A Markov Model for Dynamic Behavior of Toa-Based Ranging in Indoor Localization

The existence of undetected direct path ( UDP) conditions causes occurrence of unexpected large random ranging errors which pose a serious challenge to precise indoor localization using time of arrival ( ToA). Therefore, analysis of the behavior of the ranging error is essential for the design of precise ToA-based indoor localization systems. In this paper, we propose a novel analytical framework for the analysis of the dynamic spatial variations of ranging error observed by a mobile user based on an application of Markov chain. the model relegates the behavior of ranging error into four main categories associated with four states of the Markov process. the parameters of distributions of ranging error in each Markov state are extracted from empirical data collected from a measurement calibrated ray tracing ( RT) algorithm simulating a typical office environment. the analytical derivation of parameters of the Markov model employs the existing path loss models for the first detected path and total multipath received power in the same office environment. Results of simulated errors from the Markov model and actual errors from empirical data show close agreement

Indoor Cooperative Localization for Ultra Wideband Wireless Sensor Networks

In recent years there has been growing interest in ad-hoc and wireless sensor networks (WSNs) for a variety of indoor applications. Localization information in these networks is an enabling technology and in some applications it is the main sought after parameter. The cooperative localization performance of WSNs is ultimately constrained by the behavior of the utilized ranging technology in dense cluttered indoor environments. Recently, ultra-wideband (UWB) Time-of-Arrival (TOA) based ranging has exhibited potential due to its large bandwidth and high time resolution. However, the performance of its ranging and cooperative localization capabilities in dense indoor multipath environments needs to be further investigated. Of main concern is the high probability of non-line of sight (NLOS) and Direct Path (DP) blockage between sensor nodes, which biases the TOA estimation and degrades the localization performance. In this dissertation, we first present the results of measurement and modeling of UWB TOA-based ranging in different indoor multipath environments. We provide detailed characterization of the spatial behavior of ranging, where we focus on the statistics of the ranging error in the presence and absence of the DP and evaluate the pathloss behavior in the former case which is important for indoor geolocation coverage characterization. Parameters of the ranging error probability distributions and pathloss models are provided for different environments: traditional office, modern office, residential and manufacturing floor; and different ranging scenarios: indoor-to-indoor (ITI), outdoor-to-indoor (OTI) and roof-to-indoor (RTI). Based on the developed empirical models of UWB TOA-based OTI and ITI ranging, we derive and analyze cooperative localization bounds for WSNs in the different indoor multipath environments. First, we highlight the need for cooperative localization in indoor applications. Then we provide comprehensive analysis of the factors affecting localization accuracy such as network and ranging model parameters. Finally we introduce a novel distributed cooperative localization algorithm for indoor WSNs. The Cooperative LOcalization with Quality of estimation (CLOQ) algorithm integrates and disseminates the quality of the TOA ranging and position information in order to improve the localization performance for the entire WSN. The algorithm has the ability to reduce the effects of the cluttered indoor environments by identifying and mitigating the associated ranging errors. In addition the information regarding the integrity of the position estimate is further incorporated in the iterative distributed localization process which further reduces error escalation in the network. The simulation results of CLOQ algorithm are then compared against the derived G-CRLB, which shows substantial improvements in the localization performance

Modeling the Behavior of Multipath Components Pertinent to Indoor Geolocation

Recently, a number of empirical models have been introduced in the literature for the behavior of direct path used in the design of algorithms for RF based indoor geolocation. Frequent absence of direct path has been a major burden on the performance of these algorithms directing researchers to discover algorithms using multipath diversity. However, there is no reliable model for the behavior of multipath components pertinent to precise indoor geolocation. In this dissertation, we first examine the absence of direct path by statistical analysis of empirical data. Then we show how the concept of path persistency can be exploited to obtain accurate ranging using multipath diversity. We analyze the effects of building architecture on the multipath structure by demonstrating the effects of wall length and wall density on the path persistency. Finally, we introduce a comprehensive model for the spatial behavior of multipath components. We use statistical analysis of empirical data obtained by a measurement calibrated ray-tracing tool to model the time-of- arrival, angle-of-arrival and path gains. The relationship between the transmitter-receiver separation and the number of paths are also incorporated in our model. In addition, principles of ray optics are applied to explain the spatial evolution of path gains, time-of-arrival and angle-of-arrival of individual multipath components as a mobile terminal moves inside a typical indoor environment. We also use statistical modeling for the persistency and birth/death rate of the paths

Diffraction Analysis with UWB Validation for ToA Ranging in the Proximity of Human Body and Metallic Objects

The time-of-arrival (ToA)-based localization technique performs superior in line-of-sight (LoS) conditions, and its accuracy degrades drastically in proximity of micro-metals and human body, when LoS conditions are not met. This calls for modeling and formulation of Direct Path (DP) to help with mitigation of ranging error. However, the current propagation tools and models are mainly designed for telecommunication applications via focus on delay spread of wireless channel profile, whereas ToA-based localization strive for modeling of DP component. This thesis provides a mitigation to the limitation of existing propagation tools and models to computationally capture the effects of micro-metals and human body on ToA-based indoor localization. Solutions for each computational technique are validated by empirical measurements using Ultra-Wide-Band (UWB) signals. Finite- Difference-Time-Domain (FDTD) numerical method is used to estimate the ranging errors, and a combination of Uniform-Theory-of-Diffraction (UTD) ray theory and geometrical ray optics properties are utilized to model the path-loss and the ToA of the DP obstructed by micro- metals. Analytical UTD ray theory and geometrical ray optics properties are exploited to model the path-loss and the ToA of the first path obstructed by the human body for the scattering scenarios. The proposed scattering solution expanded to analytically model the path-loss and ToA of the DP obstructed by human body in angular motion for the radiation scenarios

Sensitivity Analysis for Measurements of Multipath Parameters Pertinent to TOA based Indoor Geolocation

Recently, indoor geolocation technologies has been attracting tremendous attention. For indoor environments, the fine time resolution of ultra-wideband (UWB) signals enables the potential of accurate distance measurement of the direct path (DP) between a number of reference sources and the people or assets of interest. However, Once the DP is not available or is shadowed, substantial errors will be introduced into the ranging measurements, leading to large localization errors when measurements are combined from multiple sources. The measurement accuracy in undetected direct path (UDP) conditions can be improved in some cases by exploiting the geolocation information contained in the indirect path measurements. Therefore, the dynamic spatial behavior of paths is an important issue for positioning techniques based on TOA of indirect paths. The objectives of this thesis are twofold. The first is to analyze the sensitivity of TOA estimation techniques based on TOA of the direct path. we studied the effect of distance, bandwidth and multipath environment on the accuracy of various TOA estimation techniques. The second is to study the sensitivity of multipath parameters pertinent to TOA estimation techniques based on the TOA of the indirect paths. We mainly looked into the effect of distance, bandwidth, threshold for picking paths, and multipath environment on the number of multipath components(MPCs) and path persistency. Our results are based on data from a new measurement campaign conducted on the 3rd floor of AK laboratory. For the TOA estimation techniques based on DP, the line of sight (LOS) scenario provides greatest accuracy and these TOA estimation techniques are most sensitive to bandwidth availability in obstructed line of sight (OLOS) scenario. All the TOA estimation algorithms perform poorly in the UDP scenario although the use of higher bandwidth can reduce the ranging error to some extent. Based on our processed results, The proposal for selecting the appropriate TOA estimation technique with certain constrains is given. The sensitivity study of multipath parameters pertinent to indirect-path-based TOA estimation techniques shows that the number of MPCs is very sensitive to the threshold for picking paths and to the noise threshold. It generally decreases as the distance increase while larger bandwidth always resolves more MPCs. The multipath components behave more persistently in line of sight (LOS) and obstructed line of sight (OLOS) scenarios than in UDP scenarios, and the use of larger bandwidth and higher threshold for picking paths also result in more persistent paths

Cooperative Localization Bounds for Indoor Ultra-Wideband Wireless Sensor Networks

In recent years there has been growing interest in ad-hoc and wireless sensor networks (WSNs) for a variety of indoor applications. Localization information in these networks is an enabling technology and in some applications it is the main sought after parameter. the cooperative localization performance of WSNs is constrained by the behavior of the utilized ranging technology in dense cluttered indoor environments. Recently, ultra-wideband (UWB) Time-of-Arrival (TOA) based ranging has exhibited potential due to its large bandwidth and high time resolution. the performance of its ranging and cooperative localization capabilities in dense indoor multipath environments, however, needs to be further investigated. of main concern is the high probability of non-line of sight (NLOS) and Direct Path (DP) blockage between sensor nodes which biases the TOA estimation and degrades the localization performance. In this paper, based on empirical models of UWB TOA-based Outdoor-to-Indoor (OTI) and Indoor-to-Indoor (ITI) ranging, we derive and analyze cooperative localization bounds for WSNs in different indoor multipath environments: residential, manufacturing floor, old office and modern office buildings. First, we highlight the need for cooperative localization in indoor applications. Then we provide comprehensive analysis of the factors affecting localization accuracy such as network and ranging model parameters

Modeling of Time-of-arrival for CM4 Body Area Networks Channel

In Time-of-Arrival (TOA) based indoor human tracking system, the human body mounted with the target sensor can cause non-line-of-sight (NLOS) scenario and result in significant ranging error. In this thesis, we measured the TOA ranging error in a typical indoor environment and analyzed sources of inaccuracy in TOAbased indoor localization system. To quantitatively describe the TOA ranging error caused by human body, we introduce a statistical TOA ranging error model for body mounted sensors based on the measurement results. This model separates the ranging error into multipath error and NLOS error caused by the on-body creeping wave phenomenon. Both multipath error and NLOS error are modeled as a Gaussian variable. The distribution of multipath error is only relative to the bandwidth of the system while the distribution of NLOS error is relative to the angle between human facing direction and the direction of Transmitter-Receiver, signal to noise ratio (SNR) and bandwidth of the system, which clearly shows the effects of human body on TOA ranging. An efficient way to fight against the TOA ranging error caused by human body is to employ site-specific channel models by using ray-tracing technology. However, existing ray-tracing softwares lack the propagation model that takes the effects of human body into account. To address that issue, this thesis presents a empirical model for near human body ultra-wideband (UWB) propagation channel that is valid for the frequency range from 3GHz to 8GHz. It is based on measurements conducted in a anechoic chamber which can be regarded as free space. The empirical model shows the joint propagation characteristics of the on body channel and the channel between body surface and external access point. It includes the loss of the first path, arrival time of the first path and the total pathloss. Models for all three aspects have been partitioned into two sections by a break point due to the geometrical property of human body and the creeping wave phenomenon. The investigation on first path behavior can be regarded as a theoretical basis of raytracing technique that takes the effects of human body into consideration

Node Density and Quality of Estimation for Infrastructure-based Indoor Geolocation Using Time of Arrival

Infrastructure-based indoor geolocation systems utilizing a regular grid arrangement of sensors are being investigated for many applications in indoor wireless networks. One of the factors affecting the Quality of Estimation (i.e. location estimation accuracy) of these systems is node density. In this dissertation we study the effects of node density on indoor geolocation systems based on time of arrival (TOA). The effects of node density on the performance of various indoor communication networks (e.g. wireless LANs) in the presence of realistic indoor radio propagation models has been analyzed and reported in the literature. However, we have noted the lack of an equivalent analysis on the effects of node density on the performance of infrastructure-based indoor geolocation systems. The goal of this dissertation is to address this knowledge gap. Due to the complicated behavior of the indoor radio channel, the relationship between the node density and Quality of Estimation (QoE) is not straightforward. Specifically, QoE depends on factors such as the bandwidth used to make the TOA-based distance measurements, the existence of undetected direct path (UDP) conditions, and coverage. In this dissertation, we characterize these dependencies. We begin by characterizing the Quality of Estimation for closest-neighbor (CN), least-squares (LS) and weighted LS techniques in the presence of different node densities and a distance measurement error (DME) model based on ray tracing (RT) that was recently proposed in the literature. Then, we propose a new indoor geolocation algorithm, Closest Neighbor with TOA Grid (CN-TOAG), characterize its performance and show that it outperforms the existing techniques. We also propose an extension to this algorithm, known as Coverage Map Search (CMS) that allows it to be used in suboptimal coverage conditions (which we refer to as partial coverage conditions) that may prevent other TOA-based geolocation techniques from being used. We treat the partial coverage case by defining coverage probabilities and relating them to the average radius of coverage and dimensions of the indoor area. Next, we characterize the effects of node density on the performance of the CN-TOAG algorithm using a DME model based on UWB measurements, and show that node density and partial coverage are intimately linked together. Since this second DME model also allows for the effects of UDP conditions (which affect the quality of the link or QoL), we also characterize the effects of varying UDP conditions on the performance. Finally, we conclude the dissertation by presenting an analysis of fundamental performance bounds for infrastructure-based indoor geolocation, specifically focusing on the Cramer-Rao Lower Bound (CRLB)