Pham et al., 2021 - Google Patents
Walking step length estimation using waist-mounted inertial sensors with known total walking distancePham et al., 2021
View PDF- Document ID
- 17874367800999498082
- Author
- Pham T
- Suh Y
- Publication year
- Publication venue
- IEEE Access
External Links
Snippet
This paper presents a new constrained optimization-based smoothing algorithm for walking step length estimation using waist-mounted inertial sensors, where the total walking distance is known. The walking trajectory is estimated by double integrating acceleration …
- 238000009499 grossing 0 abstract description 49
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
- G01C21/10—Navigation; Navigational instruments not provided for in preceding groups by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in preceding groups by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in preceding groups by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in preceding groups by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
- G01C21/20—Instruments for performing navigational calculations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/78—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using electromagnetic waves other than radio waves
- G01S3/782—Systems for determining direction or deviation from predetermined direction
- G01S3/785—Systems for determining direction or deviation from predetermined direction using adjustment of orientation of directivity characteristics of a detector or detector system to give a desired condition of signal derived from that detector or detector system
- G01S3/786—Systems for determining direction or deviation from predetermined direction using adjustment of orientation of directivity characteristics of a detector or detector system to give a desired condition of signal derived from that detector or detector system the desired condition being maintained automatically, i.e. tracking systems
- G01S3/7864—T.V. type tracking systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/53—Determining attitude
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Klein et al. | StepNet—Deep learning approaches for step length estimation | |
Qiu et al. | Inertial/magnetic sensors based pedestrian dead reckoning by means of multi-sensor fusion | |
Zhang et al. | Inertial sensor based indoor localization and monitoring system for emergency responders | |
Zhao et al. | Pedestrian dead reckoning using pocket-worn smartphone | |
Yu et al. | Comparison of pedestrian tracking methods based on foot-and waist-mounted inertial sensors and handheld smartphones | |
Windau et al. | Walking compass with head-mounted IMU sensor | |
US11162791B2 (en) | Method and system for point of sale ordering | |
Wu et al. | A pedestrian dead-reckoning system for walking and marking time mixed movement using an SHSs scheme and a foot-mounted IMU | |
Pham et al. | Walking step length estimation using waist-mounted inertial sensors with known total walking distance | |
Kong et al. | Hybrid indoor positioning method of BLE and PDR based on adaptive feedback EKF with low BLE deployment density | |
Van Nguyen et al. | Real-time human foot motion localization algorithm with dynamic speed | |
Tjhai et al. | Step-size estimation using fusion of multiple wearable inertial sensors | |
Manos et al. | Walking direction estimation using smartphone sensors: A deep network-based framework | |
Basso et al. | Triggered INS/GNSS data fusion algorithms for enhanced pedestrian navigation system | |
Hasan et al. | Smart phone based sensor fusion by using Madgwick filter for 3D indoor navigation | |
Abadleh et al. | Noise segmentation for step detection and distance estimation using smartphone sensor data | |
Deng et al. | Heading estimation fusing inertial sensors and landmarks for indoor navigation using a smartphone in the pocket | |
Kronenwett et al. | Motion monitoring based on a finite state machine for precise indoor localization | |
Soni et al. | A survey of step length estimation models based on inertial sensors for indoor navigation systems | |
Luo et al. | Learning-based complex motion patterns recognition for pedestrian dead reckoning | |
Hou et al. | HINNet: Inertial navigation with head-mounted sensors using a neural network | |
Han et al. | Stride length estimation based on a single Shank's gyroscope | |
Yuan et al. | A novel ESKF based ZUPT using midpoint integration approach for indoor pedestrian navigation | |
Huang et al. | Novel pedestrian navigation system based on zero velocity update procedure technology and improved Sage‐Husa adaptive Kalman filter with index fading memory factor | |
Terra et al. | Traveled distance estimation algorithm for indoor localization |