Research On GNSS/INS Combined Positioning Method Based On Smartphone

In recent years,with the increasing demand for location-based services,as the most widely used smart devices in daily life,location-based services based on smartphones have attracted more and more attention.At present,the use of smartphone-based GNSS chips for positioning can meet the daily positioning needs of pedestrians in open environments,but when blocked by buildings or shade,the satellite signal loss is serious,especially for indoor scenes.Based on this fact,this paper proposes a combined GNSS/PDR positioning optimization method for pedestrian positioning,and intends to achieve precise positioning in complex scenes by combining the two.The specific work of this paper includes:1.A combined GNSS/PDR positioning optimization method is proposed.First,the pedestrian’s position change is obtained through GNSS Doppler speed measurement,and then it is inferred whether the heading angle error is within an acceptable range according to the current speed.Through the obtained position change and heading angle,the Kalman filter is used.The algorithm calculates the PDR step error and heading error,and then performs error correction to obtain the final result of pedestrian positioning.2.This paper proposes a method for recognizing special gaits(side shifts,back-ups).First,use the data collected by the inertial and magnetic sensors of the smartphone to fuse to calculate the attitude of the mobile phone,and obtain the attitude matrix of the mobile phone.Then use the attitude matrix to convert the acceleration data from the carrier coordinate system to the navigation coordinate system,and judge whether the pedestrian’s current action is a special gait according to the direction of the three axes of the acceleration data and the change of the heading angle,so as to avoid the special gait.Occurrence of PDR false detection.3.The standard single point positioning algorithm has been improved.Firstly,data preprocessing is performed on the original observation data,and the bad observation data is eliminated,and then the Doppler velocimetry is used to obtain a higher-precision position change.The Puller observations smoothed the localization results in the location domain.4.Improve the influence of the errors of each link in the PDR process on the positioning results.Firstly,step detection is performed using a combination of peak-valley time thresholds as a way to reduce the effect of pseudo-peaks in acceleration data on step detection.Secondly,the mixed step size estimation model is used to complete the estimation of pedestrian step size,which increases the robustness of the step size estimation model compared with the single model.Finally,the improved complementary filtering method is used to reduce the influence of the accumulated drift error on the attitude calculation accuracy.Finally,a PDR indoor positioning experiment is designed to verify that the improved method has higher positioning accuracy than the traditional PDR positioning method.Furthermore,we design a combined positioning experiment,which verifies that the GNSS/PDR combined positioning method proposed in this paper has high positioning accuracy and that the horizontal error is within the range of 1 to 3 meters,which meets the basic positioning needs of pedestrians on a daily basis.