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In this paper we present a novel probabilistic approach to activity recognition. Our approach is to estimate posterior probabilities of different activities using Bayes' rule. The approach can handle any type of activities as long as it is possible to estimate the conditional probabilities of potential observations, and easily scales to large numbers of activities. We test our approach empirically...
Celebrated fingerprinting techniques localize users by statistically learning the signal to location relations. However, collecting a lot of labelled data to train an accurate localization model is expensive and labour-intensive. In this paper, an economic and easy-to-deploy indoor localization model suitable for ubiquitous smartphone platforms is established. The method processes embedded inertial...
A tracking scenario comprising a mobile emitter node moving through an indoor environment covered by multiple anchor receivers is investigated in this work. A localization method based on received signal strength indicators (RSSI) and making use of the extended Kalman filter (EKF) and circularly polarized (CP) antennas is proposed. The EKF implements the position-velocity (PV) model, which assumes...
Ranging accuracy and reliability is crucial for any cooperative- and non-cooperative positioning system applied for unmanned vehicle localization, and formation estimation. State of the art systems exploit received signal strength (RSS) from WiFi devices, or ultra-wide bandwidth (UWB) timing based range estimation. RSS proved to be unreliable in environments with multipath, and UWB combats multipath...
In this paper, we present a high data rate communication system with an integrated high-resolution ranging feature. The point-to-point communication system is based on an OFDM baseband processor (BB) with data rates up to 3.9 Gbps, a medium access controller (MAC), and an analog frontend (AFE) for the 60 GHz band. The ranging system determines the distance between two stations using the round trip...
In this paper we present a method for improving the precision of an RSSI-based energy-constrained localization system employed in an IEEE 802.15.4 sensor network. The goal application is localization of people in dynamic indoor environments. We introduce an approach which divides the anchor nodes into groups and assigns a path loss exponent to each group. The results from the conveyed tests in our...
In this paper we present a novel approach for the estimation of metric velocities and metric distances to landmarks utilizing monocular images and inertial measurements only. The proposed algorithm is based on an Extended Kalman Filter and is closely related to the well known Simultaneous Localization and Mapping (SLAM). In contrast to standard SLAM formulations the state of an agent is expressed...
This contribution is addressed to the problem of highly resolving the propagation time delays and the relative amplitudes associated with signals in multipath communication channels. The Unitary Matrix Pencil (UMP) algorithm is applied in a new way to estimate these parameters from the measured channel frequency response (CFR) using wideband orthogonal multicarrier signals. The mobile unit (MU) is...
Pedestrian localization systems require the knowledge of a user's position for manifold applications in indoor and outdoor environments. For this purpose several methods can be used, such as a Global Navigation Satellite System (GNSS) or an Inertial Navigation Systems (INS). Since GNSS are not available in indoor environments or street canyons a Time Difference of Arrival (TDoA) system and a low cost...
RevolverNet, operates over wireless ad-hoc networks where nodes communicate in duty cycles. When not at sleep, nodes beacon their own data and listen for data coming from neighboring nodes. Importantly, this mode of operation is increasingly becoming a prominent feature in a variety of communication setups, including emergency response networks (ERNs). RevolverNet is purposefully designed to take...
This paper presents results of a large real world experimental setup of an indoor localization system. We used a time-of-flight based radio range measurement system to collect a large body of ranging data between a mobile reference system and multiple anchor nodes with a fixed and known position. For our experiment the reference system moved autonomously through an office building while collecting...
Global Navigation Satellite System (GNSS) signals, inertial measurements (angular rates, accelerations) and magnetometer measurements complement each other for position determination: GNSS provides a precise and drift-free position solution but is susceptible to signal outages. Inertial measurements are continuously available and of higher rate but suffer from integration drifts. Magnetic field measurements...
This paper presents a novel mobility model to perform realistic simulations of human movements and behav-iors. The proposed model is based on discrete event simulation and graph theory. The proposed model is implemented in a wireless propagation simulator and used to evaluate various wireless network protocols including: propagation, localization and communication.
The positioning and tracing of multiple users is an important data source for ubiquitous assistance in smart environments and its superimposed intention recognition systems. Within application areas like elderly care or ambient assisted living, non-invasive, wireless, privacy preserving j technologies are indispensable. Device-free localization approaches (DFL) provide these advantages with no need...
Bayesian estimation methods are widely used for wireless localization systems. They employ priori information and current measurement error distribution models to derive the state of a mobile target. Cramér-Rao lower bound (CRLB) is a fundamental tool to analyze the performance of Bayesian estimators. Although CRLB is derived based on the measurement error distribution, only a few works have investigated...
In this paper we discuss robust cooperative localization in mixed line-of-sight and non-line-of-sight environments using time-of-arrival measurements. The mixed line-of-sight and non-line-of-sight environment is statistically modeled using a contaminated Gaussian mixture model in which the non-line-of-sight propagations are assumed to cause a positive bias in the time-of-arrival measurements. The...
In this paper, the problem of mobile tracking in dense environments is studied. The Global Positioning System (GPS) is the most accessible positioning technique. However, GPS does not work properly in indoor and dense areas, as the receiver typically does not have access to a sufficient number of line-of-sight satellites. Therefore, localization in these networks can be alternatively done by using...
In many localization systems, the Mobile Node (MN) takes distance measurements with reference nodes called Anchors (ANs) in order to estimate its position. In general, the MN can obtain a better estimation when it takes measurements with multiple ANs. Unfortunately, this can lead to consume more energy and generate more traffic in the network. In this paper, we present an adaptive mechanism for the...
In this paper, a 2-stage robust distributed algorithm is proposed for cooperative sensor network localization using time of arrival (TOA) data without identification of non-line of sight (NLOS) links. In the first stage, to overcome the effect of outliers, a convex relaxation of the Huber loss function is applied so that by using iterative optimization techniques, good estimates of the true sensor...
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