Enhancing the Performance of Propagation Model-Based Positioning Algorithms

Object localization in wireless networks through Received Signal Strength (RSS) measurements requires a precise estimation of the signal attenuation model in order to produce meaningful results. The popular lognormal channel model, widely adopted to describe the signal strength attenuation as a function of the distance between nodes, turns out to be too simplistic when applied to a real scenario. In this paper, we analyze two possible improvements to this model: on one hand, we build a different channel model for each reference node in the network, with the aim of tackling the anisotropy of the environment. On the other hand, we explicitly append to the lognormal model a term to account for walls attenuation. A thorough experimental testbed demonstrates the potentials of the two approaches, with the second one being especially useful to counteract the effect of the limited sensitivity of practical wireless receivers

Making Transport Safer: V2V-Based Automated Emergency Braking System

An important goal in the field of intelligent transportation systems (ITS) is to provide driving aids aimed at preventing accidents and reducing the number of traffic victims. The commonest traffic accidents in urban areas are due to sudden braking that demands a very fast response on the part of drivers. Attempts to solve this problem have motivated many ITS advances including the detection of the intention of surrounding cars using lasers, radars or cameras. However, this might not be enough to increase safety when there is a danger of collision. Vehicle to vehicle communications are needed to ensure that the other intentions of cars are also available. The article describes the development of a controller to perform an emergency stop via an electro-hydraulic braking system employed on dry asphalt. An original V2V communication scheme based on WiFi cards has been used for broadcasting positioning information to other vehicles. The reliability of the scheme has been theoretically analyzed to estimate its performance when the number of vehicles involved is much higher. This controller has been incorporated into the AUTOPIA program control for automatic cars. The system has been implemented in Citroën C3 Pluriel, and various tests were performed to evaluate its operation

FLAMINGO – Fulfilling enhanced location accuracy in the mass-market through initial GalileO services

This paper discusses FLAMINGO, an initiative that will provide a high accuracy positioning service to be used by mass market applications. The status and future for the initiative are discussed, the required accuracies and other location parameters are described, and the target applications are identified. Finally, the currently achieved accuracies from today’s Smartphones are assessed and presented. FLAMINGO (Fulfilling enhanced Location Accuracy in the Mass-market through Initial GalileO services), part funded through the European GNSS Agency, is a collaborative venture comprising NSL (as lead organization), Telespazio France, University of Nottingham, Rokubun, Thales Alenia Space France, VVA, BQ, ECLEXYS and Blue Dot Solutions. The initiative is developing the infrastructure, solutions and services to enable the use of accurate and precise GNSS within the mass-market, thereby operating predominantly in an urban environment. Whilst mass-market receivers are yet to achieve accuracies below one metre for standard positioning, the introduction of Android raw GNSS measurements and the Broadcom dual frequency chipset (BCM47755), has presented the devices such an opportunity. FLAMINGO will enable and demonstrate the future of high accuracy positioning and navigation information on mass-market devices such as smartphones and Internet of Things (IoT) devices by producing a service delivering accuracies of 50cm (at 95%) and better, employing multi-constellation, PPP and RTK mechanisms, power consumption optimisation techniques. Whereas the Galileo High Accuracy Service targets 10cm precision within professional markets, FLAMINGO targets 30-50cm precision in the mass-market consumer markets. By targeting accuracies of a few decimetres, a range of improved and new applications in diverse market sectors are introduced. These sectors include, but are not limited to, mapping and GIS, autonomous vehicles, AR environments, mobile-location based gaming and people tracking. To obtain such high accuracies with mass market devices, FLAMINGO must overcome several challenges which are technical, operational and environmental. This includes the hardware capabilities of most mass-market devices, where components such as antennas and processors are prioritised for other purposes. We demonstrate that, despite these challenges, FLAMINGO has the potential to meet the accuracy required. Tests with the current Smartphones that provide access to multi-constellation raw measurements (the dual frequency Xiaomi Mi 8 and single frequency Samsung S8 and Huawei P10) demonstrate significant improvements to the PVT solution when processing using both RTK and PPP techniques

Smartboard for surfing

The Internet of Things has democratized the use of sports' monitoring devices. The majority of these devices, available on the market, are targeted to the fitness practice creating the necessity of having different solutions for different sports. This work focuses on the development of a low-profile surf monitoring device capable of acquiring the required data for an existing algorithm developed by Fraunhofer Portugal. The resulting system should support long periods inside the water (low-power and waterproofed) without interfering with the athlete's performance (low-profile) and be able of transmitting the acquired data for an external device. Due to project's requirements, some of the technologies were already selected (microcontroller, gyroscope, magnetometer, accelerometer and GNSS module). However other technologies such as: the wireless communication system, storage method and power system needed to be selected. For the first, the system data throughput was estimated and the technology with the best relation throughput vs. power consumption was selected. To select the storage method, a survey was conducted to estimate the relation between each technology's price and data size. To select the power system, two studies were conducted in order to infer the hypothesis of supplying the system with photovoltaic cells, increasing the autonomy during a surf session: a power consumption study to estimate the system's power requirements and a solar irradiance study to predict the required area of photovoltaic cells. In order to determine the impact of having epoxy resin, commonly used to cover surf boards, some tests were conducted by applying this resin over the cells and measuring the output power