Large enterprises are often interested in tracking objects and people within buildings to improve resource allocation and occupant experience. Infrastructure-based indoor positioning systems (IIPS) can provide this service at low-cost by leveraging already deployed Wi-Fi infrastructure. Typically, IIPS perform localization and tracking of devices by measuring only Wi-Fi signals at wireless access points and do not rely on inertial sensor data at mobile devices (e.g., smartphones), which would require explicit user consent and sensing capabilities of the devices. Despite these advantages, building an economically viable cost-effective IIPS that can accurately and simultaneously track many devices over very large buildings is difficult due to three main challenges. First, Wi-Fi signal measurements are extremely noisy due to unpredictable multipath propagation and signal attenuation. Second, as the IIPS obtain measurements in a best effort manner without requiring any applications installed on a tracked device, the measurements are temporally sparse and non-periodic, which makes it difficult to exploit historical measurements. Third, the cost-effective IIPS have limited computational resources, in turn limiting scalability in terms of the number of simultaneously tracked devices. Prior approaches have narrowly focused on either improving the accuracy or reducing the complexity of localization algorithms. To compute the location at the current time step, they typically use only the latest explicit Wi-Fi measurements (e.g., signal strengths). The novelty of our approach lies in considering contexts of a device that can provide useful indications of the device's location. One such example of context is device motion. It indicates whether or not the device's location has changed. For a stationary device, the IIPS can either skip expensive device localization or aggregate noisy, temporally sparse location estimates to improve localization accuracy. Another example of context applicable to a moving device is a floor map that consists of pre-defined path segments that a user can take. The map can be leveraged to constrain noisy, temporally sparse location estimates on the paths. The thesis of this dissertation is that embedding context-aware capabilities in the IIPS enhances its performance in tracking many devices simultaneously and accurately. Specifically, we develop motion detection and map matching to show the benefits of leveraging two critical contexts: device motion and floor map. Providing motion detection and map matching is non-trivial in the IIPS where we must rely only on data from the Wi-Fi infrastructure. This thesis makes two contributions. First, we develop feature-based and deep learning-based motion detection models that exploit temporal patterns in Wi-Fi measurements across different access points to classify device motion in real time. Our extensive evaluations on datasets from real Wi-Fi deployments show that our motion detection models can detect device motion accurately. This, in turn, allows the IIPS to skip repeated location computation for stationary devices or improve the accuracy of localizing these devices. Second, we develop graph-based and image-based map matching models to exploit floor maps. The novelty of the graph-based approach lies in applying geometric and topological constraints to select which path segment to align the current location estimate. Our graph-based map matching can align a location estimate of a user device on the path taken by the user and close to the user's current location. The novelty of the image-based approach lies in representing for the first time, input data including location estimates and the floor map as 2D images. This novel representation enables the design, development, and application of encoder-decoder neural networks to exploit spatial relationships in input images to potentially improve location accuracy. In our evaluation, we show that the image-based approach can improve location accuracy with large simulated datasets, compared to the graph-based approach. Together, these contributions enable improvement of the IIPS in its ability to accurately and simultaneously track many devices over large buildings.

The effectiveness of location aware applications is dependent on the accuracy of the supporting positioning system. This work evaluates the accuracy of an indoors 802.11 positioning system based on signal strength fingerprinting. The system relies on an empirical survey of signal strength prior to positioning. During this survey, signal strength recordings are made at a set of positions across the environment. These recordings are used as training data for the system during positioning. In this thesis, two surveying methods, five positioning algorithms, and two spatial output averaging methods are trialled. Accuracy is determined by empirical testing in two separate environments: a 100m square domestic house and the 1,333m square third floor of the University of New South Wales Computer Science and Engineering building. In the two environments, the lowest mean distance errors are 1.25m and 2.86m respectively.

Specialists are expecting the knowledge of location will trigger yet another revolution in mobile services. Location-base services (LBS) have attracted many researchers and enterprises and one of the key aspects of LBS is positioning technology. Considering a wider and more complex field - ubiquitous computing, location is the fundamental element. This work focuses on some aspects of the new techniques of terrestrial positioning systems. Wireless LAN is one of the most popular systems used for positioning for indoor environments and public places. We have investigated the trilateration and fingerprinting approaches and the results showed the advantages of fingerprinting. A novel method to generate the fingerprints database based on Universal Kriging (UK) was developed, which can not only significantly decrease the training time, but also increase the accuracy of estimates. In mobile phone positioning systems, most techniques suffer from the non-line-of-sight (NLOS) propagation. We investigated the specifics of NLOS error, and proposed a method to mitigate the errors. Furthermore, a new algorithm named WSMM (wireless signal map matching) was discussed. Simulations and experiments verified the idea, and the accuracy of positioning can be improved greatly. Since fingerprinting technique can utilize rather than suffer from the NLOS propagation, it was also applied in mobile phone positioning system. Experiments showed both the deterministic approach and probabilistic approach can provide better results comparing with other techniques in suburban area. To achieve a robust positioning system and provide more useful information of the user, multisensor combination and data fusion are necessary. As the first step of future research, a mulitsensor synchronization system was developed. This system can promisingly achieve synchronization with error less than 0.4 ms, which is suitable for most land applications. Hence the main findings of this thesis are: (1) a novel method of yielding fingerprint database for both wireless LAN (WLAN) and mobile phone systems when using the fingerprinting technique for positioning; (2) a database method to mitigate NLOS error for mobile phone positioning systems; (3) a low cost synchronization system for integration of multiple sensors.

Ground deformation due to volcanic magma intrusion is recognised as an important precursor of eruptive activity at a volcano. The Global Positioning System (GPS) is ideally suited for this application by being able to measure three-dimensional coordinate changes of the monitoring points over time. Due to the highly disturbed ionosphere in equatorial regions, particularly during times of maximum solar activity, a deformation monitoring network consisting entirely of single-frequency GPS receivers cannot deliver baseline solutions at the desired accuracy level. In this thesis, a mixed-mode GPS network approach is proposed in order to optimise the existing continuous single-frequency deformation monitoring system on the Papandayan volcano in West Java, Indonesia. A sparse network of dual-frequency GPS receivers surrounding the deformation zone is used to generate empirical 'correction terms' in order to model the regional ionosphere. These corrections are then applied to the single-frequency data of the inner network to improve the accuracy of the results by modelling the residual atmospheric biases that would otherwise be neglected. This thesis reviews the characteristics of existing continuously operating GPS deformation monitoring networks. The UNSW-designed mixed-mode GPS-based volcano deformation monitoring system and the adopted data processing strategy are described, and details of the system's deployment in an inhospitable volcanic environment are given. A method to optimise the number of observations for deformation monitoring networks where the deforming body itself blocks out part of the sky, and thereby significantly reduces the number of GPS satellites being tracked, is presented. The ionosphere and its effects on GPS signals, with special consideration for the situation in equatorial regions, are characterised. The nature of the empirically-derived 'correction terms' is investigated by using several data sets collected over different baseline lengths, at various geographical locations, and under different ionospheric conditions. Data from a range of GPS networks of various sizes, located at different geomagnetic latitudes, including data collected on Gunung Papandayan, were processed to test the feasibility of the proposed mixed-mode deformation monitoring network approach. It was found that GPS baseline results can be improved by up to 50% in the midlatitude region when the 'correction terms' are applied, although the performance of the system degrades in close proximity to the geomagnetic equator during a solar maximum.

The measurements from eighteen GPS (Global Positioning System) surveys and four terrestrial surveys were used to calculate the velocities of 406 survey stations throughout the South Island, Stewart Island and the southernmost North Island. Repeated GPS measurements are available at 350 stations. The calculation of the velocities for the remaining stations is made possible through the use of terrestrial measurements. The velocity was modelled under the assumption that the displacements of the stations are either linear with time or linear punctuated by discontinuities. The discontinuous model was used to estimate the coseismic displacements of stations in the vicinity of the 1994 Arthur�s Pass earthquake (M 6.7). The maximum station displacement was estimated to be ca. 40 cm, and significant displacements are seen to a range of ca. 70 km from the earthquake epicentre. Station displacements were also calculated for two later earthquakes in the vicinity of the Arthur�s Pass earthquake, but it was not possible to separate these from the postseismic displacements due to the earlier earthquake. A continuous velocity field was estimated from the discrete station velocity measurements through a stochastic model based on the concept of minimum curvature. The selection of the basic stochastic model was effectively arbitrary; however, the model was refined to better suit the velocity field in the South Island. This was achieved through estimating the correlation between the velocity components (east and north) and the anisotropy of the velocity field. The stochastic model has the advantage over other models (e.g. polynomials or splines) in that only the probable shape of the velocity field is assumed. Therefore, the shape of the velocity field is not restricted by a priori model assumptions. The measurement of the differential velocity across the South Island plate boundary between Christchurch and Cape Farewell is less than 85% of the interplate velocity calculated from NUVEL-1A. One possibility is that the NUVEL-1A model may not be an accurate representation of the motion at this plate boundary. Alternatively, deformation (occurring during the period of survey measurements) may extend a total distance of 150 km or more (assuming that the spatial velocity differential is less than 5x10⁻⁷/year) offshore from Christchurch and Cape Farewell. In the southern South Island there is evidence for as much as 22 mm/year of east directed motion being accommodated between Fiordland�s west coast and the stable interior of the Australian Plate. An accretionary wedge has been imaged west of Fiordland (Davey and Smith, 1983; Delteil et al., 1996); therefore, some of this deformation may be related to slip on the subduction interface. The shear strain rates are clearly influenced by the dominant fault elements in the South Island, i.e. the southern and central Alpine Fault, and the eastern Hope Fault. The maximum measured shear strain rate in the South Island, 6(±1) x10⁻⁷/year, occurs adjacent to the Alpine Fault at (1 70.5°E, 43.3°S), ca. 40 km northeast of Mt Cook, and is coincident with a local dilatational strain rate minimum, -7 (±4.5) x 10⁻⁸/year. This is the only location where the measured strain rate is compatible with strike-slip and dip-slip motion on the Alpine Fault. Shear strain rates decrease eastwards along the Hope Fault: from 5(±0.7) x10⁻⁷/year at the Alpine Fault, to 3(±0.8) x10⁻⁷/year close to the Jordan Thrust. The zone of deformation broadens with a concomitant decrease in shear strain rate, such that within the northeast South Island there is no distinct maximum over any particular fault. A band of contraction and shear has been imaged at a distance of 100 km southeast of, and parallel to, the Alpine Fault. The deformation at this location may be related to a frontal thrust zone similar to that described in the two-sided wedge models. The band of deformation continues north of Christchurch, intersecting the Porters Pass Fault Zone. Significant contraction rates are seen in the measurements from four other zones. The first of these is situated towards the northeast (on land) ends of the Clarence, Awatere and Hope Faults. Some of this signal is presumably related to the uplift of the Seaward and Inland Kaikoura Ranges. The three remaining zones of significant negative dilatational strain rate are located north of the Wairau Fault, close to Jackson Bay and within central Otago. A zone of significant shear strain rate is measured along the eastern side of, and within southern Fiordland. The deformation measurements probably partially reflect the existence of an important fault running through Lake Te Anau, which accommodates the motion of the Fiordland block relative to the Pacific Plate. The remainder may be due to internal deformation of the Fiordland block. A new velocity differential measurement has been introduced, the rotational excess. This function of the shear strain rate, vorticity and dilatational strain rate should be sensitive to tectonic rotation (as measured by paleomagnetic data). Point estimates of the rotational excess are insignificant throughout the South Island. Also, there are no easily defined regions in which spatially averaged measurements are significant. If the rotational excess is assumed to be a direct measurement of tectonic rotation then the measurements place a bound on the size of the region and the rate at which it rotates. For example, the rate of tectonic rotation within a square region with side lengths of 50 km located adjacent to Cape Campbell is unlikely to be greater than 4°/Ma. However, greater tectonic rotation rates are possible within smaller regions.

The Global Positioning System (GPS) has been widely used for precise positioning applications throughout the world. However, there are still some limiting factors that affect the performance of satellite-based positioning techniques, including the ionosphere. The GPS Network-RTK (NRTK) concept has been developed in an attempt to remove the ionospheric bias from user observations within the network. This technique involves the establishment of a series of GNSS reference stations, spread over a wide geographical region. Real time data from each reference station is collected and transferred to a computing facility where the various spatial and temporal errors affecting the GNSS satellite observations are estimated. These corrections are then transmitted to users observations in the field. As part of a Victorian state government initiative to implement a cm-level real time positioning service state-wide, GPSnet is undergoing extensive infrastructure upgrades to meet high user demand. Due to the sparse (+100km) configuration of GPSnet's reference stations, the precise modelling of Victoria's ionosphere will play a key role in providing this service. This thesis aims is to develop a temporal model for the ionospheric bias within a Victorian NRTK scenario. This research has analysed the temporal variability of the ionosphere over Victoria. It is important to quantify the variability of the ionosphere as it is essential that NRTK corrections are delivered sufficiently often with a small enough latency so that they adequately model variations in the ionospheric bias. This will promote the efficient transmission of correctional data to the rover whilst still achieving cm-level accuracy. Temporal analysis of the ionosphere revealed that, during stable ionospheric conditions, Victoria's double differenced ionospheric (DDI) bias remains correlated to within +5cm out to approximately two minutes over baselines of approximately 100km. However, the data revealed that during more disturbed ionospheric conditions this may decrease to one minute. As a preliminary investigation, four global empirical ionospheric models were tested to assess their ability to estimate the DDI bias. Further, three temporal predictive modelling schemes were tested to assess their suitability for providing ionospheric corrections in a NRTK environment. The analysis took place over four seasonal periods during the previous solar maximum in 2001 and 2002. It was found that due to the global nature of their coefficients, the four global empirical models were unable to provide ionospheric corrections to a level sufficient for precise ambiguity resolution within a NRTK environment. Three temporal ionospheric predictive schemes were developed and tested. These included a moving average model, a linear model and an ARIMA (Auto-Regressive Integrated Moving Average) time series analysis. The moving average and ARIMA approaches gave similar performance and out-performed the linear modelling scheme. Both of these approaches were able to predict the DDI to +5cm within a 99% confidence interval, out to an average of approximately two minutes, on average 90% of the time when compared to the actual decorrelation rates of the ionosphere. These results suggest that the moving average scheme, could enhance the implementation of next generation NRTK systems by predicting the DDI bias to latencies that would enable cm-level positioning.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 197-204).

Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains xi, 232 p. : ill. (some col.), col. maps. Includes abstract. Includes bibliographical references (p. 193-195).

No description available.

Thesis (M.S.) University of Delaware, 2006. / Principal faculty advisor: Frederick E. Nelson, Dept. of Geography. Includes bibliographical references.