Bayesian algorithms for mobile terminal positioning in outdoor wireless environments

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Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

A Study of Environment Noise in Ultra-Wideband Indoor Position Tracking

This work is motivated by the problem of improving the accuracy of indoor ultra-wideband (UWB) position tracking through the study of the environment noise that affects such a system. Current systems can provide accuracy in the range of 30-100 cm in a small building, suitable for applications that require rough room-level precision such as asset tracking and surveillance. Our long-term goal is to improve the accuracy to 1 cm or better, expanding potential applications to telepresence, augmented reality, training and entertainment. This work investigates the possibility of systematically observing the measurement noise of an UWB position tracking system and building a map of it throughout a facility. In order to understand the effect of environment noise on UWB indoor positioning and in turn filter out the effects of this noise, it is important to have an idea of what this measurement noise looks like in a real world scenario. In this work, an understanding of the measurement noise is gained by taking many measurements using a commercially-available UWB positioning system installed in a real world scenario and analyzing these measurements in various ways. To the author\u27s knowledge, no one has used such an exhaustive approach to analyze measurement noise in UWB indoor positioning. The results of this work show that the measurement noise that affects a UWB indoor position tracking system can be effectively modeled using a weighted sum of Gaussians, is stable over time and is locally similar. Furthermore, a particle filter augmented with a measurement noise map is proposed to improve position tracking accuracy. Finally, a metric is proposed that can be used to quantify expected system performance based on sensor location, sensor orientation and facility floorplan. Using this metric, a procedure is developed to determine the parameters, i.e. sensor position, sensor orientation and potentially others, of the physical installation of the UWB tracking system that will produce minimum measurement error based on sensor geometry and physical facility constraints

Indoor Geo-location And Tracking Of Mobile Autonomous Robot

The field of robotics has always been one of fascination right from the day of Terminator. Even though we still do not have robots that can actually replicate human action and intelligence, progress is being made in the right direction. Robotic applications range from defense to civilian, in public safety and fire fighting. With the increase in urban-warfare robot tracking inside buildings and in cities form a very important application. The numerous applications range from munitions tracking to replacing soldiers for reconnaissance information. Fire fighters use robots for survey of the affected area. Tracking robots has been limited to the local area under consideration. Decision making is inhibited due to limited local knowledge and approximations have to be made. An effective decision making would involve tracking the robot in earth co-ordinates such as latitude and longitude. GPS signal provides us sufficient and reliable data for such decision making. The main drawback of using GPS is that it is unavailable indoors and also there is signal attenuation outdoors. Indoor geolocation forms the basis of tracking robots inside buildings and other places where GPS signals are unavailable. Indoor geolocation has traditionally been the field of wireless networks using techniques such as low frequency RF signals and ultra-wideband antennas. In this thesis we propose a novel method for achieving geolocation and enable tracking. Geolocation and tracking are achieved by a combination of Gyroscope and encoders together referred to as the Inertial Navigation System (INS). Gyroscopes have been widely used in aerospace applications for stabilizing aircrafts. In our case we use gyroscope as means of determining the heading of the robot. Further, commands can be sent to the robot when it is off balance or off-track. Sensors are inherently error prone; hence the process of geolocation is complicated and limited by the imperfect mathematical modeling of input noise. We make use of Kalman Filter for processing erroneous sensor data, as it provides us a robust and stable algorithm. The error characteristics of the sensors are input to the Kalman Filter and filtered data is obtained. We have performed a large set of experiments, both indoors and outdoors to test the reliability of the system. In outdoors we have used the GPS signal to aid the INS measurements. When indoors we utilize the last known position and extrapolate to obtain the GPS co-ordinates

A NAVIGATION AND AUTOMATIC COLLISION AVOIDANCE SYSTEM FOR MARINE VEHICLES

Collisions and groundings at sea still occur, and can result in financial loss, loss of life, and damage to the environment. Due to the size and capacity of moden vessels, damage can be extensive. Statistics indicate that the primary cause of accidents at sea is human error, which is often attributed to misinterpretation of the information presented to the mariner. Until recently, data collected from sensors about the vessel were displayed on the bridge individually, leaving the mariner to assimilate the material, make decisions and alter the vessels controls as appropriate. With the advent of the microprocessor a small amount of integration has taken place, but not to the extent that it has in other industries, for example the aerospace industry. This thesis presents a practical method of integrating all the navigation sensors. Through the use of Kalman filtering, an estimate of the state of the vessel is obtained using all the data available. Previous research in this field has not been implemented due to the complexity of the ship modelling process required, this is overcome by incorporating a system identification proceedure into the filter. The system further reduces the demands on the mariner by applying optimal control theory to guide the vessel on a predetermined track. Hazards such as other vessels are not incorporated into this work but they are specified in further research. Further development work is also required to reduce computation time.J&S Marine Ltd

Stochastic filtering technique for UAV-based communications on the move terminal tracking accuracy evaluation

Along with the growth of communication and satellite industry, the importance of satellite antenna evaluation is increasing. Particularly Communication On The Move (COTM) terminal antenna, including the communication between new types of constellations on LEO and MEO, requires tracking accuracy test for the communication on moving vehicles. The conventional test facilities are locally fixed and lack flexibility. To make the antenna measurement more accessible, we are developing a methodology for in-situ measurement by introducing multiple Unmanned-Aerial-Vehicles (UAVs) system with RF payload. Thanks to the dynamic flexibility of UAVs, this system can flexibly change the test configuration on site and make new test scenarios available, such as emulating the orbit of non-GEO satellites during the measurement. However, one of the challenges of the proposed system is the additional uncertainties during the measurement due to the mobility of UAVs. To overcome this challenge, we design recursive stochastic filtering and fusion approaches, and evaluate their estimation performance via numerical simulations. By introducing stochastic filter and fusion algorithms, the effect of error is mitigated, and better accuracy can be achieved compared to an existing method. This project is performed in collaboration with Cranfield University in the UK and QuadSAT in Denmark