scholarly journals Pedestrian navigation system based on the inertial measurement unit sensor for outdoor and indoor environments

2020 ◽  
Vol 9 (1) ◽  
pp. 7-13
Author(s):  
Marcin Uradzinski ◽  
Hang Guo
Keyword(s):  
Inertial Measurement Unit ◽  
Angular Rate ◽  
Dead Reckoning ◽  
Step Length ◽  
Position Estimation ◽  
Outdoor Environment ◽  
Measurement Unit ◽  
Indoor Environments ◽  
Inertial Measurement ◽  
Step Detection

Abstract. With the continuous improvement of the hardware level of the inertial measurement unit (IMU), indoor pedestrian dead reckoning (PDR) using an inertial device has been paid more and more attention. Typical PDR system position estimation is based on acceleration obtained from accelerometers to measure the step count, estimate step length and generate the position with the heading received from angular sensors (magnetometers and gyroscopes). Unfortunately, collected signals are very responsive to the alignment of sensor devices, built-in instrumental errors and distortions from the surrounding environment. In our work, a pedestrian positioning method using step detection based on a shoe-mounted inertial unit is arranged and put to the test, and the final results are analyzed. The extended Kalman filter (EKF) provides estimation of the errors which are acquired by the XSENS IMU sensor biases. The EKF is revised with acceleration and angular rate computations by the ZUPT (zero velocity update) and ZARU (zero angular rate update) algorithms. The step detection associated with these two solutions is the perfect choice to calculate the current position and distance walked and to estimate the IMU sensors' collected errors by using EKF. The test with a shoe-mounted IMU device was performed and analyzed in order to check the performance of the recommended method. The combined PDR final results were compared to GPS/Beidou postprocessing kinematic results (outdoor environment) and to a real route which was prepared and calculated for an indoor environment. After the comparison, the results show that the accuracy of the regular-speed walking under ZUPT and ZARU combination in the case of outdoor positioning did not go beyond 0.19 m (SD) and for indoor positioning accuracy did not exceed 0.22 m (SD). The authors are conscious that built-in drift errors coming from accelerometers and gyroscopes, as well as the final position obtained by XSENS IMU, are only stable for a short time period. Based on this consideration, our future work will be focused on supporting the methods presented with radio technologies (WiFi) or image-based solutions to correct all IMU imperfections.

scholarly journals An Implementation of Error Minimization Position Estimate in Wireless Inertial Measurement Unit using Modification ZUPT

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Adytia Darmawan ◽  
Sanggar Dewanto ◽  
Dadet Pramadihanto
Keyword(s):  
Inertial Measurement Unit ◽  
Robot Navigation ◽  
Angular Rate ◽  
Position Estimation ◽  
Experimental Result ◽  
Measurement Unit ◽  
Legged Robot ◽  
Positioning Systems ◽  
Inertial Measurement ◽  
Position Estimate

Position estimation using WIMU (Wireless Inertial Measurement Unit) is one of emerging technology in the field of indoor positioning systems. WIMU can detect movement and does not depend on GPS signals. The position is then estimated using a modified ZUPT (Zero Velocity Update) method that was using Filter Magnitude Acceleration (FMA), Variance Magnitude Acceleration (VMA) and Angular Rate (AR) estimation. Performance of this method was justified on a six-legged robot navigation system. Experimental result shows that the combination of VMA-AR gives the best position estimation.

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

Sensors ◽  
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.

Attitude Determination by Integration of Multi-Sensors Based on Federated Kalman Filter

2014 ◽  
Vol 602-605 ◽  
pp. 2958-2961
Author(s):  
Tao Lai ◽  
Guang Long Wang ◽  
Wen Jie Zhu ◽  
Feng Qi Gao
Keyword(s):  
Kalman Filter ◽  
Inertial Measurement Unit ◽  
Attitude Determination ◽  
Angular Rate ◽  
General Structure ◽  
Test System ◽  
Measurement Unit ◽  
Storage Test ◽  
Inertial Measurement ◽  
Federated Kalman Filter

Micro inertial measurement unit integration storage test system is a typical multi-sensor information fusion system consists of microsensors. The Federated Kalman filter is applied to micro inertial measurement unit integration storage test system. The general structure and characteristics of Federated Kalman filter is expounded. The four-order Runge-Kutta method based on quaternion differential equation was used to dispose the output angular rate data from gyroscope, and the recurrence expressions was established too. The control system based ARM Cortex-M4 master-slave structure is adopted in this paper. The result shown that the dimensionality reduced algorithm significantly reduces implementation complexity of the method and the amount computation. The filtering effect and real-time performance have much increased than traditionally method.

The Automatic Basketball Rebound System

2018 ◽  
Author(s):  
Thomas Smith ◽  
Vidya K. Nandikolla
Keyword(s):  
Inertial Measurement Unit ◽  
High Efficiency ◽  
Dead Reckoning ◽  
Measurement Unit ◽  
System Response ◽  
The Novel ◽  
Rotary Table ◽  
Inertial Measurement ◽  
Correct Orientation ◽  
High Level

In the sport of basketball, it is important to practice shooting the ball to develop the skill of making the shot in the basket at a high efficiency. Making shots at a high efficiency allows the player to succeed at a high level in the sport. The main focus of the paper describes the design and development of an automatic basketball rebound (ABR) system. The developed ABR provides a system that will launch the ball back to the player at any position on the court within a 50-foot radius. This is accomplished by a variable spring loaded launching mechanism that will compress a spring, depending on the players location, to generate the appropriate force required to launch the ball back to the player. The novel launching mechanism developed is mounted to a rotary table that ensures the launching mechanism is in the correct orientation with the player once the ball is launched. The player is outfitted with an inertial measurement unit to track their position using a method known as dead reckoning. This information is relayed back to a microcontroller that determines the system response. The ABR system is made from lightweight materials and is compact such that it is easy to move around compared to its predecessors.

scholarly journals Angular velocity fusion of the microelectromechanical system inertial measurement unit array based on extended Kalman filter with correlated system noises

2020 ◽  
pp. 002029402091770
Author(s):  
Li Xing ◽  
Xiaowei Tu ◽  
Weixing Qian ◽  
Yang Jin ◽  
Pei Qi
Keyword(s):  
Kalman Filter ◽  
Angular Velocity ◽  
Extended Kalman Filter ◽  
Inertial Measurement Unit ◽  
Angular Rate ◽  
The State ◽  
Measurement Unit ◽  
Fusion Method ◽  
Microelectromechanical System ◽  
Inertial Measurement

The paper proposes an angular velocity fusion method of the microelectromechanical system inertial measurement unit array based on the extended Kalman filter with correlated system noises. In the proposed method, an adaptive model of the angular velocity is built according to the motion characteristics of the vehicles and it is regarded as the state equation to estimate the angular velocity. The signal model of gyroscopes and accelerometers in the microelectromechanical system inertial measurement unit array is used as the measurement equation to fuse and estimate the angular velocity. Due to the correlation of the state and measurement noises in the presented fusion model, the traditional extended Kalman filter equations are optimized, so as to accurately and reliably estimate the angular velocity. By simulating angular rates in different motion modes, such as constant and change-in-time angular rates, it is verified that the proposed method can reliably estimate angular rates, even when the angular rate has been out of the microelectromechanical system gyroscope measurement range. And results show that, compared with the traditional angular rate fusion method of microelectromechanical system inertial measurement unit array, it can estimate angular rates more accurately. Moreover, in the kinematic vehicle experiments, the performance advantage of the proposed method is also verified and the angular rate estimation accuracy can be increased by about 1.5 times compared to the traditional method.

scholarly journals A Sporting Chance

2011 ◽  
Vol 133 (07) ◽  
pp. 40-45
Author(s):  
Noel C. Perkins ◽  
Kevin King ◽  
Ryan McGinnis ◽  
Jessandra Hough
Keyword(s):  
Inertial Measurement Unit ◽  
Wireless Sensors ◽  
Microelectromechanical Systems ◽  
Angular Rate ◽  
Rigid Body Dynamics ◽  
The Body ◽  
Measurement Unit ◽  
Golf Club ◽  
Sports Training ◽  
Inertial Measurement

This article discusses using wireless sensors to improve sports training. One example of wireless sensors is inertial sensors that were first developed for automotive and military applications. They are tiny accelerometers and angular rate gyros that can be combined to form a complete inertial measurement unit. An inertial measurement unit (IMU) detects the three-dimensional motion of a body in space by sensing the acceleration of one point on the body as well as the angular velocity of the body. When this small, but rugged device is mounted on or embedded within sports gear, such as the shaft of a golf club, the IMU provides the essential data needed to resolve the motion of that equipment. This technology—and sound use of the theory of rigid body dynamics—is now being developed and commercialized as the ingredients in new sports training systems. It won’t be too long before microelectromechanical systems based hardware and sophisticated software combine to enable athletes at any level to get world-class training.

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