Doctor of Philosophy

dissertationDevice-free localization (DFL) and tracking services are important components in security, emergency response, home and building automation, and assisted living applications where an action is taken based on a person's location. In this dissertation, we develop new methods and models to enable and improve DFL in a variety of radio frequency sensor network configurations. In the first contribution of this work, we develop a linear regression and line stabbing method which use a history of line crossing measurements to estimate the track of a person walking through a wireless network. Our methods provide an alternative approach to DFL in wireless networks where the number of nodes that can communicate with each other in a wireless network is limited and traditional DFL methods are ill-suited. We then present new methods that enable through-wall DFL when nodes in the network are in motion. We demonstrate that we can detect when a person crosses between ultra-wideband radios in motion based on changes in the energy contained in the first few nanoseconds of a measured channel impulse response. Through experimental testing, we show how our methods can localize a person through walls with transceivers in motion. Next, we develop new algorithms to localize boundary crossings when a person crosses between multiple nodes simultaneously. We experimentally evaluate our algorithms with received signal strength (RSS) measurements collected from a row of radio frequency (RF) nodes placed along a boundary and show that our algorithms achieve orders of magnitude better localization classification than baseline DFL methods. We then present a way to improve the models used in through-wall radio tomographic imaging with E-shaped patch antennas we develop and fabricate which remain tuned even when placed against a dielectric. Through experimentation, we demonstrate the E-shaped patch antennas lower localization error by 44% compared with omnidirectional and microstrip patch antennas. In our final contribution, we develop a new mixture model that relates a link's RSS as a function of a person's location in a wireless network. We develop new localization methods that compute the probabilities of a person occupying a location based on our mixture model. Our methods continuously recalibrate the model to achieve a low localization error even in changing environments

Mitigation of multipath fading in indoor radiometric fingerprinting systems

Wireless sensor network technology offers endless possibilities for innovative solutions for different security and intrusion detection and recognition applications. By distribut- ing multiple clusters of preconfigured wireless sensor network detection nodes, a widely monitored area can be consistently checked for intruders. These systems are simple, easy to install and reliable in detecting intruders automatically. This paper presents the utiliza- tion of a wireless sensor network as a non-invasive human identification system for smart homes and security applications. The proposed scheme analyzes the effect of individuals moving into a monitored area, where the 2.4 GHz wireless sensor network has been in- stalled. It is imperative to comprehend the critical impact caused by different human bod- ies on multiple readings of Received Signal Strength Indicator collected at different levels for individuals at the same recording position. Multiple experiments were performed by utilizing the wireless sensor network nodes on different individuals at different positions. The paper particularly studies the effect of filtration and change of filtering parameters used to mitigate the multipath effect on the accuracy and detection capacity of the pre- sented IEEE802.15.4-based radiometric human identification scheme

Doctor of Philosophy

dissertationLow-cost wireless embedded systems can make radio channel measurements for the purposes of radio localization, synchronization, and breathing monitoring. Most of those systems measure the radio channel via the received signal strength indicator (RSSI), which is widely available on inexpensive radio transceivers. However, the use of standard RSSI imposes multiple limitations on the accuracy and reliability of such systems; moreover, higher accuracy is only accessible with very high-cost systems, both in bandwidth and device costs. On the other hand, wireless devices also rely on synchronized notion of time to coordinate tasks (transmit, receive, sleep, etc.), especially in time-based localization systems. Existing solutions use multiple message exchanges to estimate time offset and clock skew, which further increases channel utilization. In this dissertation, the design of the systems that use RSSI for device-free localization, device-based localization, and breathing monitoring applications are evaluated. Next, the design and evaluation of novel wireless embedded systems are introduced to enable more fine-grained radio signal measurements to the application. I design and study the effect of increasing the resolution of RSSI beyond the typical 1 dB step size, which is the current standard, with a couple of example applications: breathing monitoring and gesture recognition. Lastly, the Stitch architecture is then proposed to allow the frequency and time synchronization of multiple nodes' clocks. The prototype platform, Chronos, implements radio frequency synchronization (RFS), which accesses complex baseband samples from a low-power low-cost narrowband radio, estimates the carrier frequency offset, and iteratively drives the difference between two nodes' main local oscillators (LO) to less than 3 parts per billion (ppb). An optimized time synchronization and ranging protocols (EffToF) is designed and implemented to achieve the same timing accuracy as the state-of-the-art but with 59% less utilization of the UWB channel. Based on this dissertation, I could foresee Stitch and RFS further improving the robustness of communications infrastructure to GPS jamming, allow exploration of applications such as distributed beamforming and MIMO, and enable new highly-synchronous wireless sensing and actuation systems

Intrusion detection based on embedded processing of received signal strength indicator

Langattomien anturiverkkojen yhteydessä, vastaanotetun signaalin voimakkuuden indikaattoria (RSSI, received signal strength indicator) on perinteisesti käytetty langattomien anturien paikallistamiseen, etäisyyden estimointiin ja radiolinkin hyvyyden arviointiin. Viimeaikainen tutkimus on osoittanut, että RSSI:n vaiheluita voidaan käyttää myös havaitsemaan ihmisten läsnäolo langattoman anturiverkon läheisyydessä. Sen lisäksi ihmisen kulkema reitti valvotulla alueella voidaan uudelleen rakentaa antureiden keräämistä RSSI mittauksista. Tämä menettely on toimiva, mutta se vaatii kaikkien RSSI mittausten lähettämistä keskussolmulle erillistä prosessointia varten ja täten se kasvattaa anturiverkon latenssia ja energian kulutusta. Diplomityön tavoitteena on käyttää RSSI mittauksia sisätilojen valvontaa varten prosessoimalla mittaukset hajautetusti anturitasolla. Hajautetulla prosessoinnilla anturiverkon solmut kykenevät itsenäisesti havaitsemaan henkilön ja seuraamaan hänen liikkeitään. Lähettämällä keskussolmulle vain hälytykset jotka liittyvät merkittäviin tapahtumiin, järjestelmän latenssi sekä energiankulutus pystytyään minimoimaan. Lisäksi järjestelmän käyttämä tarkka aikasynkronointiprotokolla mahdollistaa solmujen pitämään radionsa suljettuna yli puolet ajasta kasvattaen järjestelmän elinikää entisestään. Kokeiden aikana, esitetty järjestelmä kykeni havaitsemaan valvotulle alueelle tunkeutuneen ihmisen ja seuraamaan hänen liikkeitään reaaliajassa. Järjestelmän mahdollisia sovelluskohteita ovat kriittisen rakennusten valvonta, työntekijöiden turvallisuuden lisääminen teollisuudessa, edesauttaa pelastustyöntekijöitä löytämään ihmiset esimerkiksi tulipaloissa ja maanjäristyksissä, sekä avustamaan poliiseja panttivankitilanteissa tai terroristihyökkäyksissä.In the context of wireless sensor networks (WSNs), the received signal strength indicator (RSSI) has been traditionally exploited for nodes localization, distance estimation, and link quality assessment. Recent research has shown that variations of the RSSI in indoor environments where nodes have been deployed can be exploited to detect movements of people. Moreover, the time-histories of the RSSI of multiple links allow reconstructing the path followed by the person inside the monitored area. This approach, though effective, requires the transmission of multiple raw RSSI time-histories to a central sink node for off-line analysis, consistently increasing latency and power consumption of the system. This thesis aims at applying distributed processing of the RSSI measurements for indoor surveillance purposes. Through distributed processing, the nodes are able to autonomous-ly detect and track a moving person, minimizing latency and power consumption of the system by transmitting to the sink node only the alerts raised by significant events. More-over, a high accuracy time synchronization protocol allows the nodes to keep the radio off for over half of the time, increasing the life time of the system. During the tests, the proposed system was able to detect the intrusion of a person walking inside the monitored area, and to correctly keep track in real-time of the path he had followed. Possible applications of such a system include surveillance of buildings, enhancement of workers safety in factories, support to emergency workers in locating people e.g. during fires and earthquakes, and to police in hostage situations or terrorist attacks

Communicating through motion in dance and animal groups

This study explores principles of motion based communication in animal and human group behavior. It develops models of cooperative control that involve communication through actions aimed at a shared objective. Moreover, it aims at understanding the collective motion in multi-agent models towards a desired objective which requires interaction with the environment. In conducting a formal study of these problems, first we investigate the leader-follower interaction in a dance performance. Here, the prototype model is salsa. Salsa is of interest because it is a structured interaction between a leader (usually a male dancer) and a follower (usually a female dancer). Success in a salsa performance depends on how effectively the dance partners communicate with each other using hand, arm and body motion. We construct a mathematical framework in terms of a Dance Motion Description Language (DMDL). This provides a way to specify control protocols for dance moves and to represent every performance as sequences of letters and corresponding motion signals. An enhanced form of salsa (intermediate level) is discussed in which the constraints on the motion transitions are described by simple rules suggested by topological knot theory. It is shown that the proficiency hierarchy in dance is effectively captured by proposed complexity metrics. In order to investigate the group behavior of animals that are reacting to environmental features, we have analyzed a large data set derived from 3-d video recordings of groups of Myotis velifer emerging from a cave. A detailed statistical analysis of large numbers of trajectories indicates that within certain bounds of animal diversity, there appear to be common characteristics of the animals' reactions to features in a clearly defined flight corridor near the mouth of the cave. A set of vision-based motion control primitives is proposed and shown to be effective in synthesizing bat-like flight paths near groups of obstacles. A comparison of synthesized paths and actual bat motions culled from our data set suggests that motions are not based purely on reactions to environmental features. Spatial memory and reactions to the movement of other bats may also play a role. It is argued that most bats employ a hybrid navigation strategy that combines reactions to nearby obstacles and other visual features with some combination of spatial memory and reactions to the motions of other bats

Unmanned Aircraft Systems in the Cyber Domain

Unmanned Aircraft Systems are an integral part of the US national critical infrastructure. The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. This textbook will fully immerse and engage the reader / student in the cyber-security considerations of this rapidly emerging technology that we know as unmanned aircraft systems (UAS). The first edition topics covered National Airspace (NAS) policy issues, information security (INFOSEC), UAS vulnerabilities in key systems (Sense and Avoid / SCADA), navigation and collision avoidance systems, stealth design, intelligence, surveillance and reconnaissance (ISR) platforms; weapons systems security; electronic warfare considerations; data-links, jamming, operational vulnerabilities and still-emerging political scenarios that affect US military / commercial decisions. This second edition discusses state-of-the-art technology issues facing US UAS designers. It focuses on counter unmanned aircraft systems (C-UAS) – especially research designed to mitigate and terminate threats by SWARMS. Topics include high-altitude platforms (HAPS) for wireless communications; C-UAS and large scale threats; acoustic countermeasures against SWARMS and building an Identify Friend or Foe (IFF) acoustic library; updates to the legal / regulatory landscape; UAS proliferation along the Chinese New Silk Road Sea / Land routes; and ethics in this new age of autonomous systems and artificial intelligence (AI).https://newprairiepress.org/ebooks/1027/thumbnail.jp

Biometric Systems

Biometric authentication has been widely used for access control and security systems over the past few years. The purpose of this book is to provide the readers with life cycle of different biometric authentication systems from their design and development to qualification and final application. The major systems discussed in this book include fingerprint identification, face recognition, iris segmentation and classification, signature verification and other miscellaneous systems which describe management policies of biometrics, reliability measures, pressure based typing and signature verification, bio-chemical systems and behavioral characteristics. In summary, this book provides the students and the researchers with different approaches to develop biometric authentication systems and at the same time includes state-of-the-art approaches in their design and development. The approaches have been thoroughly tested on standard databases and in real world applications