Navigation with Limited Prior Information Using Time Difference of Arrival Measurements from Signals of Opportunity

The Global Positioning System (GPS) provides world-wide availability to high-accuracy navigation and positioning information. However, the threats to GPS are increasing, and many limitations of GPS are being encountered. Simultaneously, systems previously considered as viable backups or supplements to GPS are being shut down. This creates the need for system alternatives. Navigation using signals of opportunity (SoOP) exploits any signal that is available in a given area, regardless of whether or not the original intent of the signal was for navigation. Common techniques to compute a position estimate using SoOP include received signal strength, angle of arrival, time of arrival, and time difference of arrival (TDOA). To estimate the position of a SoOP receiver, existing TDOA algorithms require one reference receiver and multiple transmitters, all with precisely known positions. This thesis considers modifications to an existing algorithm to produce a comparable position estimate without requiring precise a priori knowledge of the transmitters or reference receiver(s). Using Amplitude Modulation (AM) SoOP, the effect of erroneous a priori data on the existing algorithm are investigated. A proof-of-concept for three new estimation algorithms is presented in this research. Two of the estimators successfully demonstrate comparable performance to the existing algorithm. This is demonstrated in six different transmitter environments using four different receiver configurations

Wireless Localization in the Absence of GPS

In this thesis, wireless localization is investigated based on multiple noisy estimates of the time-difference of arrival (TDOA) at each pair of the n \u3e= 4 sensors with different but known locations using WiFi opportunistic signals. Our work is comprehensive and includes channel estimation, symbol detection, TDOA estimation, and location estimation. To mitigate the multipath issue induced by wideband signals, such as WiFi, frequency-division is employed to decompose the wideband RF signal into multiple non-overlapping narrowband signals. To minimize the adverse effects of the clock drift, time-division is proposed to divide the signal into multiple non-overlapping signals in the time domain. In addition, Kalman filtering is proposed, assuming the wide-sense stationary and uncorrelated scattering (WSSUS) channel and the first order auto-regressive (AR) model are used. Because of the multiple TDOA estimates at each pair of the WiFi receiver sensors, an efficient algorithm is developed to estimate the target location. The localization technique developed in this thesis can also be extended to other radio frequency (RF) signals, as shown in our simulation study for out-door localization. The simulation results in our thesis show the effectiveness of the wireless localization, although further work is needed to resolve the nonlinear estimation problem involved in localization based on TDOA estimates

TDoA Based Positioning using Ultrasound Signals and Wireless Nodes

In this paper, a positioning technique based on Time Difference of Arrival (TDoA) measurements is analyzed. The proposed approach is designed to consent range and position estimation, using ultrasound transmissions of a stream of chirp pulses, received by a set of wireless nodes. A potential source of inaccuracy introduced by lack of synchronization between transmitting node and receiving nodes is identified and characterized. An algorithm to identify and correct such inaccuracies is presented.Comment: Preprin

Hyperbolic position location estimator with TDOAs from four stations

This thesis presents a detailed derivation of a set of equations needed to locate the three dimensional position of a mobile given the locations of four fixed stations (like a global positioning system (GPS) satellite or a base station in a cell) and the signal time of arrival (TOA) from the mobile to each station. From these derived equations, a synthesizable VHDL model was developed and simulated using IEEE numen*c_std package. All the inputs and outputs were described by 32 bit vectors. From the simulations, it was observed that in the best case the mobile position was off by I meter and in the worst case the position was off by 36 meters. This model was synthesized with cadence tools and the total number of gates produced was 2.7 million

Distributed localisation algorithm for wireless ad hoc networks of moving nodes

Existing ad hoc network localisation solutions rely either on external location references or network-wide exchange of information and centralised processing and computation of location estimates. Without these, nodes are not able to estimate the relative locations of other nodes within their communication range. This thesis defines a new distributed localisation algorithm for ad hoc networks of moving nodes. The Relative Neighbour Localisation (RNL) algorithm works without any external localisation signal or systems and does not assume centralised information processing. The idea behind the location estimates produced by the RNL algorithm is the relationship between the relative locations of two nodes, their mobility parameters and the signal strengths measured between them. The proposed algorithm makes use of the data available to each node to produce a location estimate. The signal strength each node is capable of measuring is used as one algorithm input. The other input is the velocity vector of the neighbouring node, composed of its speed and direction of movement, which each node is assumed to periodically broadcast. The relationship between the signal strength and the mobility parameters on one, and the relative location on the other side can be analytically formulated in an ideal case. The limitations of a realistic scenario complicate this relationship, making it very difficult to formulate analytically. An empirical approach is thus used. The angle and the distance estimates are individually computed, together forming a two-dimensional location estimate. The performance of the algorithm was analysed in detail using simulation, showing a median estimate error of under 10m, and its application was tested through design and evaluation of a distributed sensing coverage algorithm, showing RNL location estimates can provide 90% of the coverage achievable with true locations being known

Smart Passive Localization Using Time Difference of Arrival

A smart passive localization system using time difference of arrival (TDoA) measurements is designed and analyzed with the goal of providing the position information for the construction of frequency allocation maps

Passive Geolocation of Low Power Emitters in Urban Environments using TDOA

Low-power devices are commonly used by the enemy to control Improvised Explosive Devices (IEDs), and as communications nodes for command and control. Quickly locating the source of these signals is difficult, especially in an urban environment where buildings and towers can cause interference. This research presents a geolocation system that combines several geolocation and error mitigation methods to locate an emitter in an urban environment. The proposed geolocation system uses a Time Difference of Arrival (TDOA) technique to estimate the location of the emitter of interest. Using sensors at known locations, TDOA estimates are obtained by cross-correlating the signal received at all the sensors. A Weighted Least Squares (WLS) solution is used to estimate the emitter\u27s location. If the variance of the location estimate is too high, a sensor is detected as having a Non-Line of Sight (NLOS) path from the emitter, and is removed from the geolocation system and a new position estimate is calculated with the remaining sensor TDOA information. The performance of the system is assessed through modeling and simulations. The test results confirm the feasibility of identifying a NLOS sensor, thereby improving the geolocation system\u27s accuracy in an urban environment

Algorithms for propagation-aware underwater ranging and localization

Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of the crucial research problems of modern time. Underwater localization stands among the key issues on the way to the proper inspection and monitoring of this significant part of our world. In this thesis, we investigate and tackle different challenges related to underwater ranging and localization. In particular, we focus on algorithms that consider underwater acoustic channel properties. This group of algorithms utilizes additional information about the environment and its impact on acoustic signal propagation, in order to improve the accuracy of location estimates, or to achieve a reduced complexity, or a reduced amount of resources (e.g., anchor nodes) compared to traditional algorithms. First, we tackle the problem of passive range estimation using the differences in the times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand energy- effective algorithm that can be used for the localization of autonomous underwater vehicles (AUVs), and utilizes information about signal propagation. We study the accuracy of this method in the simplified case of constant sound speed profile (SSP) and compare it to a more realistic case with various non-constant SSP. We also propose an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic propagation via ray models, takes into account the difference between rectilinear and non-rectilinear sound ray paths. According to our evaluation, this offers improved range estimation results with respect to standard algorithms that consider the actual value of the speed of sound. We then propose an algorithm suitable for the non-invasive tracking of AUVs or vocalizing marine animals, using only a single receiver. This algorithm evaluates the underwater acoustic channel impulse response differences induced by a diverse sea bottom profile, and proposes a computationally- and energy-efficient solution for passive localization. Finally, we propose another algorithm to solve the issue of 3D acoustic localization and tracking of marine fauna. To reach the expected degree of accuracy, more sensors are often required than are available in typical commercial off-the-shelf (COTS) phased arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We propose a solution for passive 3D localization and tracking using a wideband acoustic array of arbitrary shape, and validate the algorithm in multiple experiments, involving both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell