A method for dead reckoning parameter correction in pedestrian navigation system

In this article, a smart pedestrian navigation system is developed to be implemented in a common smartphone. The main phases that characterize a pedestrian navigation system that is based on dead reckoning are introduced. A suitable Phase-Locked Loop is designed and the algorithm to estimate the direction of the user’s motion between one step and the next is developed. Finally, a suitable multi-rate Kalman filter (KF) is considered to merge the information from the pedestrian dead reckoning (PDR) navigation with the data provided by the global navigation satellite systems (GNSS). The proposed GNSS/PDR navigation system is implemented in Simulink as a finite-state machine and allows to define a trade-off between energy-saving and performance improvement in terms of position accuracy. The presented pedestrian navigation system is independent of the body-worn location of the smartphone and implements a compensation strategy of the systematic errors that are committed on the step-length estimation and the determination of the motion direction. Moreover, several tests are performed by walking in urban and suburban environments: the results show that a suitable trade-off between energy-saving and position accuracy can be reached by switching the GNSS receiver on and off.

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The Standing Calibration Method of MEMS Gyro Bias for Autonomous Pedestrian Navigation System

Journal of Navigation ◽

10.1017/s0373463316000722 ◽

2016 ◽

Vol 70 (3) ◽

pp. 607-617 ◽

Cited By ~ 4

Author(s):

Yanshun Zhang ◽

Xu Yang ◽

Xiangming Xing ◽

Zhanqing Wang ◽

Yunqiang Xiong

Keyword(s):

Navigation System ◽

Angular Rate ◽

Dead Reckoning ◽

Calibration Method ◽

Micro Electro Mechanical System ◽

Human Motion ◽

Pedestrian Navigation ◽

Initial Stage ◽

Angular Velocities ◽

Gyro Bias

In a waist-worn Pedestrian Navigation System (PNS) based on Dead-Reckoning (DR), heading drift caused by Micro-Electro-Mechanical System (MEMS) gyro bias is an essential factor affecting DR accuracy. Considering the characteristics of pedestrian navigation and the poor bias repeatability of MEMS gyros, this paper presents a standing calibration method for MEMS gyro bias. The current gyro biases for each boot can be calibrated accurately in the initial stage before walking. Since the attitude angles calculated by the output data from magnetic sensor and accelerometers do not drift, this paper applies the reverse algorithm of attitude updating to calculate the angular velocities of human motion. Then the gyro biases at each moment can be acquired by subtraction operation between the measured angular velocities from gyros and the calculated angular velocities of human motion. Finally, in order to restrain the random error caused by sensor noise, the calculated biases in the initial stage are smoothed, and consequently the optimal estimate of current gyro biases after each boot can be obtained. Still and dynamic turntable experiments and a walking experiment are performed to compare and analyse the proposed method and the Zero Angular Rate Update (ZARU) method. Experimental results show that the proposed method can also calibrate the gyro bias accurately in the case of body swaying.

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Electronic Compass Calibration in Pedestrian Navigation System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.490-495.1246 ◽

2012 ◽

Vol 490-495 ◽

pp. 1246-1250

Author(s):

Xiao Juan Zhang ◽

Xi Sheng Li ◽

Yi Bo Feng

Keyword(s):

Magnetic Field ◽

Navigation System ◽

Direct Method ◽

Dead Reckoning ◽

Pedestrian Navigation ◽

Movement Characteristic ◽

Calibration Algorithm ◽

Heading Angle ◽

Compass Calibration ◽

Electronic Compass

In this paper, a kind of pedestrian navigation system (PNS) that based on Earth’s magnetic field is introduced, and the error of the build-in electronic compass is analyzed, and an efficient calibration algorithm is presented. The PNS is determined pedestrian’s movement locus by calculating the heading angle and analyzing the movement characteristic, and then using the dead reckoning algorithm to combine the information together. The precision of PNS is affected by the error of the electric compass, because the heading angle is calculated from the magnetic field data measured by the compass. In order to reduce the measure error, a direct method which is used to calibrate the compass, based on ellipsoid fitting, is developed.

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RTK/Pseudolite/LAHDE/IMU-PDR Integrated Pedestrian Navigation System for Urban and Indoor Environments

Sensors ◽

10.3390/s20061791 ◽

2020 ◽

Vol 20 (6) ◽

pp. 1791

Author(s):

Ruihui Zhu ◽

Yunjia Wang ◽

Hongji Cao ◽

Baoguo Yu ◽

Xingli Gan ◽

...

Keyword(s):

Real Time ◽

High Precision ◽

Navigation System ◽

Carrier Phase ◽

Inertial Measurement Unit ◽

Dead Reckoning ◽

Measurement Unit ◽

Indoor Environments ◽

Inertial Measurement ◽

Pedestrian Navigation

This paper presents an evaluation of real-time kinematic (RTK)/Pseudolite/landmarks assistance heuristic drift elimination (LAHDE)/inertial measurement unit-based personal dead reckoning systems (IMU-PDR) integrated pedestrian navigation system for urban and indoor environments. Real-time kinematic (RTK) technique is widely used for high-precision positioning and can provide periodic correction to inertial measurement unit (IMU)-based personal dead reckoning systems (PDR) outdoors. However, indoors, where global positioning system (GPS) signals are not available, RTK fails to achieve high-precision positioning. Pseudolite can provide satellite-like navigation signals for user receivers to achieve positioning in indoor environments. However, there are some problems in pseudolite positioning field, such as complex multipath effect in indoor environments and integer ambiguity of carrier phase. In order to avoid the limitation of these factors, a local search method based on carrier phase difference with the assistance of IMU-PDR is proposed in this paper, which can achieve higher positioning accuracy. Besides, heuristic drift elimination algorithm with the assistance of manmade landmarks (LAHDE) is introduced to eliminate the accumulated error in headings derived by IMU-PDR in indoor corridors. An algorithm verification system was developed to carry out real experiments in a cooperation scene. Results show that, although the proposed pedestrian navigation system has to use human behavior to switch the positioning algorithm according to different scenarios, it is still effective in controlling the IMU-PDR drift error in multiscenarios including outdoor, indoor corridor, and indoor room for different people.

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