CN-122017912-A - Intelligent outdoor positioning method, device and system based on RTK and storage medium

CN122017912ACN 122017912 ACN122017912 ACN 122017912ACN-122017912-A

Abstract

The invention relates to an intelligent outdoor positioning method, system, device and storage medium based on RTK, wherein the method comprises the steps of obtaining a carrier phase observation value, inertia measurement data and environment data through a positioning terminal, carrying out anomaly diagnosis and correlation analysis on the carrier phase observation value based on the environment data to generate dynamic observation weight and phase correction, carrying out tight coupling fusion calculation on the inertia measurement data according to the dynamic observation weight and the phase correction to obtain fusion data, and carrying out direction constraint and carrier phase fixation on the fusion data according to the environment data to obtain a positioning result. The invention can realize the technical crossing from passive to active adaptation, and obviously improve the precision and reliability of RTK positioning under a severe outdoor scene.

Inventors

HE XIAOZE
SONG CHUANSHENG
LIU KAIHENG

Assignees

深圳市康凯思特通讯设备有限公司

Dates

Publication Date: 20260512
Application Date: 20260325

Claims (10)

1. An intelligent outdoor positioning method based on RTK, which is characterized by comprising the following steps: acquiring a carrier phase observation value, inertial measurement data and environmental data through a positioning terminal; performing anomaly diagnosis and correlation analysis on the carrier phase observation value based on the environmental data to generate dynamic observation weight and phase correction; Performing tight coupling fusion calculation on the inertial measurement data according to the dynamic observation weight and the phase correction amount to obtain fusion data; And carrying out direction constraint and carrier phase fixation on the fusion data according to the environment data to obtain a positioning result.
2. The RTK-based intelligent outdoor positioning method of claim 1, wherein the acquiring carrier phase observations, inertial measurement data, and environmental data by a positioning terminal includes: Acquiring and extracting an original carrier phase signal through a GNSS receiving module of the positioning terminal, and converting the original carrier phase signal into the carrier phase observation value; Acquiring angular velocity readings and acceleration readings in three orthogonal axial directions through an inertial measurement module of the positioning terminal, and integrating the angular velocity readings and the acceleration readings to obtain inertial measurement data; And acquiring the environmental data through an environmental sensor of the positioning terminal.
3. The RTK-based intelligent outdoor positioning method of claim 1, wherein the performing anomaly diagnosis and correlation analysis on the carrier phase observations based on the environmental data, generating dynamic observation weights and phase corrections, comprises: Extracting an environmental characteristic parameter corresponding to the carrier phase observation value from the environmental data; Comparing the carrier phase observed value with a preset phase quality threshold, if the carrier phase observed value exceeds the phase quality threshold, marking the carrier phase observed value as an observed value to be verified, otherwise, judging the carrier phase observed value as a normal observed value; when the observation value to be verified and the environmental characteristic parameter are detected to meet a preset interference condition, judging that the observation value to be verified is an abnormal observation value; performing confidence calculation and weight setting on the observation value to be verified according to the environmental characteristic parameters to obtain the dynamic observation weight; And carrying out deviation recognition on the abnormal observed value based on the preset interference condition, and carrying out phase compensation on the deviation degree data obtained by recognition and the environmental characteristic parameter to obtain the phase correction quantity.
4. The RTK-based intelligent outdoor positioning method of claim 1, wherein the performing a close-coupled fusion solution on the inertial measurement data according to the dynamic observation weight and the phase correction amount to obtain fusion data includes: Acquiring an acquisition time period of the positioning terminal, and performing motion state recursion on the inertial measurement data based on the acquisition time period through a state prediction unit of a state space model to obtain a prediction state and a prediction error; the carrier phase observation value is subjected to weighted correction according to the dynamic observation weight and the phase correction quantity through an observation unit, so that a weighted correction observation value is obtained; Comparing the weighted correction observed value with the prediction state through a close coupling fusion unit, and carrying out state correction on the obtained state comparison value and the prediction error to obtain a state correction amount; And fusing and updating the state correction quantity and the prediction state through a tightly coupled fusion unit to obtain the fused data.
5. The RTK-based intelligent outdoor positioning method of claim 4, wherein the performing, by the state prediction unit of the state space model, motion state recursion on the inertial measurement data based on the acquisition time period to obtain a predicted state and a predicted error includes: extracting an angular velocity sequence and an acceleration sequence in the acquisition time period from the inertial measurement data by the state prediction unit; sequentially performing time increment calculation on the recursion starting point according to the angular velocity sequence and the acceleration sequence by taking the inertial measurement data corresponding to the starting time of the acquisition time period as the recursion starting point to obtain position increment, velocity increment and attitude increment of each time; carrying out state prediction on the inertial measurement data based on the position increment, the speed increment and the attitude increment to obtain the prediction state; and carrying out deviation transfer calculation on the prediction state according to a preset state deviation rule and the acquisition time period to obtain the prediction error.
6. The RTK-based intelligent outdoor positioning method of claim 4, wherein comparing the weighted correction observation value with the prediction state through a close-coupling fusion unit, and performing state correction on the obtained state comparison value and the prediction error to obtain a state correction amount, includes: Performing phase difference value calculation on the corrected carrier phase value in the weighted corrected observed value and the predicted carrier phase value in the predicted state through the tight coupling fusion unit to obtain a phase residual sequence; Performing pseudo-range difference calculation on the corrected pseudo-range value in the weighted corrected observed value and the predicted pseudo-range value in the predicted state to obtain a pseudo-range residual sequence; integrating the phase residual sequence and the pseudo-range residual sequence to obtain an observation residual vector; Performing linear transformation on the observation residual vector, a state transition matrix and an observation matrix in the prediction error to obtain a state correction gain value; and carrying out correction constraint on the state correction gain value based on the observation residual vector to obtain the state correction quantity.
7. The RTK-based intelligent outdoor positioning method of claim 1, wherein the performing direction constraint and carrier phase fixing on the fusion data according to the environmental data to obtain a positioning result includes: Extracting current scene characteristics and motion direction characteristics from the environment data, and extracting a position increment sequence and a phase floating solution from the fusion data; Screening out corresponding scene constraint rules from a preset constraint rule table according to the current scene characteristics, and carrying out direction component correction on the position increment sequence according to the scene constraint rules and combining the motion direction characteristics to obtain a constraint position increment sequence; Performing successive calculation on the phase floating solution and a predefined integer candidate set to obtain a candidate integer residual value, and detecting whether the candidate integer residual value smaller than a preset residual threshold exists; If the candidate integer residual value is smaller than the preset residual threshold, setting the corresponding candidate integer as a fixed solution, otherwise, setting the phase floating solution as the fixed solution directly; And carrying out iterative positioning calculation on the constraint position increment sequence and the fixed solution to obtain the positioning result.
8. An intelligent outdoor positioning device based on RTK, characterized in that it is applied to the intelligent outdoor positioning method based on RTK as claimed in any one of the above claims 1-7, comprising: The acquisition module is used for acquiring carrier phase observation values, inertial measurement data and environmental data through the positioning terminal; the analysis module is used for carrying out abnormality diagnosis and relevance analysis on the carrier phase observation value based on the environmental data and generating dynamic observation weight and phase correction; The association module is used for carrying out tight coupling fusion calculation on the inertial measurement data according to the dynamic observation weight and the phase correction quantity to obtain fusion data; and the processing module is used for carrying out direction constraint and carrier phase fixation on the fusion data according to the environmental data to obtain a positioning result.
9. An RTK-based intelligent outdoor positioning system, comprising: A memory for storing a program; A processor for executing the program to perform the steps of an RTK-based intelligent outdoor positioning method according to any one of claims 1-7.
10. A storage medium having stored thereon computer instructions for causing a computer to perform the method according to any one of claims 1 to 7.

Description

Intelligent outdoor positioning method, device and system based on RTK and storage medium Technical Field The invention relates to the technical field of outdoor positioning, in particular to an intelligent outdoor positioning method, device and system based on RTK and a storage medium. Background The real-time dynamic carrier-phase differential (RTK) technology is a core method for realizing outdoor centimeter-level positioning at present, and is widely applied to the fields of surveying and mapping, automatic driving, unmanned aerial vehicles, precise agriculture and the like. With the application of the RTK technology to the deep complicated scenes such as urban canyons, under overhead bridges, boulevards and the like, the traditional RTK technology faces serious challenges that under the condition of multipath interference such as serious signal shielding, reflection and the like, positioning results are easy to jump, suddenly drop in precision and even lose lock. The existing method mainly depends on carrier phase observation in an ideal environment, lacks collaborative sensing and intelligent processing capability for multisource interference factors in a complex environment, cannot fully utilize built-in inertia of a terminal and environment sensor data to form deep complementation, cannot construct a fusion mechanism for dynamically adjusting the reliability of observation data according to a real-time environment and actively compensating system errors, and causes difficulty in continuously outputting stable and reliable high-precision positioning results under severe outdoor conditions. Disclosure of Invention The invention mainly aims to provide an intelligent outdoor positioning method, device, system and storage medium based on RTK, which can realize the technical crossing of passive receiving active adaptation and remarkably improve the precision and reliability of RTK positioning under a severe outdoor scene. In order to achieve the above object, the present invention provides an intelligent outdoor positioning method based on RTK, including: acquiring a carrier phase observation value, inertial measurement data and environmental data through a positioning terminal; performing anomaly diagnosis and correlation analysis on the carrier phase observation value based on the environmental data to generate dynamic observation weight and phase correction; Performing tight coupling fusion calculation on the inertial measurement data according to the dynamic observation weight and the phase correction amount to obtain fusion data; And carrying out direction constraint and carrier phase fixation on the fusion data according to the environment data to obtain a positioning result. Further, the acquiring, by the positioning terminal, the carrier phase observation value, the inertial measurement data, and the environmental data includes: Acquiring and extracting an original carrier phase signal through a GNSS receiving module of the positioning terminal, and converting the original carrier phase signal into the carrier phase observation value; Acquiring angular velocity readings and acceleration readings in three orthogonal axial directions through an inertial measurement module of the positioning terminal, and integrating the angular velocity readings and the acceleration readings to obtain inertial measurement data; And acquiring the environmental data through an environmental sensor of the positioning terminal. Further, the performing anomaly diagnosis and correlation analysis on the carrier phase observation value based on the environmental data, generating a dynamic observation weight and a phase correction amount, includes: Extracting an environmental characteristic parameter corresponding to the carrier phase observation value from the environmental data; Comparing the carrier phase observed value with a preset phase quality threshold, if the carrier phase observed value exceeds the phase quality threshold, marking the carrier phase observed value as an observed value to be verified, otherwise, judging the carrier phase observed value as a normal observed value; when the observation value to be verified and the environmental characteristic parameter are detected to meet a preset interference condition, judging that the observation value to be verified is an abnormal observation value; performing confidence calculation and weight setting on the observation value to be verified according to the environmental characteristic parameters to obtain the dynamic observation weight; And carrying out deviation recognition on the abnormal observed value based on the preset interference condition, and carrying out phase compensation on the deviation degree data obtained by recognition and the environmental characteristic parameter to obtain the phase correction quantity. Further, the performing close-coupling fusion calculation on the inertial measurement data according to the dynamic observation weight and the