Random Finite Set Approach to Signal Strength Based Passive Localization and Tracking

Radio frequency sensor networks can be utilized for locating and tracking people within coverage area of the network. The technology is based on the fact that humans alter properties of the wireless propagation channel which is observed in the channel estimates, enabling tracking without requiring people to carry any sensor, tag or device. Considerable efforts have been made to model the human induced perturbations to the channel and develop flexible models that adapt to the unique propagation environment to which the network is deployed in. This paper proposes a noteworthy conceptual shift in the design of passive localization and tracking systems as the focus is shifted from channel modeling to filter design. We approach the problem using random finite set theory enabling us to model detections, missed detections, false alarms and unknown data association in a rigorous manner. The Bayesian filtering recursion applied with random finite sets is presented and a computationally tractable Gaussian sum filter is developed. The development efforts of the paper are validated using experimental data and the results imply that the proposed approach can decrease the tracking error up to 48% with respect to a benchmark solution.Peer reviewe

Direct Path Interference Suppression Requirements for Bistatic Backscatter Communication System

The ambient backscatter communication (AmBC) system utilizes the existing ambient RF signals present in the atmosphere for backscattering the signal. One of the challenges for AmBC system is the interference at the receiver module caused by the direct path signal from the ambient source. The purpose of this paper is to study the coverage aspects of the bi-static backscatter communication system in a typical urban environment at sub-1GHz frequencies using simulations in MATLAB. For the simulation, 3rd generation partnership project (3GPP) urban microcellular and international telecommunication union (ITU) device-to-device (D2D) propagation models are used. Moreover, the dynamic range i.e., the difference in the received power level of the direct path and the backscatter path is investigated. For correctly decoding the backscatter signal at the reader, the target value set for the dynamic range is less than 30 dB. This paper studies the importance of direct path interference suppression for the successful deployment of a bi-static backscatter communication system.acceptedVersionPeer reviewe

Localization Services for Online Common Operational Picture and Situation Awareness

Many operations, be they military, police, rescue, or other field operations, require localization services and online situation awareness to make them effective. Questions such as how many people are inside a building and their locations are essential. In this paper, an online localization and situation awareness system is presented, called Mobile Urban Situation Awareness System (MUSAS), for gathering and maintaining localization information, to form a common operational picture. The MUSAS provides multiple localization services, as well as visualization of other sensor data, in a common frame of reference. The information and common operational picture of the system is conveyed to all parties involved in the operation, the field team, and people in the command post. In this paper, a general system architecture for enabling localization based situation awareness is designed and the MUSAS system solution is presented. The developed subsystem components and forming of the common operational picture are summarized, and the future potential of the system for various scenarios is discussed. In the demonstration, the MUSAS is deployed to an unknown building, in an ad hoc fashion, to provide situation awareness in an urban indoor military operation.Peer reviewe

Unsupervised Learning in RSS-Based DFLT Using an EM Algorithm

Received signal strength (RSS) changes of static wireless nodes can be used for device-free localization and tracking (DFLT). Most RSS-based DFLT systems require access to calibration data, either RSS measurements from a time period when the area was not occupied by people, or measurements while a person stands in known locations. Such calibration periods can be very expensive in terms of time and effort, making system deployment and maintenance challenging. This paper develops an Expectation-Maximization (EM) algorithm based on Gaussian smoothing for estimating the unknown RSS model parameters, liberating the system from supervised training and calibration periods. To fully use the EM algorithm's potential, a novel localization-and-tracking system is presented to estimate a target's arbitrary trajectory. To demonstrate the effectiveness of the proposed approach, it is shown that: (i) the system requires no calibration period; (ii) the EM algorithm improves the accuracy of existing DFLT methods; (iii) it is computationally very efficient; and (iv) the system outperforms a state-of-the-art adaptive DFLT system in terms of tracking accuracy

Ambient Backscatter Communications for Future Ultra-Low-Power Machine Type Communications: Challenges, Solutions, Opportunities, and Future Research Trends

The widespread applications of massive MTC are limited by energy availability, spectrum congestion, and device costs. The emerging AmBC not only addresses these bottlenecks but also opens opportunities for new applications. This article aims to explore AmBC-enhanced future ultra-low-power MTC. In this context, we present the development trends in AmBC prototype designs and discuss potential applications, highlight the specific features of the AmBC technology, and review AmBC receiver designs. Finally, we investigate and outline the future research challenges and trends from the practical aspects of AmBC systems.Peer reviewe