Accuracy Improvement of Pedestrian Dead-Reckoning Based Map Heading Constraint in GNSS-Denied Environments (original) (raw)
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Map Aided Pedestrian Dead Reckoning Using Buildings Information for Indoor Navigation Applications
Positioning, 2013
Navigation systems play an important role in many vital disciplines. Determining the location of a user relative to its physical environment is an important part of many indoor-based navigation services such as user navigation, enhanced 911 (E911), law enforcement, location-based and marketing services. Indoor navigation applications require a reliable, trustful and continuous navigation solution that overcomes the challenge of Global Navigation Satellite System (GNSS) signal unavailability. To compensate for this issue, other navigation systems such as Inertial Navigation System (INS) are introduced, however, over time there is a significant amount of drift especially in common with low-cost commercial sensors. In this paper, a map aided navigation solution is developed. This research develops an aiding system that utilizes geospatial data to assist the navigation solution by providing virtual boundaries for the navigation trajectories and limits its possibilities only when it is logical to locate the user on a map. The algorithm develops a Pedestrian Dead Reckoning (PDR) based on smart-phone accelerometer and magnetometer sensors to provide the navigation solution. Geospatial model for two indoor environments with a developed map matching algorithm was used to match and project navigation position estimates on the geospatial map. The developed algorithms were field tested in indoor environments and yielded accurate matching results as well as a significant enhancement to positional accuracy. The achieved results demonstrate that the contribution of the developed map aided system enhances the reliability, usability, and accuracy of navigation trajectories in indoor environments.
UCGE Reports Map Aided Indoor and Outdoor Navigation Applications
Navigation systems play an important role in many vital disciplines. Determining the location of a user relative to the physical environment (e.g. roadway, intersections, and services) is an important part of transportation services such as in-vehicle navigation, fleet management and infrastructure maintenance. In addition, other navigation services are required for locating the position of a user in an indoor physical environment (e.g. airports, shopping malls, public buildings, university campus). This indoor-based navigation can assist in several applications such as user navigation, enhanced 911 (E911), law enforcement, location-based and marketing services. Both indoor and outdoor navigation applications require a reliable, trustful and continuous navigation solution that overcomes the challenge of Global Navigation Satellite System (GNSS) signal unavailability. To compensate for this issue, GNSS is now commonly used in tandem with other navigation systems such as Inertial Navigation System (INS). This dual-system integration method provides a solution to GNSS signal outages. However, over time there is a significant amount of drift, characteristic of INS but especially common with low-cost commercial sensors. The effects of drift on INS accuracy highlight the need for additional absolute aiding sensors that can survive for longer periods of time.
Measurement Science and Technology, 2011
This paper introduces a method for the substantial reduction of heading errors in inertial navigation systems used under GPS-denied conditions. Presumably, the method is applicable for both vehicle-based and personal navigation systems, but experiments were performed only with a personal navigation system called 'personal dead reckoning' (PDR). In order to work under GPS-denied conditions, the PDR system uses a foot-mounted inertial measurement unit (IMU). However, gyro drift in this IMU can cause large heading errors after just a few minutes of walking. To reduce these errors, the map-matched heuristic drift elimination (MAPHDE) method was developed, which estimates gyro drift errors by comparing IMU-derived heading to the direction of the nearest street segment in a database of street maps. A heuristic component in this method provides tolerance to short deviations from walking along the street, such as when crossing streets or intersections. MAPHDE keeps heading errors almost at zero, and, as a result, position errors are dramatically reduced. In this paper, MAPHDE was used in a variety of outdoor walks, without any use of GPS. This paper explains the MAPHDE method in detail and presents experimental results.
Dead reckoning methods for pedestrian navigation
2017
The growing size of modern infrastructures and the ubiquitous presence of smartphones has brought into place indoor maps and navigation systems that facilitate indoor navigation for pedestrians. Indoor navigation methods rely on two main research approaches; solutions that depend on radio frequencies and solutions that depend on dead reckoning methods with sensors installed on the pedestrian to be tracked. Dead reckoning methods are useful to extend navigation into areas where other navigation systems are unavailable or to improve the accuracy of the existing navigation methods. With the increased offerings of sensors in smartphones several pedestrian dead reckoning (PDR) methods based on Inertial Measurement Units (IMUs) have been proposed, these methods have practical limitations restricting them to be applied in all scenarios. Thus, there is a need to explore this area and develop methods that can be used in all practical scenarios. PDR based on hand-held IMUs in devices like sma...
A Real-Time GNSS/PDR Navigation System for Mobile Devices
Remote. Sens., 2021
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...
Data Integration from GPS and Inertial Navigation Systems for Pedestrians in Urban Area
TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, 2013
The GPS system is widely used in navigation and the GPS receiver can offer long-term stable absolute positioning information. The overall system performance depends largely on the signal environments. The position obtained from GPS is often degraded due to obstruction and multipath effect caused by buildings, city infrastructure and vegetation, whereas, the current performance achieved by inertial navigation systems (INS) is still relatively poor due to the large inertial sensor errors. The complementary features of GPS and INS are the main reasons why integrated GPS/INS systems are becoming increasingly popular. GPS/INS systems offer a high data rate, high accuracy position and orientation that can work in all environments, particularly those where satellite availability is restricted. In the paper integration algorithm of GPS and INS systems data for pedestrians in urban area is presented. For data integration an Extended Kalman Filter (EKF) algorithm is proposed. Complementary characteristics of GPS and INS with EKF can overcome the problem of huge INS drifts, GPS outages, dense multipath effect and other individual problems associated with these sensors. http://www.transnav.eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 7 Number 3
ISPRS International Journal of Geo-Information
Smartphones have become indispensable in our daily lives. Their various embedded sensors have inspired innovations in mobile applications-especially for indoor navigation. However, the accuracy, reliability and generalizability of navigation all continue to struggle in environments lacking a Global Navigation Satellite System (GNSS). Pedestrian Dead Reckoning (PDR) is a popular method for indoor pedestrian navigation. Unfortunately, due to its fundamental principles, even a small navigation error will amplify itself, step by step, generally leading to the need for supplementary resources to maintain navigation accuracy. Virtually all mobile devices and most robots contain a basic camera sensor, which has led to the popularity of image-based localization, and vice versa. However, all of the image-based localization requires continuous images for uninterrupted positioning. Furthermore, the solutions provided by either image-based localization or a PDR are usually in a relative coordinate system. Therefore, this research proposes a system, which uses space resection-aided PDR with geo-referenced images of a previously mapped environment to enable seamless navigation and solve the shortcomings of PDR and image-based localization, and evaluates the performance of space resection with different assumptions using a smartphone. The indoor mobile mapping system (IMMS) is used for the effective production of geo-referenced images. The preliminary results indicate that the proposed algorithm is suitable for universal pedestrian indoor navigation, achieving the accuracy required for commercial applications.
Design of a Wireless Assisted Pedestrian Dead Reckoning System—The NavMote Experience
IEEE Transactions on Instrumentation and Measurement, 2005
In this paper, we combine inertial sensing and sensor network technology to create a pedestrian dead reckoning system. The core of the system is a lightweight sensor-and-wireless-embedded device called NavMote that is carried by a pedestrian. The NavMote gathers information about pedestrian motion from an integrated magnetic compass and accelerometers. When the Nav-Mote comes within range of a sensor network (composed of Net-Motes), it downloads the compressed data to the network. The network relays the data via a RelayMote to an information center where the data are processed into an estimate of the pedestrian trajectory based on a dead reckoning algorithm. System details including the NavMote hardware/software, sensor network middleware services, and the dead reckoning algorithm are provided. In particular, simple but effective step detection and step length estimation methods are implemented in order to reduce computation, memory, and communication requirements on the Motes. Static and dynamic calibrations of the compass data are crucial to compensate the heading errors. The dead reckoning performance is further enhanced by wireless telemetry and map matching. Extensive testing results show that satisfactory tracking performance with relatively long operational time is achieved. The paper also serves as a brief survey on pedestrian navigation systems, sensors, and techniques.