CN-122017883-A - PPP-RTK-oriented atmospheric delay dynamic space-time modeling and uncertainty quantization method

CN122017883ACN 122017883 ACN122017883 ACN 122017883ACN-122017883-A

Abstract

The invention discloses a PPP-RTK oriented atmospheric delay dynamic space-time modeling and uncertainty quantization method, which is based on regional reference station network to acquire atmospheric delay data, introducing a time dimension to construct a dynamic space-time observation window, performing space-time modeling on the atmospheric delay, and generating atmospheric delay prediction and initial uncertainty information at the position. Then, an uncertainty correction strategy of cross verification is carried out on an epoch-by-epoch basis, and the prediction uncertainty is adaptively corrected through the relation between the statistical error and the initial uncertainty. Finally, the corrected uncertainty is used for atmospheric constraint weighting in PPP-RTK positioning. According to the invention, through a dynamic space-time joint modeling and epoch-by-epoch cross verification method, the cooperative optimization of the atmospheric delay prediction precision and uncertainty is realized, and the precision, stability and reliability of PPP-RTK positioning under complex atmospheric conditions and different network scales are improved.

Inventors

GAO WANG
SUN ZHIHAN
PAN SHUGUO
ZHAO QING
TAO XIANLU

Assignees

东南大学

Dates

Publication Date: 20260512
Application Date: 20260305

Claims (6)

1. The atmosphere delay dynamic space-time modeling and uncertainty quantization method for PPP-RTK is characterized by comprising the following steps: step1, acquiring global satellite navigation system observation data of a regional reference station, combining a precise orbit, a precise clock error and a phase deviation product, performing PPP or PPP-AR calculation on the regional reference station, and extracting atmospheric delay observation data of the regional reference station; Step 2, based on the atmospheric delay observation data, introducing time dimension information, and constructing an atmospheric delay dynamic space-time observation window comprising a plurality of epochs, wherein the atmospheric delay dynamic space-time observation window is used for representing the continuous change characteristics of regional atmospheric delay in space and time; Step 3, in the dynamic space-time observation window, carrying out dynamic space-time modeling on regional atmospheric delay, generating an atmospheric delay prediction result at a target position, and synchronously obtaining initial prediction uncertainty information corresponding to the prediction result; Step 4, based on a cross verification strategy reserved from epoch to epoch, carrying out statistical analysis and correction on the initial prediction uncertainty information to obtain corrected uncertainty information consistent with the actual atmospheric delay error level; And 5, introducing the atmospheric delay prediction result and the uncertainty information corrected by the atmospheric delay prediction result into PPP-RTK positioning calculation at the user side as atmospheric enhancement constraint, completing the user positioning calculation based on an uncertainty self-adaptive weighting strategy, and outputting a user positioning result.
2. The method for dynamic space-time modeling and uncertainty quantization of the atmospheric delay for PPP-RTK according to claim 1, wherein the obtaining the atmospheric delay observations of the regional reference station in step 1 comprises: Establishing a precise single-point positioning observation model based on GNSS original observation data of a regional reference station, wherein the observation model is used for describing the relation among the observation quantity, unknown parameters and observation errors, and the unknown parameters at least comprise a receiver coordinate parameter, a receiver clock error parameter, a carrier phase ambiguity parameter and an atmospheric delay parameter; And obtaining the atmospheric delay estimated value of each reference station under different epochs by PPP or PPP-AR calculation of the observation model, and taking the estimated value as the observation input data of the subsequent dynamic space-time modeling.
3. The method for modeling and quantifying uncertainty in dynamic space-time of atmospheric delay for PPP-RTK according to claim 1, wherein constructing the dynamic space-time observation window in step 2 comprises: based on the atmospheric delay observation data of the regional reference station under different epochs acquired in the step 1, the first in the region The reference station is at The atmospheric delay observations at each epoch are noted: ; Wherein, the Represent the first The spatial position coordinates of the individual reference stations, Representing a corresponding observation epoch time; selecting a plurality of continuous epochs within a preset time range The atmospheric delay observation values of all the reference stations in the corresponding epoch are combined with the spatial positions thereof to form a dynamic space-time observation window, and the observation data set is expressed as: ; Wherein, the Indicating the number of regional reference stations, The method comprises the steps of representing the epoch number contained in a dynamic space-time observation window, wherein the dynamic space-time observation window is used for describing the joint change characteristic of regional atmosphere delay on spatial distribution and time evolution and updating along with epoch promotion so as to provide a space-time joint observation data base for dynamic space-time modeling of subsequent regional atmosphere delay.
4. The method for dynamic space-time modeling and uncertainty quantization of atmospheric delay for PPP-RTK according to claim 1, wherein the dynamic space-time modeling of regional atmospheric delay in step 3 comprises: And (3) in the dynamic space-time observation window constructed in the step (2), the regional atmosphere delay observation value is expressed as: ; Wherein, the In the form of a spatial position coordinate, Is epoch time; Is a trend term used for describing large-scale space-time variation of regional atmospheric delay; the random disturbance term is zero mean value and is used for describing local fluctuation and random error; (1) Expression of trend term The trend term is constructed by adopting a first order polynomial comprising space and time, and the expression is as follows: ; Wherein, the To be estimated as a trend parameter, the spatial gradient for characterizing regional atmospheric delay and its change characteristics over time are equivalently defined as a trend basis function vector: ; And order The following steps are: ; (2) Spatio-temporal correlation description of random disturbance terms The random disturbance term Having a spatio-temporal correlation, the correlation being determined by the spatial distance With time interval Co-determination, in one embodiment, a correlation function form with independent space and time is adopted: ; Wherein, the As a parameter of the spatial correlation scale, Is a time-dependent scale parameter; represents the first A plurality of spatiotemporal observations; (3) BLUP-based predictive solution For all observation points in dynamic space-time observation window And observations thereof Constructing a trend matrix And constructing an observation covariance matrix according to the space-time correlation For the target position and the target epoch Definition: ; in satisfying unbiased constraints Under the condition of (1) obtaining weight vector by BLUP Lagrange multiplier And then obtain the predicted value of the atmospheric delay at the target position And outputting initial prediction uncertainty information corresponding to the predicted value for uncertainty correction processing in the step 4.
5. The method for dynamic space-time modeling and uncertainty quantization of PPP-RTK-oriented atmospheric delay of claim 1, wherein the uncertainty quantization based on a cross-validation on an epoch-by-epoch basis of step4 comprises: Performing a leave-one-out cross-validation epoch by epoch along the time dimension Personal calendar element And (3) carrying out modeling prediction in the step (3) by using the rest epoch data to obtain the reference station in the epoch Predicted value at And calculates a prediction error: ; at the same time obtain corresponding initial prediction standard deviation Based on summary And (3) with Determining a global variance correction factor : ; Correcting the initial prediction standard deviation according to the initial prediction standard deviation to obtain a corrected prediction standard deviation: ; the said Used as an uncertainty input in the step 5 user-side PPP-RTK atmospheric enhanced positioning.
6. The method for dynamic space-time modeling and uncertainty quantization of PPP-RTK-oriented atmospheric delay as defined in claim 1, wherein the atmospheric uncertainty-based user-side PPP-RTK atmospheric enhancement positioning in step 5 comprises: Transmitting the regional atmosphere delay correction obtained in the step 3 and the uncertainty information obtained in the step 4 after correction to a user side, introducing the atmospheric delay correction as an external constraint into a PPP-RTK positioning and resolving model of the user side, and carrying out self-adaptive weighting on the corresponding constraint according to the uncertainty information, thereby completing PPP-RTK atmospheric enhancement and positioning and resolving of the user side and outputting a user positioning result.

Description

PPP-RTK-oriented atmospheric delay dynamic space-time modeling and uncertainty quantization method Technical Field The invention belongs to the technical field of GNSS (Global Navigation SATELLITE SYSTEM) positioning and navigation, and particularly relates to a PPP-RTK-oriented atmospheric delay dynamic space-time modeling and uncertainty quantization method. Background High-precision modeling and reliable uncertainty quantification of regional atmospheric delay correction are core preconditions for achieving high-quality PPP-RTK positioning services. In the PPP-RTK positioning system, a server estimates ionosphere and troposphere delays through a regional reference station network and broadcasts atmospheric delay correction information to a user side, so that the user can introduce atmospheric errors as external constraints into positioning calculation, thereby obviously shortening convergence time and improving positioning accuracy. Currently, in the regional atmosphere delay modeling method, the method based on the spatial interpolation or spatial statistics theory is widely applied because of relatively mature implementation and strong applicability. The existing regional atmosphere delay modeling flow generally follows the following steps of (1) carrying out PPP or PPP-AR calculation based on a regional reference station network to obtain an atmosphere delay estimated value of each reference station at discrete time, (2) carrying out regional modeling and interpolation on discrete atmosphere delay observation based on a reference station spatial distribution relation in a single epoch to generate an atmosphere delay correction number at a user position, (3) giving corresponding uncertainty estimation to a modeling result, introducing the correction number and the uncertainty as pseudo-observation into user side PPP-RTK positioning calculation, and (4) weighting atmosphere constraint according to the uncertainty to finish user positioning calculation. The above-described flow forms the basic technical framework of current PPP-RTK regional atmosphere enhancement services. Although the existing regional atmosphere delay modeling method improves the positioning performance of PPP-RTK to a certain extent, inherent defects caused by model idealization assumption are unavoidable. On one hand, the existing method focuses on space dimension modeling, the continuous evolution characteristic of atmospheric delay in time dimension is not considered sufficiently, and under the condition that ionosphere activity is enhanced or atmospheric disturbance is obvious, the correction is easy to generate discontinuity, hysteresis or mutation in time sequence, so that the positioning stability of a user is influenced. On the other hand, existing uncertainty estimation methods are typically based on model assumptions or finite residual statistics, which may have systematic deviations from the actual prediction error. When the uncertainty estimation of the atmospheric delay is too optimistic, the low-quality or abnormal atmospheric correction is given too high weight, and the ambiguity fixation abnormality or the abrupt change of the positioning result can be caused, and when the uncertainty estimation is too conservative, the restraint effect of the atmospheric correction is difficult to fully play, and the convergence speed and the precision advantage of PPP-RTK positioning are weakened. The problems are particularly prominent in the scenes of enhanced atmospheric activity, uneven distribution of reference stations or larger network scale, so that the accuracy, stability and reliability of a positioning result are difficult to be simultaneously considered. In addition, the traditional uncertainty evaluation method based on station-by-station leave-one-out cross verification can reflect the overall accuracy level of region modeling, but the evaluation result does not directly correspond to the working mode of generating correction products based on all reference stations in the actual PPP-RTK service, so that the dynamic change characteristics of the atmospheric delay prediction error in the time dimension are difficult to truly describe, and the application effect of the method in the real-time or quasi-real-time PPP-RTK service is limited. Therefore, how to introduce a modeling method capable of jointly describing the atmospheric delay time-space evolution characteristic under the existing PPP-RTK technical framework, and realize self-adaption and reliable quantification of uncertainty on the basis so as to improve the positioning precision and stability of a user side is still a technical problem to be solved currently. Disclosure of Invention In order to solve the problems, the invention discloses a PPP-RTK-oriented atmosphere delay dynamic space-time modeling and uncertainty quantification method, which is characterized in that a dynamic space-time joint modeling strategy is introduced in the regional atmosphere delay m