CN-121995415-A - Doppler velocity measurement-based self-adaptive RTK positioning method and system

CN121995415ACN 121995415 ACN121995415 ACN 121995415ACN-121995415-A

Abstract

The invention provides a Doppler velocity measurement-based self-adaptive RTK positioning method and system, which comprise the steps of extracting pseudo-range, carrier phase, doppler frequency shift and navigation message of an observation satellite from a baseband chip of a satellite user machine in real time, calculating satellite coordinates at the current moment by utilizing the navigation message, calculating a carrier three-dimensional velocity vector and a carrier velocity scalar based on the Doppler frequency shift in real time, presetting a first velocity judgment threshold value and a second velocity judgment threshold value, judging the motion state of the current carrier, adaptively selecting and configuring corresponding processing strategies and parameters for an RTK positioning filter, executing RTK positioning calculation, outputting a final positioning result and completing the Doppler velocity measurement-based self-adaptive RTK positioning. By applying the technical scheme of the invention, the technical problems that the convergence speed acceleration and the potential of precision improvement caused by the static state cannot be fully utilized in the whole-course dynamic mode positioning in the prior art, and the satellite is unlocked or the positioning result is greatly jumped due to restarting or switching the positioning mode are solved.

Inventors

QIN JIE
HONG SHIPIN
XU ZHENHAO
ZHUANG SHUFENG
Shao Peihan
GAO YAHAO

Assignees

北京自动化控制设备研究所

Dates

Publication Date: 20260508
Application Date: 20251229

Claims (10)

1. The self-adaptive RTK positioning method based on Doppler velocity measurement is characterized by comprising the following steps of: Firstly, extracting pseudo-range, carrier phase, doppler frequency shift and navigation message of an observation satellite from a baseband chip of a satellite user machine in real time, and calculating satellite coordinates at the current moment by utilizing the navigation message; Calculating a carrier three-dimensional speed vector and a carrier speed scalar based on Doppler frequency shift in real time according to the pseudo range, carrier phase, doppler frequency shift and satellite coordinates of the current moment of the observation satellite; Step three, a first speed judgment threshold v thre1 and a second speed judgment threshold v thre2 are preset, a carrier speed scalar is respectively compared with the first speed judgment threshold v thre1 and the second speed judgment threshold v thre2 , and the motion state of the current carrier is judged; step four, according to the judgment result in the step three, adaptively selecting and configuring corresponding processing strategies and parameters for the RTK positioning filter; and fifthly, performing RTK positioning calculation by utilizing the strategy and parameters configured in the step four and the pseudo range and carrier phase of the observed satellite extracted in the step one, outputting a final positioning result, and completing the self-adaptive RTK positioning based on Doppler velocity measurement.
2. The adaptive RTK positioning method based on doppler velocity measurement according to claim 1, wherein in the second step, a carrier three-dimensional velocity vector Can be according to Calculated and obtained, the carrier velocity scalar v u can be based on Calculating and obtaining, wherein s is the number of observation satellites participating in positioning, v is the residual error of an observation equation of each satellite, (l, m, k) is the cosine of the three-dimensional direction of each satellite, c is the speed of light, For satellite user machine speeds, i.e. carrier three-dimensional speed vectors, For the receiver Zhong Piao, the unit is seconds/second, and L is a constant term.
3. The adaptive RTK positioning method based on doppler velocity measurement according to claim 2, wherein the second step further includes performing quality evaluation on the doppler velocity measurement result, including checking satellite geometric distribution, rationality of velocity vector, and residual detection.
4. The adaptive RTK positioning method based on doppler velocity measurement according to claim 3, wherein in the third step, the motion state is decided by the carrier velocity scalar obtained by the calculation in the second step, and the specific decision is outlined as follows:
5. The adaptive RTK positioning method based on doppler velocimetry according to claim 4, wherein in the fourth step, a position prediction process of inter-epoch filtering is: Wherein, the A state transition matrix is represented and is used to represent, A predicted value representing the current epoch carrier position and velocity, x k represents the last epoch carrier position and velocity, Representing the predicted covariance of the current epoch position and velocity, P k represents the covariance of the last epoch position and velocity, Representing process noise.
6. The adaptive RTK positioning method based on Doppler velocity measurement according to claim 5, wherein when the motion state of the carrier is a quasi-stationary state, the method can directly follow the solution result of the last epoch, i.e. the state transition matrix is a unit matrix, the process noise is zero,
7. The adaptive RTK positioning method based on doppler velocity measurement according to claim 5, wherein when the motion state of the carrier is a low-speed state scenario, the carrier position is predicted based on velocity, and the filtering prediction process is as follows: Where τ r ＝t k+1 -t k represents the time interval between two epochs. Q 3×3 represents increased process noise per unit time.
8. The adaptive RTK positioning method based on doppler velocity measurement according to claim 5, wherein when the motion state of the carrier is a conventional dynamic scenario, the position and velocity state of the current epoch are reinitialized by using the result of pseudo-range single-point positioning: Where x spp represents the pseudorange single point location result and Q 3×3,pos and Q 3×3,vel represent the initialization covariance of position and velocity, respectively.
9. An adaptive RTK positioning system based on doppler velocity measurement, wherein the adaptive RTK positioning system based on doppler velocity measurement performs adaptive RTK positioning using the adaptive RTK positioning method based on doppler velocity measurement as claimed in claims 1 to 8.
10. The adaptive RTK positioning system based on doppler velocimetry of claim 9, wherein the adaptive RTK positioning system based on doppler velocimetry comprises: The satellite parameter acquisition module is used for extracting pseudo-range, carrier phase, doppler frequency shift and navigation message of an observation satellite from a baseband chip of the satellite user machine in real time, and calculating satellite coordinates at the current moment by utilizing the navigation message; the carrier speed calculation module is used for calculating a carrier three-dimensional speed vector and a carrier speed scalar based on Doppler frequency shift in real time according to the pseudo range of the observation satellite, the Doppler frequency shift and the satellite coordinates at the current moment; the motion state judgment module is used for presetting a first speed judgment threshold v thre1 and a second speed judgment threshold v thre2 , respectively comparing a carrier speed scalar with the first speed judgment threshold v thre1 and the second speed judgment threshold v thre2 , and judging the motion state of the current carrier; the strategy and parameter configuration module is used for adaptively selecting and configuring corresponding processing strategies and parameters for the RTK positioning filter according to the motion state judgment result of the current carrier; And the RTK positioning module is used for executing RTK positioning calculation by using the configured strategy and parameters, the pseudo range and the carrier phase of the observation satellite, outputting a final positioning result and completing the self-adaptive RTK positioning based on Doppler velocity measurement.

Description

Doppler velocity measurement-based self-adaptive RTK positioning method and system Technical Field The invention relates to the technical field of satellite navigation, in particular to a Doppler velocity measurement-based self-adaptive RTK positioning method and system. Background The real-time dynamic carrier-phase differential technology (RTK) is one of the satellite navigation positioning technologies with the highest current precision, and can provide positioning precision of centimeter level or even millimeter level. In conventional RTK positioning processes, a single, fixed processing strategy is typically employed. Under the condition that the known carrier is static, the position parameters have strict equal constraint relation among epochs, and dynamic models such as speed and the like do not need to be considered, so that faster convergence and higher precision can be realized. When the carrier moves, the position change relation among the epochs needs to be considered, and if necessary, the position parameters even need to be reset. However, the prior art has the obvious defect that in practical application, the motion state of a carrier is dynamically changed. For example, vehicles need to be frequently switched in states of deceleration, parking, running, acceleration and the like, and unmanned aerial vehicles can go through stages of cruising, hovering, maneuvering and the like. In order to ensure the continuity of navigation, the prior art mostly adopts a whole-course dynamic mode for positioning, so that the potential of accelerating the convergence speed and improving the precision caused by the static state cannot be fully utilized when the vehicle stops or the unmanned plane hovers. Restarting the system or switching the positioning mode strongly may cause the satellite to lose lock or the positioning result to jump greatly, which affects the continuity and reliability. Disclosure of Invention The invention provides a Doppler velocity measurement-based self-adaptive RTK positioning method and system, which can solve the technical problems that in the prior art, a full-course dynamic mode is adopted for positioning, so that the potential of accelerating convergence speed and improving precision caused by a static state cannot be fully utilized when a vehicle stops or an unmanned plane hovers, and the satellite unlocking or the positioning result is greatly jumped due to the fact that a positioning mode is restarted or is strongly switched, so that the continuity and reliability are influenced. According to one aspect of the invention, the self-adaptive RTK positioning method based on Doppler velocity measurement comprises the steps of firstly extracting pseudo ranges, carrier phases, doppler frequency shifts and navigation messages of observation satellites from a baseband chip of a satellite user machine in real time, calculating satellite coordinates at the current moment by using the navigation messages, secondly calculating carrier three-dimensional velocity vectors and carrier velocity scalar based on the Doppler frequency shifts in real time according to the pseudo ranges, the carrier phases, the Doppler frequency shifts and the satellite coordinates at the current moment of the observation satellites, thirdly, presetting a first velocity judgment threshold v thre1 and a second velocity judgment threshold v thre2, comparing the carrier velocity scalar with the first velocity judgment threshold v thre1 and the second velocity judgment threshold v thre2 respectively, judging the motion state of the current carrier, fourthly, adaptively selecting and configuring corresponding processing strategies and parameters for an RTK positioning filter according to the judgment results in the third step, and finally outputting the self-adaptive RTK positioning based on the Doppler velocity measurement results by using the strategy and the parameters which are configured in the step IV and the pseudo ranges and the carrier velocity of the observation satellites extracted in the step one. Further, in step two, the carrier three-dimensional velocity vectorCan be according toCalculated, the carrier velocity scalar v u may be based onCalculating and obtaining, wherein s is the number of observation satellites participating in positioning, v is the residual error of an observation equation of each satellite, (l, m, k) is the cosine of the three-dimensional direction of each satellite, c is the speed of light,For satellite user machine speeds, i.e. carrier three-dimensional speed vectors,For the receiver Zhong Piao, the unit is seconds/second, and L is a constant term. Further, the second step further comprises the step of carrying out quality evaluation on Doppler velocity measurement results, including satellite geometric distribution checking, velocity vector rationality checking and residual error detection. Further, in the third step, the motion state is judged by the vector speed scalar obtained t