Radar positioning method and device, storage medium and terminal

Abstract

The invention provides a radar positioning method and device, a storage medium and a terminal, and the method is applied to a mobile device, and comprises the steps: constructing an approximate nearest domain field based on an architectural plan of an environment; generating a fitting plane based on the first point cloud data of the environment; calculating an optimal solution of a first group of pose estimation values of the mobile device based on the fitting plane, wherein the optimal solution comprises a first coordinate axis change value, a roll angle change value and a pitch angle change value; filtering the first point cloud data to obtain second point cloud data; extracting line features and surface features of the second point cloud data based on the second point cloud data; and matching the line features and the surface features with the approximate nearest domain field to obtain a second group of pose estimation values of the mobile equipment, wherein the second group of pose estimation values comprises a second coordinate axis change value, a third coordinate axis change value and a yaw angle change value. According to the invention, the calculation amount and the power consumption can be obviously reduced under the condition of ensuring the positioning precision; the system can be widely applied to the fields of scientific research, entertainment service, building construction, logistics management and the like.

Description

technical field [0001] The invention relates to the fields of computer vision and machine perception, in particular to a radar positioning method, device, storage medium and terminal. Background technique [0002] For the Absolute Indoor Localization problem (Absolute Indoor Localization), some solutions in the prior art rely on one or more passive wireless communication sensors to assist positioning, and detect the target position by receiving electromagnetic waves radiated or reflected by the target. For example, radio frequency identifiers, Wi-Fi, Bluetooth beacons, ultrasonic beacons, etc., have relatively large limitations and require professionals to enter the site in advance to arrange and debug, which is time-consuming, laborious and expensive, and the service life of the hardware is limited; another part of the solution uses The known map is used to assist positioning. The core algorithm is based on Monte Carlo Localization, Stochastic Gradient Descent or Voronoi Se...

AI Technical Summary

Problems solved by technology

[0002] For the Absolute Indoor Localization problem (Absolute Indoor Localization), some solutions in the prior art rely on one or more passive wireless communication sensors to assist positioning, and detect the target position by receiving electromagnetic waves radiated or reflected by the target. For example, radio frequency identifiers, Wi-Fi, Bluetooth beacons, ultrasonic beacons, etc., have relatively large limitations and require professionals to enter the site in advance to arrange and debug, which is time-consuming, laborious and expensive, and the service life of the hardware is limited; another part of the solution uses The known map is used to assist positioning. The core algorithm is based on Monte Carlo Localization, Stochastic Gradient Descent or Voronoi Segmentation. However, since the map needs to be discrete in such methods In order to achieve a certain accuracy, a large amount of information needs to be stored, which inevitably has the disadvantage of large storage space requirements, and a large amount of data needs to be processed when performing positioning tasks, which not only consumes computing resources, but also affects the real-time performance of positioning.

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