scholarly journals Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering

2016 ◽  
Author(s):  
Wei Shi ◽  
Yang Wang ◽  
Yuanxin Wu
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Inertial Navigation ◽  
Inequality Constraint ◽  
Time Range ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Pedestrian Navigation ◽  
External Assistance ◽  
Constraint Method

The foot-mounted inertial navigation system is an important application of pedestrian navigation as it in principle does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial sensors with ZUPT (zero-velocity update) and range decomposition constraint perform better than in either single way. This paper recommends that the distance of separation between the position estimates of feet-mounted inertial navigation systems be restricted in the ellipsoidal constraint which relates to the maximum step and leg height. The performance of the proposed method is studied utilizing experimental data. The results indicate that the method can effectively correct the dual navigation systems’ position over the existing spherical constraint.

Developments in Inertial Navigation

1986 ◽  
Vol 39 (3) ◽  
pp. 401-415 ◽  
Author(s):  
S. G. Smith
Keyword(s):  
Inertial Navigation ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Automatic Navigation ◽  
Starting Conditions ◽  
External Assistance ◽  
The Ideal

Inertial navigation systems represent the ideal in automatic navigation. They operate entirely without external assistance, other than information as to their starting conditions, which makes them of great interest to both military and civil operators.

scholarly journals Analysis and Verification of Rotation Modulation Effects on Inertial Navigation System based on MEMS Sensors

2013 ◽  
Vol 66 (5) ◽  
pp. 751-772 ◽  
Author(s):  
Xueyun Wang ◽  
Jie Wu ◽  
Tao Xu ◽  
Wei Wang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Inertial Navigation ◽  
Cost Effective ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Mems Sensors ◽  
Micro Electro Mechanical Systems ◽  
Position Accuracy

Inertial Navigation Systems (INS) were large, heavy and expensive until the development of cost-effective inertial sensors constructed with Micro-electro-mechanical systems (MEMS). However, the large errors and poor error repeatability of MEMS sensors make them inadequate for application in many situations even with frequent calibration. To solve this problem, a systematic error auto-compensation method, Rotation Modulation (RM) is introduced and detailed. RM does no damage to autonomy, which is one of the most important characteristics of an INS. In this paper, the RM effects on navigation performance are analysed and different forms of rotation schemes are discussed. A MEMS-based INS with the RM technique applied is developed and specific calibrations related to rotation are investigated. Experiments on the developed system are conducted and results verify that RM can significantly improve navigation performance of MEMS-based INS. The attitude accuracy is improved by a factor of 5, and velocity/position accuracy by a factor of 10.

scholarly journals A Reconstruction Filter for Saturated Accelerometer Signals Due to Insufficient FSR in Foot-mounted Inertial Navigation System

2021 ◽  
Author(s):  
Chi-Shih Jao ◽  
Andrei M. Shkel
Keyword(s):  
Inertial Sensors ◽  
Inertial Navigation ◽  
Gaussian Process Regression ◽  
Navigation Systems ◽  
Analog Device ◽  
Bias Drift ◽  
Pedestrian Navigation ◽  
Angular Velocities ◽  
Reconstruction Filter ◽  
Commercial Off The Shelf

In pedestrian inertial navigation, one possible placement of Inertial Measurement Units (IMUs) is on a footwear. This placement allows to limit the accumulation of navigation errors due to the bias drift of inertial sensors and is generally a preferable placement of sensors to achieve the highest precision of pedestrian inertial navigation. However, inertial sensors mounted on footwear experience significantly higher accelerations and angular velocities during regular pedestrian activities than during more conventional navigation tasks, which could exceed Full Scale Range (FSR) of many commercial-off-the-shelf IMUs, therefore degrading accuracy of pedestrian navigation systems. This paper proposes a reconstruction filter to mitigate localization error in pedestrian navigation due to insufficient FSR of inertial sensors. The proposed reconstruction filter approximates immeasurable accelerometer's signals with a triangular function and estimates the size of the triangles using a Gaussian Process regression. To evaluate performance of the proposed reconstruction filter, we conducted two series of indoor pedestrian navigation experiments with a VectorNav VN-200 IMU and an Analog Device ADIS16497-3 IMU. In the first series of experiments, forces experienced by the IMUs did not exceed the FSRs of the sensors, while in the second series, the forces surpassed the FSR of the VN-200 IMU and saturated the accelerometer's readings. The saturated readings reduced the accuracy of estimated positions using the VN-200 by 1.34× and 3.37× along horizontal and vertical directions. When applying our proposed reconstruction filter to the saturated measurements, the navigation accuracy was increased by 5% horizontally and 50% vertically, as compared to using unreconstructed signals.

Aiding Low Cost Inertial Navigation with Building Heading for Pedestrian Navigation

2011 ◽  
Vol 64 (2) ◽  
pp. 219-233 ◽  
Author(s):  
Khairi Abdulrahim ◽  
Chris Hide ◽  
Terry Moore ◽  
Chris Hill
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensors ◽  
Low Cost ◽  
Inertial Navigation ◽  
Field Trials ◽  
Basic Knowledge ◽  
Effective Solution ◽  
Pedestrian Navigation

In environments where GNSS is unavailable or not useful for positioning, the use of low cost MEMS-based inertial sensors has paved a way to a more cost effective solution. Of particular interest is a foot mounted pedestrian navigation system, where zero velocity updates (ZUPT) are used with the standard strapdown navigation algorithm in a Kalman filter to restrict the error growth of the low cost inertial sensors. However heading drift still remains despite using ZUPT measurements since the heading error is unobservable. External sensors such as magnetometers are normally used to mitigate this problem, but the reliability of such an approach is questionable because of the existence of magnetic disturbances that are often very difficult to predict. Hence there is a need to eliminate the heading drift problem for such a low cost system without relying on external sensors to give a possible stand-alone low cost inertial navigation system. In this paper, a novel and effective algorithm for generating heading measurements from basic knowledge of the orientation of the building in which the pedestrian is walking is proposed to overcome this problem. The effectiveness of this approach is demonstrated through three field trials using only a forward Kalman filter that can work in real-time without any external sensors. This resulted in position accuracy better than 5 m during a 40 minutes walk, about 0·1% in position error of the total distance. Due to its simplistic algorithm, this simple yet very effective solution is appealing for a promising future autonomous low cost inertial navigation system.

scholarly journals Particle-Filter-Based WiFi-Aided Reduced Inertial Sensors Navigation System for Indoor and GPS-Denied Environments

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
M. M. Atia ◽  
M. J. Korenberg ◽  
A. Noureldin
Keyword(s):  
Particle Filter ◽  
Inertial Sensors ◽  
Low Cost ◽  
Indoor Navigation ◽  
Feature Reduction ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Error Accumulation ◽  
Non Gaussian ◽  
Multipath Errors

Indoor navigation is challenging due to unavailability of satellites-based signals indoors. Inertial Navigation Systems (INSs) may be used as standalone navigation indoors. However, INS suffers from growing drifts without bounds due to error accumulation. On the other side, the IEEE 802.11 WLAN (WiFi) is widely adopted which prompted many researchers to use it to provide positioning indoors using fingerprinting. However, due to WiFi signal noise and multipath errors indoors, WiFi positioning is scattered and noisy. To benefit from both WiFi and inertial systems, in this paper, two major techniques are applied. First, a low-cost Reduced Inertial Sensors System (RISS) is integrated with WiFi to smooth the noisy scattered WiFi positioning and reduce RISS drifts. Second, a fast feature reduction technique is applied to fingerprinting to identify the WiFi access points with highest discrepancy power to be used for positioning. The RISS/WiFi system is implemented using a fast version of Mixture Particle Filter for state estimation as nonlinear non-Gaussian filtering algorithm. Real experiments showed that drifts of RISS are greatly reduced and the scattered noisy WiFi positioning is significantly smoothed. The proposed system provides smooth indoor positioning of 1 m accuracy 70% of the time outperforming each system individually.

scholarly journals IMPROVEMENT OF NAVIGATION SYSTEMS OF VEHICLES BY MEANS OF INERTIAL SENSORS AND INFORMATION PROCESSING USING PROBABILITY-GEOMETRIC METHODS

2020 ◽  
Vol 1 (46) ◽  
pp. 353-364
Author(s):  
Topolskov E ◽  
◽  
Beljaevskiy L L ◽  
Serdjuke A ◽  
◽  
...  
Keyword(s):  
Information Processing ◽  
Moving Objects ◽  
Inertial Sensors ◽  
Inertial Navigation ◽  
Satellite Navigation ◽  
Navigation Systems ◽  
Inertial Navigation Systems ◽  
Ground Vehicle ◽  
Geometric Methods ◽  
Urgent Task

Providing high accuracy of the coordinates and trajectories of objects by measurements conducted in navigation systems and complexes is an urgent task, which improves safety and efficiency of different modes of transport. However difficult environmental conditions, where vehicles are commonly used, stipulate influence of different factors on performance of onboard satellite navigation receivers, which are used as basic navigation devices for ground vehicle nowadays. Setting on cars used for common purposes additional navigation devices, which provide better performance, in most cases is economically unreasonable. Economically reasonable ways to improve onboard navigation complexes of vehicles, which are used for common purposes, are examined in this article. Functional diagram and principles of work of navigational complex, which uses the satellite navigation receiver and simplified variant of inertial navigation system is pointed as well. Also, the justification of methods for minimizing the error formats of coordinates and trajectories of moving objects based on information processing in multipositional, in particular satellite-inertial navigation systems and complexes, is presented. The obtained research results give an opportunity to develop an algorithm for coordinate refinement, which can be implemented in the improved on-board navigational complex of vehicle. KEY WORDS: NAVIGATION SYSTEMS AND COMPLEXES, INERTIAL SENSORS, NAVIGATION DEFINITIONS, ACCURACY AND RELIABILITY OF COORDINATES AND TRAJECTORIES OF MOVING OBJECTS, ELLIPS OF ERRORS, PROBABILISTIC-GEOMETRIC METHODS.

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