There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Over the coming decades, high-definition situationally-aware networks have the potential to create revolutionary applications in the social, scientific, commercial, and military sectors Ultrawide bandwidth (UWB) technology is a viable candidate for enabling accurate localization capabilities through time-of-arrival (TOA)-based ranging techniques These techniques exploit the fine delay resolution property of UWB signals by estimating the TOA of the first signal path Exploiting the full capabilities of UWB TOA estimation can be challenging, especially when operating in harsh propagation environments, since the direct path may not exist or it may not be the strongest In this paper, we first give an overview of ranging techniques together with the primary sources of TOA error (including propagation effects, clock drift, and interference) We then describe fundamental TOA bounds (such as the Cramer-Rao bound and the tighter Ziv-Zakai bound) in both ideal and multipath environments These bounds serve as useful benchmarks in assessing the performance of TOA estimation techniques We also explore practical low-complexity TOA estimation techniques and analyze their performance in the presence of multipath and interference using IEEE 802154a channel models as well as experimental data measured in indoor residential environments

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Ranging With Ultrawide Bandwidth Signals in Multipath Environments

.............................................................................................................................................................. 6 1 Introduction ............................................................................................................................................. 7 1.1 Motivation .......................................................................................................................................................... 7 1.2 Previous Surveys ............................................................................................................................................. 8 1.3 Overview of Technologies ........................................................................................................................... 9 1.4 Indoor Positioning Applications ............................................................................................................ 11 1.5 Structure of this Work ............................................................................................................................... 14 2 User Requirements ............................................................................................................................. 15 2.1 Requirements Parameters Overview .................................................................................................. 15 2.2 Positioning Requirements Parameters Definition ......................................................................... 17 2.3 Man Machine Interface Requirements ................................................................................................ 19 2.4 Security and Privacy Requirements ..................................................................................................... 20 2.5 Costs .................................................................................................................................................................. 20 2.6 Generic Derivation of User Requirements......................................................................................... 20 2.7 Requirements for Selected Indoor Applications ............................................................................. 21 3 Definition of Terms ............................................................................................................................. 25 3.1 Disambiguation of Terms for Positioning .......................................................................................... 25 3.2 Definition of Technical Terms ................................................................................................................ 27 3.3 The Basic Measuring Principles ............................................................................................................. 29 3.4 Positioning Methods ................................................................................................................................... 31 4 Cameras .................................................................................................................................................. 34 4.1 Reference from 3D Building Models .................................................................................................... 35 4.2 Reference from Images .............................................................................................................................. 36 4.3 Reference from Deployed Coded Targets .......................................................................................... 37 4.4 Reference from Projected Targets ........................................................................................................ 38 4.5 Systems without Reference ..................................................................................................................... 39 4.6 Reference from Other Sensors ............................................................................................................... 40 4.7 Summary on Camera Based Indoor Positioning Systems ........................................................... 40 5 Infrared ................................................................................................................................................... 42 5.1 Active Beacons .............................................................................................................................................. 42 5.2 Imaging of Natural Infrared Radiation ............................................................................................... 43 5.3 Imaging of Artificial Infrared Light ....................................................................................................... 43 5.4 Summary on Infrared Indoor Positioning Systems ....................................................................... 44

Indoor Positioning Technologies

Jamming represents the most serious security threat in the field of wireless sensor networks (WSNs), as it can easily put out of order even WSNs that utilize strong highlayer security mechanisms, simply because it is often ignored in the initial WSN design. The objective of this article is to provide a general overview of the critical issue of jamming in WSNs and cover all the relevant work, providing the interested researcher pointers for open research issues in this field. We provide a brief overview of the communication protocols typically used in WSN deployments and highlight the characteristics of contemporary WSNs, that make them susceptible to jamming attacks, along with the various types of jamming which can be exercised against WSNs. Common jamming techniques and an overview of various types of jammers are reviewed and typical countermeasures against jamming are also analyzed. The key ideas of existing security mechanisms against jamming attacks in WSNs are presented and open research issues, with respect to the defense against jamming attacks are highlighted.

A survey on jamming attacks and countermeasures in WSNs

We describe our experiences deploying BikeNet, an extensible mobile sensing system for cyclist experience mapping leveraging opportunistic sensor networking principles and techniques. BikeNet represents a multifaceted sensing system and explores personal, bicycle, and environmental sensing using dynamically role-assigned bike area networking based on customized Moteiv Tmote Invent motes and sensor-enabled Nokia N80 mobile phones. We investigate real-time and delay-tolerant uploading of data via a number of sensor access points (SAPs) to a networked repository. Among bicycles that rendezvous en route we explore inter-bicycle networking via data muling. The repository provides a cyclist with data archival, retrieval, and visualization services. BikeNet promotes the social networking of the cycling community through the provision of a web portal that facilitates back end sharing of real-time and archived cycling-related data from the repository. We present: a description and prototype implementation of the system architecture, an evaluation of sensing and inference that quantifies cyclist performance and the cyclist environment; a report on networking performance in an environment characterized by bicycle mobility and human unpredictability; and a description of BikeNet system user interfaces. Visit [4] to see how the BikeNet system visualizes a user's rides.

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The BikeNet mobile sensing system for cyclist experience mapping

The research topic of sensor networks has been around for some time. With improvements in device size, power consumption, communications, and computing technology, sensor networks are becoming more popular for an ever increasing range of applications. Since 2002, there has been an increased in the popularity of commercial applications based on ultra wideband. This, in turn, has ignited interest in the use of this technology for sensor networks and fuelled research in the area. Impulse-radio-based UWB technology has a number of inherent properties that are well suited to sensor network applications. In particular, UWB systems have potentially low complexity and low cost, have noise-like signal, are resistant to severe multipath and jamming, and have very good time domain resolution allowing for location and tracking applications. This article examines one example of a UWB sensor network for outdoor sport and lifestyle applications.

UWB wireless sensor networks: UWEN - a practical example

Impulse-radio (IR)-based ultra-wideband (UWB) technology is a strong candidate for short-range data communication and positioning systems. This paper examines the performance of time-of-arrival (TOA) position estimation techniques as well as the simulated and measured performances of an IR-UWB noncoherent energy-collection receiver. The noncoherent IR-UWB transceiver has been designed for operation over the frequency range 3.1-4.1 GHz and implemented in 0.35-/spl mu/m SiGe BiCMOS technology. The performance of two different algorithms, namely, the threshold-crossing and the maximum selection (MAX) algorithms, are compared in terms of TOA estimation error in Saleh Valenzuela channel model 3 and channel model 4. The implemented structure of the TOA MAX algorithm suitable for IR-UWB-based noncoherent receivers is presented. A UWB testbed has been constructed in order to test and measure the transmitted waveform as well the receiver performances. The simulated receiver noise figure is 7.3 dB while the receiver gain is 34 dB. The TOA MAX algorithm can achieve /spl plusmn/5-ns positioning accuracy for 95% of cases. Constant transconductance tuning circuits for improved TOA estimation reliability are also presented.

A low-complexity noncoherent IR-UWB transceiver architecture with TOA estimation

With the latest improvements in device size, power consumption, and communications, sensor networks are becoming increasingly more popular. There has also been a great increase in the popularity of commercial applications based on ultrawideband (UWB). Impulse radio (IR) based UWB technology utilizes noise-like signal, has potentially low complexity and low cost, is resistant to severe multipath, and has very good time domain resolution allowing for location and tracking applications. In this paper, the architecture and performance of a noncoherent low complexity UWB impulse radio based transceiver designed for low data rate, low cost sensor network applications is presented. The UWB-IR transmitter is based on a delay locked loop (DLL) and UWB monocycle pulse generator. The UWB-IR receiver utilises a noncoherent, energy detection based approach, which makes it largely independent of the shape of the transmit waveform and robust to multipath channels. The test circuits are designed for 0.35 /spl mu/m SiGe BiCMOS technology. This paper presents system simulations results as well as the performance of key functional blocks of the designed UWB application specific integrated circuit (ASIC) transceiver architecture. The simulated power consumption of UWB-IR transceiver circuits is 136 mW with 100% duty cycle with a 3.3 V power supply.

An ultrawideband system architecture for tag based wireless sensor networks

Preface 7 List of symbols and abbreviations 9

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Non-coherent energy detection transceivers for Ultra Wideband Impulse radio systems

The paper presents the architecture of a low power, low complexity ultra wideband (UWB) transceiver circuit. The circuit is designed for low data rate, low cost applications with built in location and tracking. The system is based on a non-coherent architecture which enables the receiver to be extremely simple and largely insensitive to the transmitted pulse shape. The circuit presented contains the oscillator generator, the transmitter, the receiver and baseband digital signal processing (DSP) block. The oscillator generator contains the quartz oscillator, a delay-locked loop (DLL) and edge combiner for clock multiplication to generate a 495 MHz timing signal for pulse generation. The transmitter contains a second DLL (to fix the UWB pulse delay), UWB pulse generator and antenna. The 495 MHz RF signal together with the transmitted UWB pulse are presented. The receiver contains low noise amplifier, variable gain amplifier, squaring circuits, integrators for energy collection, 4 bit A/D converters, digital control logic, integrator and gain selection logic block and detection/bit decision block. The circuits are designed in a 0.35 /spl mu/m Si-Ge BiCMOS process from Austria Microsystems. The UWB TAG is not yet manufactured.

https://ieeexplore.ieee.org/iel5/9232/29256/01320975.pdf

L. Stoica

Papers

UWB wireless sensor networks: UWEN - a practical example

A low-complexity noncoherent IR-UWB transceiver architecture with TOA estimation

An ultrawideband system architecture for tag based wireless sensor networks

Non-coherent energy detection transceivers for Ultra Wideband Impulse radio systems

An ultra wideband TAG circuit transceiver architecture