A high-precision navigation system and method, and navigation terminal device

Abstract

The present invention provides a high-precision navigation system and method, and a navigation terminal device. The navigation terminal device is configured to: obtain satellite observation data; calculate a floating-point solution and variance of satellite ambiguity; calculate a first group of integer ambiguities and variances using a first strategy; upload the obtained floating-point solution and variance of ambiguity to a navigation server via a network; receive a second group of integer ambiguities and variances of the navigation server via the network, wherein the second group of integer ambiguities and variances are calculated by the navigation server using a second strategy; and select multiple integer ambiguities and variances from the first group of integer ambiguities and variances and the second group of integer ambiguities and variances to form a selected group of integer ambiguities and variances. In this way, it is possible to support fast fixing of integer ambiguities with only a small amount of calculation.

Description

Technical Field

[0001] The present invention relates to the field of navigation, and in particular to a high-precision navigation system and method, and a navigation terminal device. Background Art

[0002] Real-time kinematic (RTK) positioning of the Global Navigation Satellite System (GNSS) is an effective high-precision positioning technology route for the low-cost automotive consumer market.

[0003] Navigation satellites transmit pseudorange, phase and Doppler observations. Pseudorange and phase observations can measure position, and Doppler observations can measure velocity. The accuracy of pseudorange observations is usually around 0.3 meters, and the theoretical accuracy of phase observations can reach 1 / 100 of the signal wavelength, with an accuracy between 2-3 mm. However, there is an additional unknown integer in the observation, namely the integer ambiguity. Therefore, this technology can provide centimeter-level dynamic positioning services under ideal observation conditions. The key lies in the rapid determination and correct verification of the integer ambiguity.

[0004] At present, the least squares decorrelation adjustment (LAMBDA) technology is applied to the rapid fixation of ambiguity. The key lies in: 1) reducing the correlation between ambiguities to reduce the ambiguity search space and improve the search efficiency; 2) determining the optimal ambiguity solution based on the integer least squares theory. The ambiguity verification methods are roughly divided into two categories: one is the ratio test based on the ambiguity residual; the other is the probability of success or failure based on the ambiguity variance calculation. In order to ensure the high fixation rate of the integer ambiguity, when all ambiguities cannot be fixed, a worst ambiguity solution is proposed through iteration, and other ambiguities are tried to be fixed until the alternative ambiguity combination passes the test position, that is, the ambiguity is partially fixed. The integer ambiguity weighted average method does not need to determine the optimal integer ambiguity solution. All ambiguity candidate combinations are weighted averaged according to the size of the sum of squares of the ambiguity residuals to obtain the final ambiguity combination. The disadvantage is that the amount of calculation is much greater than the former. The current implementation of fast fixation of integer ambiguity in low-cost terminals faces the following difficulties:

[0005] 1) The contradiction between the high fix rate of integer ambiguity and the limited memory and computing power of low-cost navigation terminal equipment.

[0006] 2) The contradiction between the reliability of integer ambiguity verification and the limited memory and computing power of low-cost navigation terminal equipment.

[0007] Therefore, it is necessary to propose a new solution to overcome the related problems. Summary of the invention

[0008] One of the purposes of the present invention is to provide a high-precision navigation system and method, which can enable a navigation terminal device to support rapid fixation of integer ambiguities with a relatively small amount of calculation.

[0009] A second object of the present invention is to provide a navigation terminal device that can support rapid fixation of integer ambiguity with only a small amount of calculation.

[0010] To achieve the purpose of the invention, according to one aspect of the present invention, the present invention provides a high-precision navigation system, which includes: a navigation server; a navigation terminal device, which is configured to: obtain satellite observation data; calculate satellite ambiguity floating-point solutions and variances based on the satellite observation data; calculate a first group of integer ambiguities and variances based on the obtained ambiguity floating-point solutions and variances using a first integer ambiguity search and verification strategy, wherein the first group of integer ambiguities and variances includes multiple integer ambiguities and variances; upload the obtained ambiguity floating-point solutions and variances to the navigation server via a network; and obtain the satellite ambiguity floating-point solutions and variances through the network. The network receives a second group of integer ambiguities and variances from the navigation server, wherein the second group of integer ambiguities and variances are calculated by the navigation server according to the obtained ambiguity floating-point solutions and variances using a second integer ambiguity search and verification strategy, the second group of integer ambiguities and variances includes multiple integer ambiguities and variances, and the amount of calculation required by the first integer ambiguity search and verification strategy is less than the amount of calculation required by the second integer ambiguity search and verification strategy; and multiple integer ambiguities and variances are selected from the first group of integer ambiguities and variances and the second group of integer ambiguities and variances to form a selected group of integer ambiguities and variances.

[0011] According to another aspect of the present invention, there is provided a high-precision navigation method, which comprises: a navigation terminal device obtains satellite observation data; the navigation terminal device calculates a satellite ambiguity floating-point solution and a variance based on the satellite observation data; the navigation terminal device calculates a first group of integer ambiguities and variances based on the obtained ambiguity floating-point solution and variance using a first integer ambiguity search and verification strategy, wherein the first group of integer ambiguities and variances comprises a plurality of integer ambiguities and variances; the navigation terminal device uploads the obtained ambiguity floating-point solution and variance to a navigation server via a network; the navigation terminal device transmits the obtained ambiguity floating-point solution and variance to a navigation server via the network Receive a second group of integer ambiguities and variances from the navigation server, wherein the second group of integer ambiguities and variances are calculated by the navigation server according to the obtained ambiguity floating-point solutions and variances using a second integer ambiguity search and verification strategy, the second group of integer ambiguities and variances includes multiple integer ambiguities and variances, and the amount of calculation required for the first integer ambiguity search and verification strategy is less than the amount of calculation required for the second integer ambiguity search and verification strategy; the navigation terminal device selects multiple integer ambiguities and variances from the first group of integer ambiguities and variances and the second group of integer ambiguities and variances to form a selected group of integer ambiguities and variances.

[0012] According to another aspect of the present invention, there is provided a navigation terminal device, which includes a satellite positioning receiver, a processing module, and a wireless transmission module, wherein the navigation terminal device is configured to: obtain satellite observation data; calculate a satellite ambiguity floating-point solution and variance based on the satellite observation data; calculate a first group of integer ambiguities and variances based on the obtained ambiguity floating-point solution and variance using a first integer ambiguity search and verification strategy, wherein the first group of integer ambiguities and variances includes multiple integer ambiguities and variances; upload the obtained ambiguity floating-point solution and variance to a navigation server via a network; and The network receives a second set of integer ambiguities and variances from the navigation server, wherein the second set of integer ambiguities and variances are calculated by the navigation server according to the obtained ambiguity floating-point solutions and variances using a second integer ambiguity search and verification strategy, the second set of integer ambiguities and variances includes multiple integer ambiguities and variances, and the amount of calculation required for the first integer ambiguity search and verification strategy is less than the amount of calculation required for the second integer ambiguity search and verification strategy; multiple integer ambiguities and variances are selected from the first set of integer ambiguities and variances and the second set of integer ambiguities and variances to form a selected set of integer ambiguities and variances.

[0013] Compared with the prior art, the navigation terminal device in the present invention can support fast fixation of integer ambiguity with only a small amount of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A schematic diagram of the structure of a high-precision navigation system in one embodiment of the present invention;

[0015] Figure 2 A schematic diagram of the structure of a navigation terminal device in an embodiment of the present invention;

[0016] Figure 3 FIG. 4 is a flow chart of a high-precision navigation method in one embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0018] The present invention provides a high-precision navigation system. Based on this architecture, the high-precision navigation system can run on a low-cost (for example, US$50) navigation terminal device, and only requires a small amount of calculation to support fast fixation of integer ambiguity, thereby resolving the contradiction between the high fixation rate of integer ambiguity and the limited memory and computing power of the low-cost navigation terminal device, as well as the contradiction between the reliability of integer ambiguity verification and the limited memory and computing power of the low-cost navigation terminal device.

[0019] Figure 1 FIG. 1 is a schematic diagram of the structure of a high-precision navigation system 100 of the present invention in one embodiment. The high-precision navigation system 100 includes a navigation terminal device 102 and a navigation server 106 .

[0020] There may be a plurality of navigation terminal devices 102. The navigation terminal device 102 may be installed on a motor vehicle to perform high-precision navigation for the driving navigation of the motor vehicle, especially unmanned driving. The navigation terminal device 102 may communicate with the navigation server 106 via a wireless network 104. The wireless network 104 may be a 2G, 3G, 4G or 5G network, or a combination of multiple networks, such as Bluetooth + 4G, Wifi + 4G, Wifi + Internet + 5G, etc. The present invention has no requirements for the specific type of the wireless network 104, as long as it can support stable communication.

[0021] Figure 2 FIG. 2 is a schematic diagram of the structure of a navigation terminal device 102 in one embodiment of the present invention. The navigation terminal device 102 includes a satellite positioning receiver 220 , a processing module 230 and a wireless transmission module 240 .

[0022] Figure 3 FIG. 1 is a flow chart of a high-precision navigation method in one embodiment of the present invention. Figure 3 Here we introduce the specific implementation scheme of the high-precision navigation system and method in the present invention.

[0023] Step 310: The navigation terminal device obtains satellite observation data.

[0024] Specifically, the satellite positioning receiver 220 of the navigation terminal device obtains satellite observation data, and the satellite observation data includes pseudorange observation values, phase observation values ​​and Doppler observation values.

[0025] Step 320: The navigation terminal device calculates a floating-point solution and a variance of the satellite ambiguity based on the satellite observation data.

[0026] Specifically, the navigation terminal device 102 also obtains the pseudo-range observation value and phase observation value of the reference station. The reference station is a commonly used technology in satellite navigation. The reference station is a navigation station with a known position. The setting of the reference station is helpful for high-precision satellite positioning. The navigation terminal device 102 obtains the ambiguity floating-point solution through real-time dynamic positioning (RTK) floating-point solution based on the pseudo-range observation value and phase observation value of the reference station and the pseudo-range observation value and phase observation value obtained by the local navigation terminal device 102 (also referred to as the user station). and the variance and

[0027] The specific calculation process is as follows:

[0028] For short-range RTK (baseline less than 20 km), the single-difference GNSS observation model between the reference station and the user station is as follows:

[0029]

[0030]

[0031] In formulas (1) and (2), Δ represents the single difference between stations; P and L represent the GNSS pseudorange and phase observations, respectively; the subscripts i and s represent the frequency and satellite PRN number, respectively; p is the position; c is the speed of light; t is the clock error; r is the receiver; d is the pseudorange deviation; u is the phase deviation; N is the ambiguity. ε is the observation error.

[0032] Select reference satellites to form double-difference observations between non-reference satellites and reference satellites, eliminating receiver clock errors and pseudo-range phase deviations.

[0033]

[0034]

[0035] Represents the intersatellite single difference.

[0036] For GPS, GLONASS, GALILLEO and BEIDOU systems, the estimated state parameters are the position and double-difference ambiguity corrections:

[0037] Estimate the ambiguity float solution and variance via least squares or Kalman filtering.

[0038] Step 330: the wireless transmission module 240 of the navigation terminal device 102 may obtain the ambiguity floating point solution. and the variance and Uploaded to the navigation server 106 via the network 104 .

[0039] Step 340: the navigation terminal device 102 solves the ambiguity floating point solution and the variance and The first set of integer ambiguities and variances are calculated using the first integer ambiguity search and verification strategy, wherein the first set of integer ambiguities and variances includes multiple integer ambiguities and variances, and each integer ambiguity and variance corresponds to a frequency band of a satellite.

[0040] Step 350: the navigation server 106 solves the ambiguity floating point solution and the variance and The second set of integer ambiguities and variances are calculated using the second integer ambiguity search and verification strategy, wherein the second set of integer ambiguities and variances includes multiple integer ambiguities and variances, and each integer ambiguity and variance corresponds to a frequency band of a satellite.

[0041] It should be noted that step 340 and step 350 are performed synchronously by the navigation terminal device 102 and the navigation server 106 respectively, and there is no order relationship between the two. The computational amount required for the first integer ambiguity search and verification strategy is less than the computational amount required for the second integer ambiguity search and verification strategy.

[0042] Preferably, the first full-cycle ambiguity search and verification strategy includes:

[0043] Set the maximum fixed ambiguity number and the minimum tracking epoch number and the maximum ambiguity variance

[0044] The ambiguities and variances that meet the conditions are used to determine the optimal group of candidate integer ambiguities and variances and the suboptimal group of candidate integer ambiguities and variances in the search space by using the least squares criterion;

[0045] According to the optimal group of candidate integer ambiguities and variances and the suboptimal group of candidate integer ambiguities and variances, it is determined whether to fix the first group of integer ambiguities and variances based on the optimal group of candidate integer ambiguities and variances (verification step).

[0046] The preferred second integer ambiguity search and verification strategy includes:

[0047] Set the minimum number of tracking epochs and the maximum ambiguity variance

[0048] The qualified ambiguities and variances are used in the search space by using the least squares criterion to determine m groups of candidate integer ambiguities and variances, where m is greater than or equal to 3;

[0049] The second set of integer ambiguities and variances are calculated based on the m sets of candidate integer ambiguities and variances (verification step).

[0050] Since the first integer ambiguity search and verification strategy sets a maximum fixed ambiguity number, while the second integer ambiguity search and verification strategy does not set a maximum fixed ambiguity number, the computational complexity of the first integer ambiguity search and verification strategy can be reduced. In addition, the verification step in the first integer ambiguity search and verification strategy saves more computational complexity than the verification step in the second integer ambiguity search and verification strategy.

[0051] In one embodiment, the first integer ambiguity search and verification strategy includes:

[0052] The ambiguity floating point solution and variance are transformed into Z space to remove the correlation between ambiguities, and the ambiguity floating point solution and variance in Z space are obtained, that is, and

[0053] Set the maximum fixed blur Minimum tracking epochs and the maximum ambiguity variance Discard those that do not meet the minimum tracking epoch number and the maximum ambiguity variance If the number of remaining ambiguities exceeds The fuzziness with larger variance is discarded;

[0054] The ambiguities and variances that meet the conditions are determined in the search space by the least squares criterion to determine the optimal group of candidate integer ambiguities and variances. and And the candidate integer ambiguity and variance of the suboptimal group and

[0055] Calculate the corresponding residual squared sum ratio value R,

[0056]

[0057] If R is greater than a predetermined threshold, the optimal group of candidate integer ambiguities and variances are fixed; otherwise, after removing the ambiguity with the largest variance, the remaining ambiguities and variances are continued to be determined in the search space by the least squares criterion to obtain the next optimal group of candidate integer ambiguities and variances. and And the candidate integer ambiguity and variance of the suboptimal group and

[0058] The fixed satellite integer modulus ambiguity and variance in Z space are converted to normal space to obtain the first set of integer ambiguity and variance, that is, and

[0059] In one embodiment, the second integer ambiguity search and verification strategy includes:

[0060] The ambiguity floating point solution and variance are transformed into Z space to remove the correlation between ambiguities. The ambiguity floating point solution and variance in Z space are obtained, that is, and

[0061] Set the minimum number of tracking epochs and the maximum ambiguity variance Need to discard those that do not meet the minimum number of tracking epochs and the maximum ambiguity variance The fuzziness and variance of

[0062] The ambiguities and variances that meet the conditions are determined in the search space by the least squares criterion to obtain the optimal m groups of candidate integer ambiguities and variances. and

[0063] Calculate the chi value of each group of candidate integer ambiguity. The chi value of the kth group of candidate integer ambiguity is calculated as follows:

[0064]

[0065] Get the chi corresponding to the optimal combination of fuzziness b (i.e. the smallest chi).

[0066] The weight of each group of candidate integer ambiguities is calculated according to the chi value:

[0067]

[0068]

[0069]

[0070] Calculate the weighted average z of the integer ambiguity and variancew and Q w :

[0071] and

[0072] The weighted average integer ambiguity and variance z in Z space w and Q w Converting to normal space gives the second set of integer ambiguities and variances, namely: and

[0073] In step 360, the navigation terminal device 102 selects a plurality of integer ambiguities and variances from the first set of integer ambiguities and variances and the second set of integer ambiguities and variances to form a selected set of integer ambiguities and variances. Preferably, a plurality of more reliable integer ambiguities and variances are selected to form the selected set of integer ambiguities and variances.

[0074] In one embodiment, for There is a fixed integer ambiguity in If there is no fixed integer ambiguity in The fixed integer ambiguity in can be set to 1.0-e8 corresponding to the variance, but it can also be set to other values, such as zero;

[0075] for Neutralization There is a fixed integer ambiguity in both. If the difference between the two is less than a predetermined threshold, such as 0.01 week, it is considered to be fixed correctly and the or The fixed integer ambiguity in , otherwise, it is considered to be fixed error, and the initial floating point ambiguity and variance are used;

[0076] for Neutralization The integer ambiguity is not fixed in Neutralization In the example, floating point ambiguities and variances are used as unfixed integer ambiguities and variances, so we use Floating point blurriness and variance in ;

[0077] for The fixed integer ambiguity in There is no fixed integer ambiguity in The fixed integer ambiguities and variances in .

[0078] In the present invention, the ambiguity fixing and verification method is optimized for low-cost navigation terminal equipment to ensure a high fixing rate and reliability of the ambiguity fixing.

[0079] Finally, the navigation terminal device can perform positioning based on the integer ambiguity and variance of the filtered group and the satellite observation data, thereby obtaining the precise position of the navigation terminal device.

[0080] like Figure 3 As shown, steps 310, 320, 330, 340, and 360 are implemented on the navigation terminal device, and step 350 is implemented on the navigation server.

[0081] For the relevant implementation details of the high-precision navigation method, please refer to the high-precision navigation system mentioned above, which will not be repeated here.

[0082] In this document, the terms "comprises," "comprising," or any other variations thereof, are intended to cover a non-exclusive inclusion of elements other than those listed and may also include additional elements not expressly listed.

[0083] In this document, the directional words such as front, back, top, and bottom are defined by the positions of the components in the drawings and the positions of the components relative to each other, and are only for the sake of clarity and convenience in expressing the technical solution. It should be understood that the use of the directional words should not limit the scope of protection claimed in this application.

[0084] In the absence of conflict, the above embodiments and features in the embodiments may be combined with each other.

[0085] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A high-precision navigation system, characterized in that: It includes: Navigation server; Navigation terminal device, which is configured with: Obtain satellite observation data; Calculate the satellite ambiguity floating point solution and variance based on the satellite observation data; A first set of integer ambiguities and variances are calculated based on the obtained ambiguity floating point solutions and variances using a first integer ambiguity search and verification strategy, wherein the first set of integer ambiguities and variances includes a plurality of integer ambiguities and variances; The obtained ambiguity floating point solution and variance are uploaded to the navigation server via the network; receiving, through the network, a second set of integer ambiguities and variances of the navigation server, wherein the second set of integer ambiguities and variances are calculated by the navigation server according to the obtained ambiguity floating point solutions and variances using a second integer ambiguity search and verification strategy, the second set of integer ambiguities and variances includes a plurality of integer ambiguities and variances, and the amount of calculation required by the first integer ambiguity search and verification strategy is less than the amount of calculation required by the second integer ambiguity search and verification strategy; A plurality of integer ambiguities and variances are selected from the first group of integer ambiguities and variances and the second group of integer ambiguities and variances to form a selected group of integer ambiguities and variances.

2. The high-precision navigation system according to claim 1, characterized in that: The satellite observation data includes pseudorange observation values, phase observation values ​​and Doppler observation values. Each integer ambiguity and variance corresponds to a frequency band of a satellite. Position determination is performed based on the filtered set of integer ambiguities and variances and the satellite observation data.

3. The high-precision navigation system according to claim 1, characterized in that: The satellite observation data includes pseudorange observation values, phase observation values ​​and Doppler observation values. The navigation terminal device obtains the pseudorange observation values ​​and phase observation values ​​of the reference station. The ambiguity floating point solution is obtained by real-time dynamic positioning floating point solution calculation based on the pseudorange observation values ​​and phase observation values ​​of the reference station and the pseudorange observation values ​​and phase observation values ​​obtained locally by the navigation terminal device. and variance 4. The high-precision navigation system according to claim 1, characterized in that: The first full week fuzzy search and verification strategy includes: Set the maximum fixed ambiguity number and the minimum tracking epoch number and the maximum ambiguity variance The ambiguities and variances that meet the conditions are used to determine the optimal group of candidate integer ambiguities and variances and the suboptimal group of candidate integer ambiguities and variances in the search space by using the least squares criterion; According to the optimal group of candidate integer ambiguities and variances and the suboptimal group of candidate integer ambiguities and variances, it is determined whether to fix the first group of integer ambiguities and variances based on the optimal group of candidate integer ambiguities and variances.

5. The high-precision navigation system according to claim 1, characterized in that: The first full week fuzzy search and verification strategy includes: The ambiguity floating point solution and variance are transformed into Z space to remove the correlation between ambiguities, and the ambiguity floating point solution and variance in Z space are obtained, that is, and Set the maximum fixed blur Minimum number of tracking epochs and the maximum ambiguity variance Discard those that do not meet the minimum tracking epoch number and the maximum ambiguity variance If the number of remaining ambiguities exceeds The fuzziness with larger variance is discarded; The ambiguities and variances that meet the conditions are determined in the search space by the least squares criterion to determine the optimal group of candidate integer ambiguities and variances. and And the candidate integer ambiguity and variance of the suboptimal group and Calculate the corresponding residual squared sum ratio value R, If R is greater than a predetermined threshold, the optimal group of candidate integer ambiguities and variances are fixed; otherwise, after removing the ambiguity with the largest variance, the remaining ambiguities and variances are continued to be determined in the search space by the least squares criterion to obtain the next optimal group of candidate integer ambiguities and variances. and And the candidate integer ambiguity and variance of the suboptimal group and The fixed satellite integer ambiguity and variance in Z space are converted to normal space to obtain the first set of integer ambiguity and variance, that is, and 6. The high-precision navigation system according to claim 1, characterized in that: The second full week fuzzy search and verification strategy includes: Set the minimum number of tracking epochs and the maximum ambiguity variance The qualified ambiguities and variances are used in the search space by using the least squares criterion to determine m groups of candidate integer ambiguities and variances, where m is greater than or equal to 3; The second set of integer ambiguities and variances are calculated based on the m sets of candidate integer ambiguities and variances.

7. The high-precision navigation system or method according to claim 1, characterized in that: The second full week fuzzy search and verification strategy includes: The ambiguity floating point solution and variance are transformed into Z space to remove the correlation between ambiguities, and the ambiguity floating point solution and variance in Z space are obtained, that is, and Set the minimum number of tracking epochs and the maximum ambiguity variance Need to discard those that do not meet the minimum number of tracking epochs and the maximum ambiguity variance The fuzziness and variance of The ambiguities and variances that meet the conditions are determined in the search space by the least squares criterion to obtain the optimal m groups of candidate integer ambiguities and variances. and Calculate the chi value of each set of candidate integer ambiguities and obtain the chi value corresponding to the optimal combination of ambiguities. b , i.e. the smallest chi, the kth group of candidate integer ambiguity chi k The calculation is as follows Where k = 1 ~ m, The weight of each group of candidate integer ambiguities is calculated according to the chi value: Calculate the weighted average z of the integer ambiguity and variance w and Q w : and The weighted average integer ambiguity and variance z in Z space w and Q w Converting to normal space gives the second set of integer ambiguities and variances, namely: and 8. The high-precision navigation system according to claim 1, characterized in that: From the first set of integer ambiguities and variances and and the second set of integer ambiguities and variances and The multiple integer ambiguities and variances are selected to form a selection group. The integer ambiguities and variances include: for There is a fixed integer ambiguity in If there is no fixed integer ambiguity in The fixed integer ambiguity in ; for Neutralization There are fixed integer ambiguities in both. If the difference between the two is less than a predetermined threshold, it is considered that the fix is ​​correct and the or The fixed integer ambiguity in , otherwise it is considered fixed error, and the initial floating point ambiguity and variance are used; for Neutralization The integer ambiguity is not fixed in Floating point blurriness and variance in ; for The fixed integer ambiguity in There is no fixed integer ambiguity in The fixed integer ambiguities and variances in .

9. A high-precision navigation method, characterized in that: It includes: The navigation terminal equipment obtains satellite observation data; The navigation terminal device calculates the satellite ambiguity floating point solution and variance based on the satellite observation data; The navigation terminal device calculates a first set of integer ambiguities and variances according to the obtained ambiguity floating point solutions and variances using a first integer ambiguity search and verification strategy, wherein the first set of integer ambiguities and variances includes a plurality of integer ambiguities and variances; The navigation terminal device uploads the obtained ambiguity floating point solution and variance to the navigation server via the network; The navigation terminal device receives a second set of integer ambiguities and variances from the navigation server through the network, wherein the second set of integer ambiguities and variances are calculated by the navigation server according to the obtained ambiguity floating point solutions and variances using a second integer ambiguity search and verification strategy, the second set of integer ambiguities and variances includes a plurality of integer ambiguities and variances, and the amount of calculation required by the first integer ambiguity search and verification strategy is less than the amount of calculation required by the second integer ambiguity search and verification strategy; The navigation terminal device selects a plurality of more reliable integer ambiguities and variances from the first group of integer ambiguities and variances and the second group of integer ambiguities and variances to form a selected group of integer ambiguities and variances.

10. The high-precision navigation method according to claim 9, characterized in that: The satellite observation data includes pseudorange observation values, phase observation values ​​and Doppler observation values. Each integer ambiguity and variance corresponds to a frequency band of a satellite. Position determination is performed based on the filtered set of integer ambiguities and variances and the satellite observation data.

11. The high-precision navigation method according to claim 9, characterized in that: The satellite observation data includes pseudorange observation values, phase observation values ​​and Doppler observation values. The navigation terminal device obtains the pseudorange observation values ​​and phase observation values ​​of the reference station. The ambiguity floating point solution is obtained by real-time dynamic positioning floating point solution calculation based on the pseudorange observation values ​​and phase observation values ​​of the reference station and the pseudorange observation values ​​and phase observation values ​​obtained locally by the navigation terminal device. and variance 12. The high-precision navigation method according to claim 9, characterized in that: The first full week fuzzy search and verification strategy includes: Set the maximum fixed ambiguity number and the minimum tracking epoch number and the maximum ambiguity variance The ambiguities and variances that meet the conditions are used to determine the optimal group of candidate integer ambiguities and variances and the suboptimal group of candidate integer ambiguities and variances in the search space by using the least squares criterion; According to the optimal group of candidate integer ambiguities and variances and the suboptimal group of candidate integer ambiguities and variances, it is determined whether to fix the first group of integer ambiguities and variances based on the optimal group of candidate integer ambiguities and variances.

13. The high-precision navigation method according to claim 9, characterized in that: The first full week fuzzy search and verification strategy includes: The ambiguity floating point solution and variance are transformed into Z space to remove the correlation between ambiguities, and the ambiguity floating point solution and variance in Z space are obtained, that is, and Set the maximum fixed blur Minimum number of tracking epochs and the maximum ambiguity variance Discard those that do not meet the minimum tracking epoch number and the maximum ambiguity variance If the number of remaining ambiguities exceeds The fuzziness with larger variance is discarded; The ambiguities and variances that meet the conditions are determined in the search space by the least squares criterion to determine the optimal group of candidate integer ambiguities and variances. and And the candidate integer ambiguity and variance of the suboptimal group and Calculate the corresponding residual squared sum ratio value R, If R is greater than a predetermined threshold, the optimal group of candidate integer ambiguities and variances are fixed; otherwise, after removing the ambiguity with the largest variance, the remaining ambiguities and variances are continued to be determined in the search space by the least squares criterion to obtain the next optimal group of candidate integer ambiguities and variances. and And the candidate integer ambiguity and variance of the suboptimal group and The fixed satellite integer ambiguity and variance in Z space are converted to normal space to obtain the first set of integer ambiguity and variance, that is, and 14. The high-precision navigation method according to claim 9, characterized in that: The second full week fuzzy search and verification strategy includes: Set the minimum number of tracking epochs and the maximum ambiguity variance The qualified ambiguities and variances are used in the search space by using the least squares criterion to determine m groups of candidate integer ambiguities and variances, where m is greater than or equal to 3; The second set of integer ambiguities and variances are calculated based on the m sets of candidate integer ambiguities and variances.

15. The high-precision navigation system or method according to claim 9, characterized in that: The second full week fuzzy search and verification strategy includes: The ambiguity floating point solution and variance are transformed into Z space to remove the correlation between ambiguities, and the ambiguity floating point solution and variance in Z space are obtained, that is, and Set the minimum number of tracking epochs and the maximum ambiguity variance Need to discard those that do not meet the minimum number of tracking epochs and the maximum ambiguity variance The fuzziness and variance of The ambiguities and variances that meet the conditions are determined in the search space by the least squares criterion to obtain the optimal m groups of candidate integer ambiguities and variances. and Calculate the chi value of each set of candidate integer ambiguities and obtain the chi value corresponding to the optimal combination of ambiguities. b , i.e. the smallest chi, the kth group of candidate integer ambiguity chi k The calculation is as follows Where k = 1 ~ m, The weight of each group of candidate integer ambiguities is calculated according to the chi value: Calculate the weighted average z of the integer ambiguity and variance w and Q w : and The weighted average integer ambiguity and variance z in Z space w and Q w Converting to normal space gives the second set of integer ambiguities and variances, namely: and 16. The high-precision navigation method according to claim 9, characterized in that: From the first set of integer ambiguities and variances and and the second set of integer ambiguities and variances and The multiple integer ambiguities and variances are selected to form a selection group. The integer ambiguities and variances include: for There is a fixed integer ambiguity in If there is no fixed integer ambiguity in The fixed integer ambiguity in ; for Neutralization There are fixed integer ambiguities in both. If the difference between the two is less than a predetermined threshold, it is considered that the fix is ​​correct and the or The fixed integer ambiguity in , otherwise it is considered fixed error, and the initial floating point ambiguity and variance are used; for Neutralization The integer ambiguity is not fixed in Floating point blurriness and variance in ; for The fixed integer ambiguity in There is no fixed integer ambiguity in The fixed integer ambiguities and variances in .

17. A navigation terminal device, characterized in that: It includes a satellite positioning receiver, a processing module, and a wireless transmission module. The navigation terminal device is configured as follows: Obtain satellite observation data; Calculate the satellite ambiguity floating point solution and variance based on the satellite observation data; A first set of integer ambiguities and variances are calculated based on the obtained ambiguity floating point solutions and variances using a first integer ambiguity search and verification strategy, wherein the first set of integer ambiguities and variances includes a plurality of integer ambiguities and variances; The obtained ambiguity floating point solution and variance are uploaded to the navigation server via the network; receiving, through the network, a second set of integer ambiguities and variances of the navigation server, wherein the second set of integer ambiguities and variances are calculated by the navigation server according to the obtained ambiguity floating point solutions and variances using a second integer ambiguity search and verification strategy, the second set of integer ambiguities and variances includes a plurality of integer ambiguities and variances, and the amount of calculation required by the first integer ambiguity search and verification strategy is less than the amount of calculation required by the second integer ambiguity search and verification strategy; A plurality of integer ambiguities and variances are selected from the first group of integer ambiguities and variances and the second group of integer ambiguities and variances to form a selected group of integer ambiguities and variances.

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