PINSPOT: An oPen platform for INtelligent context-baSed Indoor POsiTioning

This work proposes PINSPOT; an open-access platform for collecting and sharing of context, algorithms and results in the cutting-edge area of indoor positioning. It is envisioned that this framework will become reference point for knowledge exchange which will bring the research community even closer and potentially enhance collaboration towards more effective and efficient creation of indoor positioning-related knowledge and innovation. Specifically, this platform facilitates the collection of sensor data useful for indoor positioning experimentation, the development of novel, self-learning, indoor positioning algorithms, as well as the enhancement and testing of existing ones and the dissemination and sharing of the proposed algorithms along with their configuration, the data used, and with their results

A Statistically Modelling Method for Performance Limits in Sensor Localization

In this paper, we study performance limits of sensor localization from a novel perspective. Specifically, we consider the Cramer-Rao Lower Bound (CRLB) in single-hop sensor localization using measurements from received signal strength (RSS), time of arrival (TOA) and bearing, respectively, but differently from the existing work, we statistically analyze the trace of the associated CRLB matrix (i.e. as a scalar metric for performance limits of sensor localization) by assuming anchor locations are random. By the Central Limit Theorems for $U$-statistics, we show that as the number of the anchors increases, this scalar metric is asymptotically normal in the RSS/bearing case, and converges to a random variable which is an affine transformation of a chi-square random variable of degree 2 in the TOA case. Moreover, we provide formulas quantitatively describing the relationship among the mean and standard deviation of the scalar metric, the number of the anchors, the parameters of communication channels, the noise statistics in measurements and the spatial distribution of the anchors. These formulas, though asymptotic in the number of the anchors, in many cases turn out to be remarkably accurate in predicting performance limits, even if the number is small. Simulations are carried out to confirm our results

Yeni Bir İç Mekân Konum Bulma Sistemi

Teknolojinin gelişimine paralel olarak konum bulma sistemleri çok önem kazanmıştır. Konum bulma sistemleri dış mekân konum bulma sistemleri ve iç mekân konum bulma sistemleri diye temel olarak iki sınıf altında toplanmıştır. Dış mekân konum bulma sistemleri genellikle GPS sinyallerini temel aldığı için iç ortamda verimli bir şekilde çalışmamaktadır. İç mekân konum bulma sistemleri gelişimini sürdürmektedir ve üzerine birçok çalışma yapılmaktadır. Bu çalışmada, verimli bir iç mekan konum bulma sistemi oluşturabilmek için elektronik kart tasarımları gerçekleştirilmiştir. İç mekân konum bulma yöntemi için bu kartlara uygun yazılımlar hazırlanmıştır. Ayrıca sistemi verimli bir şekilde analiz edebilmek için arayüz programı tasarlanmıştır. Yapılan test sonuçları ve veriler incelendiğinde iç mekân konum bulma sistemi için uygun maliyet ile yakın doğruluk değerlerine ulaşıldığı gözlemlenmiştir

Preliminary Deep Water Results in Single-Beacon One-Way-Travel-Time Acoustic Navigation for Underwater Vehicles

This paper reports the development and experimental evaluation of a novel navigation system for underwater vehicles that employs Doppler sonar, synchronous clocks, and acoustic modems to achieve simultaneous acoustic communication and navigation. The system reported herein, which is employed to renavigate the vehicle in post-processing, forms the basis for a vehicle-based real-time navigation system. Existing high-precision absolute navigation techniques for underwater vehicles are impractical over long length scales and lack scalability for simultaneously navigating multiple vehicles. The navigation method reported in this paper relies on a single moving reference beacon, eliminating the requirement for the underwater vehicle to remain in a bounded navigable area. The use of underwater modems and synchronous clocks enables range measurements based on one-way time-of-flight information from acoustic data packet broadcasts. The acoustic data packets are broadcast from the single, moving reference beacon and can be received simultaneously by multiple vehicles within acoustic range. We report experimental results from the first deep-water evaluation of this method using data collected from an autonomous underwater vehicle (AUV) survey carried out in 4000 m of water on the southern Mid-Atlantic Ridge. We report a comparative experimental evaluation of the navigation fixes provided by the proposed synchronous acoustic navigation system in comparison to navigation fixes obtained by an independent conventional long baseline acoustic navigation system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86040/1/swebster-7.pd

Indoor Localization Using Uncooperative Wi-Fi Access Points

Indoor localization using fine time measurement (FTM) round-trip time (RTT) with respect to cooperating Wi-Fi access points (APs) has been shown to work well and provide 1–2 m accuracy in both 2D and 3D applications. This approach depends on APs implementing the IEEE 802.11-2016 (also known as IEEE 802.11mc) Wi-Fi standard (“two-sided” RTT). Unfortunately, the penetration of this Wi-Fi protocol has been slower than anticipated, perhaps because APs tend not to be upgraded as often as other kinds of electronics, in particular in large institutions—where they would be most useful. Recently, Google released Android 12, which also supports an alternative “one-sided” RTT method that will work with legacy APs as well. This method cannot subtract out the “turn-around” time of the signal, and so, produces distance estimates that have much larger offsets than those seen with two-sided RTT—and the results are somewhat less accurate. At the same time, this method makes possible distance measurements for many APs that previously could not be used. This increased accessibility can compensate for the decreased accuracy of individual measurements. We demonstrate here indoor localization using one-sided RTT with respect to legacy APs that do not support IEEE 802.11-2016. The accuracy achieved is 3–4 m in cluttered environments with few line-of-sight readings (and using only 20 MHz bandwidths). This is not as good as for two-sided RTT, where 1–2 m accuracy has been achieved (using 80 MHz bandwidths), but adequate for many applications A wider Wi-Fi channel bandwidth would increase the accuracy further. As before, Bayesian grid update is the preferred method for determining position and positional accuracy, but the observation model now is different from that for two-sided RTT. As with two-sided RTT, the probability of an RTT measurement below the true distance is very low, but, in the other direction, the range of measurements for a given distance can be much wider (up to well over twice the actual distance). We describe methods for formulating useful observation models. As with two-sided RTT, the offset or bias in distance measurements has to be subtracted from the reported measurements. One difference is that here, the offsets are large (typically in the 2400–2700 m range) because of the “turn-around time” of roughly 16 μs (i.e., about two orders of magnitude larger than the time of flight one is attempting to measure). We describe methods for estimating these offsets and for minimizing the effort required to do so when setting up an installation with many APs

Position certainty propagation: a location service for MANETs

International audienceLocalization in Mobile Ad-hoc Networks (MANETs) and Wireless Sensor Networks (WSNs) is an issue of great interest, especially in applications such as the IoT and VANETs. We propose a solution that overcomes two limiting characteristics of these types of networks. The first is the high cost of nodes with a location sensor (such as GPS) which we will refer to as anchor nodes. The second is the low computational capability of nodes in the network. The proposed algorithm addresses two issues; self-localization where each non-anchor node should discover its own position, and global localization where a node establishes knowledge of the position of all the nodes in the network. We address the problem as a graph where vertices are nodes in the network and edges indicate connectivity between nodes. The weights of edges represent the Euclidean distance between the nodes. Given a graph with at least three anchor nodes and knowing the maximum communication range for each node, we are able to localize nodes using fairly simple computations in a moderately dense graph

On the Performance Limits of Map-Aware Localization

Establishing bounds on the accuracy achievable by localization techniques represents a fundamental technical issue. Bounds on localization accuracy have been derived for cases in which the position of an agent is estimated on the basis of a set of observations and, possibly, of some a priori information related to them (e.g., information about anchor positions and properties of the communication channel). In this paper, new bounds are derived under the assumption that the localization system is map-aware, i.e., it can benefit not only from the availability of observations, but also from the a priori knowledge provided by the map of the environment where it operates. Our results show that: a) map-aware estimation accuracy can be related to some features of the map (e.g., its shape and area) even though, in general, the relation is complicated; b) maps are really useful in the presence of some combination of low SNRs and specific geometrical features of the map (e.g., the size of obstructions); c) in most cases, there is no need of refined maps since additional details do not improve estimation accuracy.United States. Air Force Office of Scientific Research (Grant FA9550-12-0287)United States. Office of Naval Research (Grant N00014-11-1-0397)Massachusetts Institute of Technology. Institute for Soldier Nanotechnologie