Indoor Ego‐Localization Method for Low Cost Millimeter Wave Radar

Objectives Millimeter wave radar has been widely used in automotive industry and other fields, but its application is mainly limited to the environmental perception of obstacles or specific tasks. At pres‍ent, there is little research on the application of millimeter wave radar in the field of navigation and positioning.

Methods This paper first studies the raw data processing principle of millimeter wave radar, and then designs an indoor ego‐localization method which only depends on a low‐cost millimeter wave radar. The process mainly includes extracting centroid feature points using density based spatial clustering of applications with noise(DBSCAN) algorithm, matching centroid feature point pairs through nearest neighbor criterion, constructing nonlinear optimization function and solving positioning results using levenberg marquardt method.

Results and Conclusions Experiments show that indoor navigation and positioning can be solved in real time by using a low‐cost millimeter wave radar. Under static conditions, the average horizontal positioning accuracy can reach sub centimeter level (mean value is 0.82 cm and standard deviation is 0.47 cm). Under dynamic conditions, the absolute trajectory error can reach 0.66 m and the average head‍ing angle error can reach 4.58°, which shows the feasibility of ego‐localization of low‐cost millimeter wave radar. Finally, this paper discusses the problems and feasible research ideas of low‐cost millimeter wave radar in navigation and positioning.