Positioning data processing method and apparatus, device, and storage medium

A computer device, comprising a processor and a memory, the memory having a program code stored therein, and the program code, when executed by the processor, causing the computer device to perform a positioning data processing method including:

• acquiring a plurality of sets of original observation data from a plurality of intelligent terminals, each set of original observation data comprising navigation positioning information generated when the intelligent terminal performs positioning and a signal-noise ratio;
• mapping the navigation positioning information in each set of original observation data to a respective index;
• for each index, removing, from at least two sets of original observation data associated with the index, abnormal data whose signal-noise ratios are greater than a first set threshold, to obtain an observation data subset;
• obtaining statistical features of the signal-noise ratios in the observation data subset based on an occurrence count of each signal-noise ratio in the observation data subset;
• and
• adjusting at least one model parameter one a pre-constructed stochastic model by using the observation data subset and the statistical features, the at least one model parameter being used for configuring a preset type of stochastic model for positioning in the intelligent terminal.

A non-transitory computer-readable storage medium, storing a program code therein, and the program code, when executed by a processor of a computer device, causing the computer device to perform a positioning data processing method including:

• acquiring a plurality of sets of original observation data from a plurality of intelligent terminals, each set of original observation data comprising navigation positioning information generated when the intelligent terminal performs positioning and a signal-noise ratio;
• mapping the navigation positioning information in each set of original observation data to a respective index;
• for each index, removing, from at least two sets of original observation data associated with the index, abnormal data whose signal-noise ratios are greater than a first set threshold, to obtain an observation data subset;
• obtaining statistical features of the signal-noise ratios in the observation data subset based on an occurrence count of each signal-noise ratio in the observation data subset;
• and
• adjusting at least one model parameter one a pre-constructed stochastic model by using the observation data subset and the statistical features, the at least one model parameter being used for configuring a preset type of stochastic model for positioning in the intelligent terminal.