Average performance analysis of circular and hyperbolic geolocation

A comparative performance analysis of four geolocation methods in terms of their theoretical root mean square positioning errors is provided. Comparison is established in two different ways: strict and average. In the strict type, methods are examined for a particular geometric configuration of base stations(BSs) with respect to mobile position, which determines a given noise profile affecting the respective time-of-arrival (TOA) or timedifference- of-arrival (TDOA) estimates. In the average type, methods are evaluated in terms of the expected covariance matrix of the position error over an ensemble of random geometries, so that comparison is geometry independent. Exact semianalytical equations and associated lower bounds (depending solely on the noise profile) are obtained for the average covariance matrix of the position error in terms of the so-called information matrix specific to each geolocation method. Statistical channel models inferred from field trials are used to define realistic prior probabilities for the random geometries. A final evaluation provides extensive results relating the expected position error to channel model parameters and the number of base stations.Peer Reviewe

Performance Evaluation of Hyperbolic Position Location Technique in Cellular Wireless Networks

This study addresses the wireless geolocation problem that has been an attractive subject for the last few years after Federal Communications Commission (FCC) mandate for wireless service providers to locate emergency 911 users with a high degree of accuracy -within a radius of 125 meters, 67 percent of the time by October 2001. There are a number of different geolocation technologies that have been proposed. These include, Assisted GPS (A-GPS), network-based technologies such as Enhanced Observed Time Difference (E-OTD), Time Difference of Arrival (TDOA), Angle of Arrival (AOA), and Cell of Origin (COO). This research focuses on network based techniques, namely the more prominent TDOA which is also called hyperbolic position location technique. The main problem in time-based positioning systems is solving nonlinear hyperbolic equations derived from set of TDOA estimates. Two algorithms are implemented as a solution to this problem: A closed form solution and a Least Squares (LS) algorithm. Accuracy and computational efficiency performances are compared in a wireless system established using DGPS measurements in Dayton, OH area

Analysis of Geolocation Approaches Using Satellites

A space based system capable of geolocating radio frequency signals of interest has wide reaching application to the Air Force. This system would provide increased situational awareness to the warfighter on the battlefield. The Air Force Institute of technology is developing a satellite to conduct research on geolocation using CubeSats. A methodology to evaluate space based geolocation systems by varying orbital altitude and transmitter position for a given geolocation algorithm and satellite configuration was developed. This method allows multiple satellite configurations and geolocation algorithms to be compared during the design process of a space based geolocation system. The method provides a tool to facilitate decision making on the configuration design and geolocation methods chosen for a given system design. This research explains the geolocation methods and provides comparisons for one through four satellite configurations for time difference of arrival and angle of arrival geolocation algorithms

Techniques for Communication and Geolocation using Wireless Ad hoc Networks

Networks with hundreds of ad hoc nodes equipped with communication and position finding abilities are conceivable with recent advancements in technology. Methods are presented in this thesis to assess the communicative capabilities and node position estimation of mobile ad hoc networks. Specifically, we investigate techniques for providing communication and geolocation with specific characteristics in wireless ad hoc networks. The material presented in this thesis, communication and geolocation, may initially seem a collection of disconnected topics related only distantly under the banner of ad hoc networks. However, systems currently in development combining these techniques into single integrated systems. In this thesis first, we investigate the effect of multilayer interaction, including fading and path loss, on ad hoc routing protocol performance, and present a procedure for deploying an ad hoc network based on extensive simulations. Our first goal is to test the routing protocols with parameters that can be used to characterize the environment in which they might be deployed. Second, we analyze the location discovery problem in ad hoc networks and propose a fully distributed, infrastructure-free positioning algorithm that does not rely on the Global Positioning System (GPS). The algorithm uses the approximate distances between the nodes to build a relative coordinate system in which the node positions are computed in three-dimensions. However, in reconstructing three-dimensional positions from approximate distances, we need to consider error threshold, graph connectivity, and graph rigidity. We also statistically evaluate the location discovery procedure with respect to a number of parameters, such as error propagation and the relative positions of the nodes

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

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)

Low Cost, Low Complexity Sensor Design for Non-Cooperative Geolocation via Received Signal Strength

Obtaining accurate non-cooperative geolocation is vital for persistent surveillance of a hostile emitter. Current research for developing a small, cheap and energy efficient sensor network for non-cooperative geolocation measurements via received signal strength (RSS) is limited. Most existing work focuses on simulating a non-cooperative network (NN) and in doing so, simulated models often ignore localization errors caused from the hardware processing raw RSS data and often model environment-dependent errors as random. By comparing real-time measured non-cooperative geolocation data to a simulated system a more accurate model can be developed. This thesis discusses the development and performance of a small, low cost, low complexity, and energy efficient sensor network that can locate a NN via RSS. The main focus of this research effort is designing a Poor Man\u27s Spectrum Analyzer (PMSA) to locate a wireless device in a non-cooperative network (NN) that is transmitting in the Industrial, Scientific and Medical (ISM) radio band of 2.403 GHz to 2.48 GHz by measuring the emitter\u27s received signal strength (RSS)

Enhanced Precision Geolocation in 4G Wire-less Networks

The objective of this thesis is to improve the performance of geolocation schema though estimating the speed of light via the refractive index of air, estimating the target velocity, and exercising receiver choice. A method for incorporating the speed of light into geolocation models is proposed in this thesis. A generic receiver choice algorithm is proposed with application to time-of-arrival, time-difference-of-arrival, and Doppler velocity estimation schemes. An object-oriented MATLAB package was developed to describe the environment, network, target behavior, simulate data, and conduct simulation study. Simulation results show that using an incorrect estimate of propagation velocity, when timing information is sufficiently precise, can yield position estimates that are, on average, significantly less accurate and less precise. Further, simulation results show that inclusion of choice enables large improvements in both the average error and the dispersion of the errors.http://archive.org/details/enhancedprecisio1094532867Lieutenant, United States NavyApproved for public release; distribution is unlimited

Non-Linear Optimization Applied to Angle-of-Arrival Satellite-Based Geolocation with Correlated Measurements

A common remote sensing application is producing geolocation estimates for an object of interest from multiple sensor platforms. Geolocation estimates are desired to help improve situational awareness when dealing with space objects that do not actively broadcast their location. A depiction of the error parameters are calculated in conjunction with the positional estimates. Problems occur when multiple measurements from a single sensor are used to estimate a location due to correlations in sensor error. A non-linear optimization approach is presented for determining geolocation estimates and their associated error parameters. The error parameters directly reflect the error present on the individual measurements used to produce the position estimates. Correlations in errors are dealt with by augmenting the non-linear optimization with a covariance intersection algorithm. Finally, the ability to account for correlated errors within the optimization algorithm is analyzed using Monte-Carlo simulations. The ability to describe an objects location with a given confidence helps aid in the analysis of the system at large