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).

Currently there is a need to design, develop, and deploy autonomous and portable indoor geolocation systems to fulfil the needs of military, civilian, governmental and commercial customers where GPS and GLONASS signals are not available due to the limitations of both GPS and GLONASS signal structure designs. The goal of this dissertation is (1) to introduce geolocation systems; (2) to classify the state of the art geolocation systems; (3) to identify the issues with the state of the art indoor geolocation systems; and (4) to propose and assess four WPI indoor geolocation systems. It is assessed that the current GPS and GLONASS signal structures are inadequate to overcome two main design concerns; namely, (1) the near-far effect and (2) the multipath effect. We propose four WPI indoor geolocation systems as an alternative solution to near-far and multipath effects. The WPI indoor geolocation systems are (1) a DSSS/CDMA indoor geolocation system, (2) a DSSS/CDMA/FDMA indoor geolocation system, (3) a DSSS/OFDM/CDMA/FDMA indoor geolocation system, and (4) an OFDM/FDMA indoor geolocation system. Each system is researched, discussed, and analyzed based on its principle of operation, its transmitter, the indoor channel, and its receiver design and issues associated with obtaining an observable to achieve indoor navigation. Our assessment of these systems concludes the following. First, a DSSS/CDMA indoor geolocation system is inadequate to neither overcome the near-far effect not mitigate cross-channel interference due to the multipath. Second, a DSSS/CDMA/FDMA indoor geolocation system is a potential candidate for indoor positioning, with data rate up to 3.2 KBPS, pseudorange error, less than to 2 m and phase error less than 5 mm. Third, a DSSS/OFDM/CDMA/FDMA indoor geolocation system is a potential candidate to achieve similar or better navigation accuracy than a DSSS/CDMA indoor geolocation system and data rate up to 5 MBPS. Fourth, an OFDM/FDMA indoor geolocation system is another potential candidate with a totally different signal structure than the pervious three WPI indoor geolocation systems, but with similar pseudorange error performance.

Three main elements for an indoor positioning and navigation system design are the signal structure, the signal processing algorithm and the digital and RF prototype hardware. This thesis focuses on the design and development of RF prototype hardware. The signal structure being used in the precise positioning system discussed in this thesis is a Multicarrier-Ultra Wideband (MC-UWB) type signal structure. Unavailability of RF modules suitable for MC-UWB based systems, led to design and development of custom RF transmitter and receiver modules which can be used for extensive field testing. The lack of RF design guidelines for multicarrier positioning systems that operate over fractional bandwidth ranging from 10% to 25% makes the RF design challenging as the RF components are stressed using multicarrier signal in a way not anticipated by the designers. This thesis, first presents simulation based performance evaluation of impulse radio based and multicarrier based indoor positioning systems. This led to an important revelation that multicarrier based positioning system is preferred over impulse radio based positioning systems. Following this, ADS simulations for a direct upconversion transmitter and a direct downconversion receiver, using multicarrier signal structure is presented. The thesis will then discuss the design and performance of the 24% fractional bandwidth RF prototype transmitter and receiver custom modules. This optimized 24% fractional bandwidth RF design, under controlled testing environment demonstrates positioning accuracy improvement by 2-4 times over the initial 11% fractional bandwidth non-optimized RF design. The thesis will then present the results of various indoor wireless tests using the optimized RF prototype modules which led to better understanding of the issues in a field deployable indoor positioning system.

"Recently considerable attention has been paid to indoor geolocation using wireless local area networks (WLAN) and wireless personal area networks (WPAN) devices. As more applications using these technologies are emerging in the market, the need for accurate and reliable localization increases. In response to this need, a number of technologies and associated algorithms have been introduced in the literature. These algorithms resolve the location either by using estimated distances between a mobile station (MS) and at least three reference points (via triangulation) or pattern recognition through radio frequency (RF) fingerprinting. Since RF fingerprinting, which requires on site measurements is a time consuming process, it is ideal to replace this procedure with the results obtained from radio channel modeling techniques. Localization algorithms either use the received signal strength (RSS) or time of arrival (TOA) of the received signal as their localization metric. TOA based systems are sensitive to the available bandwidth, and also to the occurrence of undetected direct path (UDP) channel conditions, while RSS based systems are less sensitive to the bandwidth and more resilient to UDP conditions. Therefore, the comparative performance evaluation of different positioning systems is a multifaceted and challenging problem. This dissertation demonstrates the viability of radio channel modeling techniques to eliminate the costly fingerprinting process in pattern recognition algorithms by introducing novel ray tracing (RT) assisted RSS and TOA based algorithms. Two sets of empirical data obtained by radio channel measurements are used to create a baseline for comparative performance evaluation of localization algorithms. The first database is obtained by WiFi RSS measurements in the first floor of the Atwater Kent laboratory; an academic building on the campus of WPI; and the other by ultra wideband (UWB) channel measurements in the third floor of the same building. Using the results of measurement campaign, we specifically analyze the comparative behavior of TOA- and RSS-based indoor localization algorithms employing triangulation or pattern recognition with different bandwidths adopted in WLAN and WPAN systems. Finally, we introduce a new RT assisted hybrid RSS-TOA based algorithm which employs neural networks. The resulting algorithm demonstrates a superior performance compared to the conventional RSS and TOA based algorithms in wideband systems."

Time-Difference-of-Arrival (TDOA) location estimation is central to an OFDM based Precision Personnel Locator system being developed at WPI. Here we describe a component of the effort towards characterizing the performance of such a system and verifying the functionality of hardware and software implementations. The performance degradations due to noise in the received signal and misalignments between transmitter and receiver clock and heterodyne frequencies are investigated. This investigation involves development of a MATLAB simulator for the entire system, experimental measures using a prototype implementation and linearized analytic analysis of specific subsystems. The three types of characterizations are compared, confirming agreement, and analytic results are used to demonstrate construction of a system engineering design tool.

Thesis (M.S.) -- Worcester Polytechnic Institute. / Keywords: error propagation; indoor channel model; localization algorithm. Includes bibliographical references (p.137-142).

Recently, there are great interests in the location-based applications and the location-awareness of mobile wireless systems in indoor areas, which require accurate location estimation in indoor environments. The traditional geolocation systems such as the GPS are not designed for indoor applications, and cannot provide accurate location estimation in indoor environments. Therefore, there is a need for new location finding techniques and systems for indoor geolocation applications. In this thesis, a wide variety of technical aspects and challenging issues involved in the design and performance evaluation of indoor geolocation systems are presented first. Then the TOA estimation techniques are studied in details for use in indoor multipath channels, including the maximum-likelihood technique, the MUSIC super-resolution technique, and diversity techniques as well as various issues involved in the practical implementation. It is shown that due to the complexity of indoor radio propagation channels, dramatically large estimation errors may occur with the traditional techniques, and the super-resolution techniques can significantly improve the performance of the TOA estimation in indoor environments. Also, diversity techniques, especially the frequency-diversity with the CMDCS, can further improve the performance of the super-resolution techniques.

In spite of major research initiatives by DARPA and other research organizations, precise indoor geolocation still remains as a challenge facing the research community. The core of this challenge is to understand the cause of large ranging errors in estimating the time of arrival (TOA) of the direct path between the transmitter and the receiver. Results of wideband measurement in variety of indoor areas reveal that large ranging errors are caused by severe multipath conditions and frequent occurrence of undetected direct path (UDP) situations. Empirical models for the behavior of the ranging error, which we refer to as the distance measurement error (DME), its relation to the distance between the transmitter and the receiver and the bandwidth of the system is needed for development of localization algorithms for precise indoor geolocation. The main objective of this dissertation is to design a direct empirical model for the behavior of the DME. In order to achieve this objective we provide a framework for modeling of DME, which relates the error to the distance between the transmitter and the receiver and bandwidth of the system. Using this framework we first designed a set of preliminary models for the behavior of the DME based on the CWINS proprietary measurement calibrated ray-tracing simulation tool. Then, we collected a database of 2934 UWB channel impulse response measurements at 3-8GHz in four different buildings to incorporate a variety of building materials and architectures. This database was used for the design of more in depth and realistic models for the behavior of the DME. The DME is divided into two components, Multipath-DME (MDME) and UDP-DME (UDME). Based on the empirical data, models for the behavior of each of these components are developed. These models reflect the sensitivity to bandwidth and show that by increasing the bandwidth MDME decreases. However in UDME the behavior is complicated. At first it reduces as we increase the bandwidth but after a certain bandwidth it starts to increase. In addition to these models through an analysis on direct path power versus the total power the average probability of having a UDP was calculated.

Recently, there has been an enormous growth of interests in geolocation applications that demand an accurate estimation of the user’s location in indoor areas. The traditional geolocation system, GPS, which was designed for being used in outdoor environments, does not perform well in indoor areas, causing frequent inaccuracies in location estimation. Therefore the need for more accurate positioning systems and even positioning techniques is a motivation for researchers to turn their attention into indoor positioning systems. In this thesis we present a unique testbed for indoor geolocation system’s real-time performance evaluation. Then we present a real-time performance evaluation of a sample indoor positioning system. We make a comparison between the simulated results of the performance evaluation of the positioning engine and the real-time performance evaluation of the positioning system. Finally, we perform a sensitivity analysis for Ekahauâ„¢ indoor positioning engine. We show that the simulation with the introduced testbed yields the same results as one would obtain by evaluating the performance of the positioning system by means of massive measurement campaigns. Running the testbed for several measurement campaigns for different scenarios enabled us to compare the results and study the effect of selected parameters on the performance of the positioning system. We also perform primitive error analysis in terms of distance error to verify the validity of the result obtained with the testbed. We show that under the same configuration both real-time performance evaluation and simulated performance evaluation will yield same result with respect to position error. We also use error modeling to determine which error model is best matched to the observed indoor positioning error. Amongst all of the possibilities of choosing methods of positioning, we focused on the Received Signal Strength (RSS) based method along with fingerprinting. Briefly said, profiles previously gathered by measurement or simulation will decide on the location of mobile terminal if a new profile comes in. It is worth mentioning that previous work similar to this testbed has been done for outdoor areas according to Ekahau's white paper. Their work is mainly focused on outdoor environment, in which multipath does not exist. In this research effort we tried to analyze the effect of different parameters on sensitivity of indoor positioning systems who suffer from multipath. Different setups for simulating real-time radio channels have been studied in literature, but still not focused on indoor areas.

"A well-known challenge in estimating the distance of the antenna pair in time-of-arrival (ToA) based RF localization systems is the problem of obstruction of the direct path (DP) between transmitter and receiver. The absence of DP component in received channel profile creates undetected direct path (UDP) conditions. UDP condition, in turn, will cause occurrence of unexpected large ranging errors which pose serious challenge to precise indoor localization. Analysis of the behavior of the ranging error in such conditions is essential for the design of precise ToA-based indoor localization systems. This dissertation discusses two open problems in ToA-based indoor localization systems. The first contribution of this dissertation discusses the problem of modeling of dynamic behavior of ranging error. We propose a novel analytical framework for analysis of 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 Markov process. Parameters of distributions of ranging error in each Markov state are extracted from empirical data collected from a measurement-calibrated ray tracing algorithm simulating a typical office environment. The analytical derivation of parameters of the Markov model employs the existing path-loss models for 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. The second contribution of this dissertation discusses the problem of identification of UDP condition given an unknown channel profile. Existing of UDP condition in a channel profile poses serious degradation to ranging estimate process. Therefore, identification of occurrence of UDP condition is of our subsequent concern. After identification, the second step is to mitigate ranging errors in such conditions. In this dissertation we present two methodologies, based on binary hypothesis testing and an application of artificial neural network design, to identify UDP conditions and mitigate ranging error using statistics extracted from wideband frequency-domain indoor measurements conducted in typical office building. "