguity based on a linear combination of four fixed non-difference ambiguities, the specific steps may include:

[0096] The difference between the non-differential ambiguities observed by the first station for the first satellite and the second satellite is calculated to obtain the first difference value;

[0097] The difference between the non-difference ambiguities observed by the second station from the first and second satellites is calculated to obtain the second difference value;

[0098] The difference between the first difference and the second difference is calculated to obtain the second double-difference ambiguity.

[0099] Step 106: Obtain the non-differential fixed solution based on the verified fixed non-differential fuzzy constraint floating-point solution.

[0100] After traversing all fixed double-difference ambiguities, the four fixed unequal ambiguities corresponding to each fixed double-difference ambiguity can be verified. In this embodiment, only the fixed unequal ambiguities that have passed the verification are used to constrain the floating-point solutions to obtain the unequal fixed solutions, which can improve the accuracy of the unequal fixed solutions. At this time, since the unequal ambiguities have higher accuracy but lower stability, verifying the unequal ambiguities using double-difference ambiguities, which have higher stability but relatively lower accuracy, can remove erroneous fixed unequal ambiguities and improve the stability of the fixed unequal ambiguities.

[0101] The method for fixing unequal ambiguities in this application involves acquiring original observation data, establishing observation equations based on the original observation data, performing floating-point calculations to obtain floating-point solutions, where the floating-point solutions include floating-point ambiguities. Then, based on the original observation data and the floating-point ambiguities, a fixed unequal ambiguity is obtained by solving for the UPD (Undifferenced Persistent Value). Furthermore, double-difference observations are formed based on the original observation data and the floating-point ambiguities to obtain fixed double-difference ambiguities. Finally, the corresponding fixed unequal ambiguities are verified based on each fixed double-difference ambiguity. Thus, the unequal fixed solution is obtained by constraining the floating-point solutions with the verified fixed unequal ambiguities. According to this application, the method solves the problem of low accuracy in related technologies that directly use unequal ambiguities or double-difference ambiguities for fixing.

[0102] refer to Figure 2An optional implementation of the non-differential ambiguity fixing method provided in the embodiments of this application is as follows: Figure 2 As shown, the method may include the following steps:

[0103] Step 1: Obtain global GNSS observation data.

[0104] Step 2: Perform floating-point calculations using global GNSS observation data to obtain floating-point ambiguity.

[0105] Step 3: After performing Step 2, use global GNSS observation data and floating-point ambiguity to perform UPD and differential ambiguity resolution to obtain a fixed set of differential ambiguities.

[0106] Step 4: After performing Step 2, a fixed double-difference ambiguity is obtained through double-difference ambiguity resolution.

[0107] Steps three and four are executed independently, and there is no restriction on the order in which they are performed.

[0108] Step 5: After performing steps 3 and 4, the fixed non-difference ambiguity can be checked by using the fixed double-difference ambiguity.

[0109] Step 6: Retain the fixed set of non-differential fuzzynesses that passed the test in Step 5.

[0110] Step 7: Using the fixed floating-point solution obtained from the verified fixed set of non-difference fuzziness, substitute it back into the observation equation to output a non-difference fixed solution that combines stability and accuracy.

[0111] Figure 3 This diagram illustrates the structure of a non-differential ambiguity fixing device according to an embodiment of this application. The non-differential ambiguity fixing device provided in this embodiment can be used to execute the non-differential ambiguity fixing method provided in this embodiment. For parts not described in detail in the embodiments of the non-differential ambiguity fixing device provided in this embodiment, please refer to the descriptions in the embodiments of the non-differential ambiguity fixing method provided in this embodiment.

[0112] like Figure 3 As shown, the non-difference ambiguity fixing device provided in this application embodiment includes an acquisition unit 11, an execution unit 12, a solution unit 13, a calculation unit 14, a verification unit 15, and a constraint unit 16.

[0113] Acquisition unit 11 is used to acquire raw observation data;

[0114] Execution unit 12 is used to establish observation equations based on the original observation data, perform floating-point calculations, and obtain floating-point solutions, which include floating-point ambiguity.

[0115] Solving unit 13 is used to solve UPD based on the original observation data and floating-point ambiguity to obtain fixed non-difference ambiguity;

[0116] The calculation unit 14 is used to compose double-difference observations based on the original observation data and floating-point ambiguity, and obtain fixed double-difference ambiguity;

[0117] The verification unit 15 is used to verify the corresponding fixed non-difference ambiguity based on each fixed double-difference ambiguity;

[0118] The constraint unit 16 is used to obtain the non-differential fixed solution based on the verified fixed non-differential fuzzy constraint floating-point solution.

[0119] Optionally, the verification unit includes:

[0120] The first determining subunit is used to determine four fixed non-difference ambiguities corresponding to the fixed first double-difference ambiguity.

[0121] The first calculation subunit is used to obtain the second double-difference ambiguity corresponding to the first double-difference ambiguity based on a linear combination of four fixed non-difference ambiguities;

[0122] The judgment subunit is used to determine whether the first double-difference ambiguity and the second double-difference ambiguity are consistent; if they are consistent, the four fixed non-difference ambiguities are determined to pass the verification; otherwise, if they are inconsistent, the four fixed non-difference ambiguities are determined to fail the verification.

[0123] Optionally, the first determined subunit includes:

[0124] The second determining subunit is used to determine four fixed non-difference ambiguities corresponding to the first double-difference ambiguity based on the satellite and station corresponding to the first double-difference ambiguity;

[0125] The satellites and stations corresponding to the first double-difference ambiguity include the first satellite, the second satellite, the first station, and the second station. The four fixed non-difference ambiguities include: the non-difference ambiguities observed by the first station for the first satellite and the second satellite respectively, and the non-difference ambiguities observed by the second station for the first satellite and the second satellite respectively.

[0126] Optionally, the first computational subunit includes:

[0127] The second calculation subunit is used to calculate the difference in non-differential ambiguity between the observations of the first satellite and the second satellite by the first station, and to obtain the first difference value;

[0128] The third calculation subunit is used to calculate the difference in non-difference ambiguity between the observations of the first satellite and the second satellite by the second station, and to obtain the second difference value;

[0129] The fourth calculation subunit is used to calculate the difference between the first difference and the second difference to obtain the second double-difference ambiguity.

[0130] The non-differential ambiguity fixing device of this application embodiment acquires original observation data, establishes observation equations based on the original observation data, performs floating-point calculations to obtain floating-point solutions, wherein the floating-point solutions include floating-point ambiguities. Then, based on the original observation data and the floating-point ambiguities, the UPD is calculated to obtain fixed non-differential ambiguities, and double-difference observations are formed based on the original observation data and the floating-point ambiguities to obtain fixed double-difference ambiguities. Furthermore, the corresponding fixed non-differential ambiguities are verified based on each fixed double-difference ambiguity, thereby constraining the floating-point solutions with the verified fixed non-differential ambiguities to obtain a non-differential fixed solution. According to the embodiments of this application, the problem of low accuracy in related technologies where methods directly using non-differential or double-difference ambiguities for fixing are low is solved.

[0131] Figure 4 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0132] The electronic device may include a processor 301 and a memory 302 storing program instructions.

[0133] Specifically, the processor 301 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0134] Memory 302 may include mass storage for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 302 may include removable or non-removable (or fixed) media. Where appropriate, memory 302 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 302 is non-volatile solid-state memory.

[0135] In a particular embodiment, memory 302 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0136] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this application.

[0137] The processor 301 reads and executes the program instructions stored in the memory 302 to implement any of the non-difference ambiguity fixing methods in the above embodiments.

[0138] In one example, the electronic device may also include a communication interface 303 and a bus 310. For example, Figure 4 As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 310 and complete communication with each other.

[0139] The communication interface 303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0140] Bus 310 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel 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 combinations of two or more of these. Where appropriate, bus 310 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0141] In conjunction with the non-difference ambiguity fixing methods in the above embodiments, this application embodiment can provide a readable storage medium for implementation. This readable storage medium stores program instructions; when executed by a processor, these program instructions implement any of the non-difference ambiguity fixing methods in the above embodiments.

[0142] It should be clarified that this 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 this 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 of steps, after understanding the spirit of this application.

[0143] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "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 disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0144] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0145] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by program instructions. These program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. 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 diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0146] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for fixing non-differential ambiguity, characterized in that, include: Obtain raw observation data; An observation equation is established based on the original observation data, and a floating-point solution is obtained, which includes floating-point ambiguity. Based on the original observation data and the floating-point ambiguity, the UPD is calculated to obtain a fixed non-difference ambiguity. Based on the original observation data and the floating-point ambiguity, double-difference observation values ​​are formed, and a fixed double-difference ambiguity is obtained. The corresponding fixed non-difference ambiguity is verified based on each fixed double-difference ambiguity. Based on the verified fixed non-difference ambiguity, substitute it back into the observation equation to constrain the floating-point solution, and obtain the non-difference fixed solution.

2. The method according to claim 1, characterized in that, The step of verifying the corresponding fixed non-difference ambiguity based on each fixed double-difference ambiguity includes: For a fixed first double-difference ambiguity, determine four fixed non-difference ambiguities corresponding to the first double-difference ambiguity; The second double-difference ambiguity corresponding to the first double-difference ambiguity is obtained by linearly combining the four fixed non-difference ambiguities. Determine whether the first double-difference ambiguity and the second double-difference ambiguity are consistent; wherein, if they are consistent, determine that the four fixed non-difference ambiguities have passed the verification; otherwise, if they are inconsistent, determine that the four fixed non-difference ambiguities have failed the verification.

3. The method according to claim 2, characterized in that, The step of determining the four fixed non-difference ambiguities corresponding to the first double-difference ambiguity includes: Based on the satellite and station corresponding to the first double-difference ambiguity, four fixed non-difference ambiguities corresponding to the first double-difference ambiguity are determined; The satellites and stations corresponding to the first double-difference ambiguity include the first satellite, the second satellite, the first station, and the second station. The four fixed non-difference ambiguities include: the non-difference ambiguities observed by the first station for the first satellite and the second satellite, and the non-difference ambiguities observed by the second station for the first satellite and the second satellite, respectively.

4. The method according to claim 3, characterized in that, The step of obtaining the second double-difference ambiguity corresponding to the first double-difference ambiguity based on the linear combination of the four fixed non-difference ambiguities includes: The difference between the non-differential ambiguities observed by the first station for the first satellite and the second satellite is calculated to obtain the first difference value; The difference between the non-differential ambiguities observed by the second station from the first satellite and the second satellite is calculated to obtain the second difference value; The difference between the first difference and the second difference is calculated to obtain the second double-difference ambiguity.

5. A fixing device for non-differential ambiguity, characterized in that, include: The acquisition unit is used to acquire raw observation data; An execution unit is used to establish an observation equation based on the original observation data, perform floating-point calculations, and obtain a floating-point solution, wherein the floating-point solution includes floating-point ambiguity. The calculation unit is used to calculate the UPD to obtain a fixed non-difference ambiguity based on the original observation data and the floating-point ambiguity; The calculation unit is used to form double-difference observations based on the original observation data and the floating-point ambiguity, and obtain a fixed double-difference ambiguity. The verification unit is used to verify the corresponding fixed non-difference ambiguity based on each fixed double-difference ambiguity; The constraint unit is used to substitute back the observation equation to constrain the floating-point solution based on the verified fixed non-difference ambiguity, thereby obtaining the non-difference fixed solution.

6. The apparatus according to claim 5, characterized in that, The verification unit includes: The first determining subunit is used to determine four fixed non-difference ambiguities corresponding to the first double-difference ambiguity for a fixed first double-difference ambiguity; The first calculation subunit is used to obtain the second double-difference ambiguity corresponding to the first double-difference ambiguity based on the linear combination of the four fixed non-difference ambiguities; The judgment subunit is used to determine whether the first double-difference ambiguity and the second double-difference ambiguity are consistent; wherein, if they are consistent, the four fixed non-difference ambiguities are determined to pass the verification; otherwise, if they are inconsistent, the four fixed non-difference ambiguities are determined to fail the verification.

7. The apparatus according to claim 6, characterized in that, The first determining subunit includes: The second determining subunit is used to determine four fixed non-difference ambiguities corresponding to the first double-difference ambiguity based on the satellite and station corresponding to the first double-difference ambiguity; The satellites and stations corresponding to the first double-difference ambiguity include the first satellite, the second satellite, the first station, and the second station. The four fixed non-difference ambiguities include: the non-difference ambiguities observed by the first station for the first satellite and the second satellite, and the non-difference ambiguities observed by the second station for the first satellite and the second satellite, respectively.

8. The apparatus according to claim 7, characterized in that, The first computing subunit includes: The second calculation subunit is used to calculate the difference in non-differential ambiguity between the first station's observations of the first satellite and the second satellite, respectively, to obtain a first difference value; The third calculation subunit is used to calculate the difference in non-difference ambiguity between the observations of the first satellite and the second satellite by the second station, respectively, to obtain the second difference value; The fourth calculation subunit is used to calculate the difference between the first difference and the second difference to obtain the second double-difference ambiguity.

9. An electronic device, characterized in that, The electronic device includes: a processor and a memory storing program instructions; When the processor executes the program instructions, it implements the method for fixing non-difference ambiguity as described in any one of claims 1-4.

10. A readable storage medium, characterized in that, The readable storage medium stores program instructions that, when executed by a processor, implement the method for fixing non-difference ambiguity as described in any one of claims 1-4.

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