Method and apparatus for obtaining emission probability, method and apparatus for obtaining transition probability, and sequence positioning method and apparatus

Patent metadata

Field	Value
Publication number	US-12047902-B2
Application number	US-202217688087-A
Country	US
Kind code	B2
Filing date	Mar 7, 2022
Priority date	Aug 15, 2017
Publication date	Jul 23, 2024
Grant date	Jul 23, 2024

Abstract

A method for obtaining an emission probability includes obtaining a plurality of measurement reports (MRs) of a terminal in a target region and an engineering parameter of at least one base station in the target region, obtaining, based on parameter information in each of the plurality of MRs and the engineering parameter of the at least one base station, a feature vector corresponding to each of the plurality of MRs, processing, using a regression model, location information in each of the plurality of MRs and the feature vector corresponding to each of the plurality of MRs, to obtain a single-point positioning model, calculating, based on the single-point positioning model, the location information in each of the plurality of MRs, and the feature vector corresponding to each of the plurality of MRs, an emission probability of the feature vector corresponding to each of the plurality of MRs.

First claim

What is claimed is:

1. A method, comprising:
obtaining pieces of track data of terminals in a target region from a third-party platform, wherein the target region is a predetermined geographical region, wherein the pieces of track data comprise a same environment parameter, wherein the same environment parameter indicates an environment in which a first terminal in the terminals corresponding to track data comprising the same environment parameter is located, wherein each of the pieces of track data comprises at least two pieces of location information, wherein the at least two pieces of location information indicate a first location that is in the target region and that is of a second terminal in the terminals corresponding to track data comprising first location information, and wherein each piece of location information in the at least two pieces of location information corresponds to a time stamp; and
calculating a transition probability based on the pieces of track data,
wherein the transition probability comprises at least one transition probability value, and
wherein the at least one transition probability value indicates a probability that movement from a first piece of location information to a second piece of location information occurs after a time interval T.

2. The method of claim 1 , wherein calculating the transition probability comprises:
processing the pieces of track data to obtain at least one combination sequence of each of the pieces of track data, wherein the at least one combination sequence comprises any two pieces of location information in one piece of track data and a first time interval between the any two pieces of location information; and
obtaining, based on a first preset condition and the at least one combination sequence, a first transition probability corresponding to the first preset condition, wherein the first preset condition is any one of a plurality of preset conditions, wherein each preset condition in the plurality of preset conditions comprises a preset time interval and preset location information, wherein the preset time interval corresponds to the time interval T, and wherein the preset location information corresponds to a piece of location information.

3. The method of claim 2 , wherein obtaining the first transition probability corresponding to the first preset condition comprises:
obtaining first combination sequences that comprise the preset time interval and the preset location information in the first preset condition and that are in all combination sequences in the pieces of track data;
collecting statistics about the first combination sequences; and
calculating the first transition probability corresponding to the first preset condition.

4. The method of claim 1 , wherein before calculating the transition probability, the method further comprises removing defective track data from the pieces of track data, and wherein the defective track data is one of first track data in which at least one piece of location information deviates from a road in the target region by a first distance greater than a first threshold or second track data in which a second distance between two pieces of adjacent location information is greater than a second threshold.

5. The method of claim 1 , wherein before calculating the transition probability, the method further comprises:
obtaining sparse track data in the pieces of track data, wherein the sparse track data is track data in which a distance between any two pieces of adjacent location information is greater than a third threshold; and
inserting one or more pieces of location information between the any two pieces of adjacent location information in the sparse track data based on map information of the target region.

6. The method of claim 1 , wherein obtaining the pieces of track data comprises obtaining the pieces of track data in a peak traffic time period or a non-peak traffic time period.

7. The method of claim 1 , wherein the environment parameter comprises at least one of time period information, weather information, or event information.

8. The method of claim 2 , wherein the preset time interval is a preset time interval range.

9. An apparatus, comprising:
a memory configured to store a programmable instruction; and
a processor coupled to the memory and configured to execute the programmable instruction to:
obtain pieces of track data of terminals in a target region from a third-party platform, wherein the target region is a predetermined geographical region, wherein the pieces of track data comprise a same environment parameter, wherein the same environment parameter indicates an environment in which a first terminal in the terminals corresponding to track data comprising the same environment parameter is located, wherein each of the pieces of track data comprises at least two pieces of location information, wherein the at least two pieces of location information indicate a first location that is in the target region and that is of a second terminal in the terminals corresponding to track data comprising first location information, and wherein each piece of location information in the at least two pieces of location information corresponds to a time stamp; and
calculate a transition probability based on the pieces of track data,
wherein the transition probability comprises at least one transition probability value, and
wherein the at least one transition probability value indicates a probability that movement from a first piece of location information to a second piece of location information occurs after a time interval T.

10. The apparatus of claim 9 , wherein the processor is configured to execute the programmable instruction to calculate the transition probability by:
processing the pieces of track data to obtain at least one combination sequence of each of the pieces of track data, wherein the at least one combination sequence comprises any two pieces of location information in one piece of track data and a first time interval between the any two pieces of location information; and
obtaining, based on a first preset condition and the at least one combination sequence, a first transition probability corresponding to the first preset condition.

11. The apparatus of claim 10 , wherein the first preset condition is any one of a plurality of preset conditions, and wherein each preset condition in the plurality of preset conditions comprises a preset time interval and preset location information.

12. The apparatus of claim 11 , wherein the preset time interval corresponds to the time interval T, and wherein the preset location information corresponds to a piece of location information.

13. The apparatus of claim 12 , wherein the processor is configured to execute the programmable instruction to obtain the transition probability corresponding to the first preset condition by:
obtaining first combination sequences that comprise the preset time interval and the preset location information in the first preset condition and that are in all combination sequences in the pieces of track data;
collecting statistics about the first combination sequences; and
calculating the transition probability corresponding to the first preset condition.

14. The apparatus of claim 9 , wherein before calculating the transition probability, the processor is configured to execute the programmable instruction to remove defective track data from the pieces of track data, and wherein the defective track data is one of first track data in which at least one piece of location information deviates from a road in the target region by a first distance great

Assignees

• Huawei Tech Co Ltd

Inventors

• Zhu Fangzhou
• Yuan Mingxuan
• Zeng Jia
• Rao Weixiong

Classifications

• H04W72/0446

  Resources in time domain, e.g. slots or frames · CPC title

• H04W24/10

  Scheduling measurement reports {; Arrangements for measurement reports} · CPC title

• G06N20/00

  Machine learning · CPC title

• H04W76/11

  Allocation or use of connection identifiers · CPC title

• H04W4/023

  using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds · CPC title