Collaborative navigation as a solution for PNT applications in GNSS challenged environments: report on field trials of a joint FIG / IAG working group

PNT stands for Positioning, Navigation, and Timing. Space-based PNT refers to the capabilities enabled by GNSS, and enhanced by Ground and Space-based Augmentation Systems (GBAS and SBAS), which provide position, velocity, and timing information to an unlimited number of users around the world, allowing every user to operate in the same reference system and timing standard. Such information has become increasingly critical to the security, safety, prosperity, and overall qualityof-life of many citizens. As a result, space-based PNT is now widely recognized as an essential element of the global information infrastructure. This paper discusses the importance of the availability and continuity of PNT information, whose application, scope and significance have exploded in the past 10–15 years. A paradigm shift in the navigation solution has been observed in recent years. It has been manifested by an evolution from traditional single sensor-based solutions, to multiple sensor-based solutions and ultimately to collaborative navigation and layered sensing, using non-traditional sensors and techniques – so called signals of opportunity. A joint working group under the auspices of the International Federation of Surveyors (FIG) and the International Association of Geodesy (IAG), entitled ‘Ubiquitous Positioning Systems’ investigated the use of Collaborative Positioning (CP) through several field trials over the past four years. In this paper, the concept of CP is discussed in detail and selected results of these experiments are presented. It is demonstrated here, that CP is a viable solution if a ‘network’ or ‘neighbourhood’ of users is to be positioned / navigated together, as it increases the accuracy, integrity, availability, and continuity of the PNT information for all users

Performance evaluation of MEMS based INS/GPS integration

© 2010 Azmir Hasnur RabiainContinuous positioning and attitude determination are of great interest in many applications such as location based services (LBS) and vehicle navigation systems. Global Navigation Satellite System (GNSS) is the most widely employed technique where it could provide global positioning solutions, at any given time of day and weather. However, its use is limited particularly in urban canyon environments due to its signals being obstructed by buildings and thick foliages. Therefore, it is often integrated with other positioning systems to overcome the problem. The most common system integrated with GNSS is the Inertial Navigation Systems (INS). However, conventional INS are not practically suitable to be used in most land based or commercial applications primarily due to its cost and size. With the advent of technology, it is possible to mass produce Micro-Electronic- Mechanical-System (MEMS) INS, which is relatively inexpensive and smaller than conventional INS. When integrated with GNSS using the Extended Kalman Filter (EKF) algorithm, it can create a more robust navigation system. This in turn makes it a more practical system to be employed in applications such as LBS. However, MEMS INS/GNSS performance is relatively poor compared to conventional INS/GNSS due to its fabrication process and noisy sensors. Therefore, more research is needed to in- vestigate its capability for applications which require continuous positioning solutions. This research aims to evaluate the performance of INS/GNSS integration. This is achieved by comparing the capabilities of two INS/GNSS integration architectures, namely loosely (LC) and tightly coupled (TC), and through the testing of six MEMS based INS. Firstly, a static test was conducted to obtain INS stochastic coecients using Allan Variance (AV) and Power Spectral Density (PSD) analyses. The results from the analyses allow for a performance comparison of the six INS. Secondly, two independent kinematic tests were conducted to evaluate INS performances when integrated with GPS, using both LC and TC integration architectures. GPS outages were simulated to further investigate the capability of INS/GPS to bridge positioning solution when GPS measurements are unavailable. The result of the research showed that the accuracy of integrated INS/GPS using LC integration architecture was comparative to GPS-Single Point Positioning (SPP) solution whereas, considerable improvements were observed when TC integration architecture was employed. Similar trends were observed during simulated GPS outages, where INS/GPS positional errors were signicantly decreased when using TC compared to LC. Ultimately, the positional growth is dependent on the INS grade, where the results showed that higher grade INS outperformed lower grade INS particularly during simulated GPS outages

Hybrid CFO-RSS Cooperative Positioning for Environments with Limited GNSS Visibility

Abstract — Cooperative Positioning (CP) techniques are used to enhance the performance of positioning through sharing position-related data among a number of agents. These agents are usually users with mobility and, possibly, the infrastructure node(s). In CP systems, position-related data are shared among the participating nodes using a communication medium. Internode distance is a common parameter considered in CP techniques, especially for those in the environments with limited Global Navigation Satellite System (GNSS) visibility including dense urban areas and indoor environments. Radio ranging based on Received Signal Strength (RSS) is popular among researchers for its simplicity. However, the accuracy of this method is far beyond the requirements of CP systems. Here, we introduce Carrier Frequency Offset (CFO) as a potential observable to improve RSS ranging. Regardless of the content of the data communicated among the agents, RSS and CFO always exist in the communication signal. Therefore, the results of this work can be applied to improve the performance of any other CP method. Here, a hybrid CFO-RSS ranging method is presented to improve the accuracy of RSS ranging. The experimental results show up to 80 % accuracy improvement over RSS using the proposed hybrid CFO-RSS technique. Although the examples used here are for outdoor situations, the outcomes are directly applicable indoors or any situation where GNSS signals are not available

Collaborative navigation with ground vehicles and personal navigators

2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Conference Proceedings 2012, Article number 6418893An integrated positioning solution termed 'collaborative positioning' employs multiple location sensors with different accuracy on different platforms for sharing of their absolute and relative localizations. Typical application scenarios are dismounted soldiers, swarms of UAV's, team of robots, emergency crews and first responders. The stakeholders of the solution (i.e., mobile sensors, users, fixed stations and external databases) are involved in an iterative algorithm to estimate or improve the accuracy of each node's position based on statistical models. This paper studies the challenges to realize a public and low-cost solution, based on mass users of multiple-sensor platforms. For the investigation field experiments revolved around the concept of collaborative navigation, and partially indoor navigation. For this purpose different sensor platforms have been fitted with similar type of sensors, such as geodetic and low-cost high-sensitivity GNSS receivers, tactical grade IMU's, MEMS-based IMU's, miscellaneous sensors, including magnetometers, barometric pressure and step sensors, as well as image sensors, such as digital cameras and Flash LiDAR, and ultra-wide band (UWB) receivers. The employed platforms in the tests include a train on a building roof, mobile mapping vans, a personal navigator and a foot tracker unit. In terms of the tests, the data from the different platforms are recorded simultaneously. Several field experiments conducted in a week at the University of Nottingham are described and investigated in the paper. The personal navigator and a foot tracker unit moved on the building roof, then trough the building down to where it logged data simultaneously with the vans, all of them moving together and relative to each other. The platforms then logged data simultaneously covering various accelerations, dynamics, etc. over longer trajectories. Promising preliminary results of the field experiments showed that a positioning accuracy on the few meter level can be achieved for the navigation of the different platforms. © 2012 IEEE

Collaborative navigation field trials with different sensor platforms

2013 10th Workshop on Positioning, Navigation and Communication, WPNC 2013 - Proceedings 2013, Article number 6533262Collaborative (or cooperative) positioning or navigation uses multiple location sensors with different accuracy on different platforms for sharing of their absolute and relative localizations. Typical application scenarios are dismounted soldiers, swarms of UAV's, team of robots, emergency crews and first responders. This paper studies the challenges to realize a public and low-cost solution, based on mass users of multiple-sensor platforms. For the investigation field experiments revolved around the concept of collaborative navigation in a week at the University of Nottingham in May 2012. Different sensor platforms have been fitted with similar type of sensors, such as geodetic and low-cost high-sensitivity GNSS receivers, tactical grade IMU's, MEMS-based IMU's, miscellaneous sensors, including magnetometers, barometric pressure and step sensors, as well as image sensors, such as digital cameras and Flash LiDAR, and ultra-wide band (UWB) receivers. The employed platforms in the tests include a train on a building roof, mobile mapping vans and personal navigators. The presented preliminary results of the field experiments show that a positioning accuracy on the few meter level can be achieved for the navigation of the different platforms. © 2013 IEEE