Survey on the Performance of Source Localization Algorithms

The localization of emitters using an array of sensors or antennas is a prevalent issue approached in several applications. There exist different techniques for source localization, which can be classified into multilateration, received signal strength (RSS) and proximity methods. The performance of multilateration techniques relies on measured time variables: the time of flight (ToF) of the emission from the emitter to the sensor, the time differences of arrival (TDoA) of the emission between sensors and the pseudo-time of flight (pToF) of the emission to the sensors. The multilateration algorithms presented and compared in this paper can be classified as iterative and non-iterative methods. Both standard least squares (SLS) and hyperbolic least squares (HLS) are iterative and based on the Newton&-Raphson technique to solve the non-linear equation system. The metaheuristic technique particle swarm optimization (PSO) used for source localisation is also studied. This optimization technique estimates the source position as the optimum of an objective function based on HLS and is also iterative in nature. Three non-iterative algorithms, namely the hyperbolic positioning algorithms (HPA), the maximum likelihood estimator (MLE) and Bancroft algorithm, are also presented. A non-iterative combined algorithm, MLE-HLS, based on MLE and HLS, is further proposed in this paper. The performance of all algorithms is analysed and compared in terms of accuracy in the localization of the position of the emitter and in terms of computational time. The analysis is also undertaken with three different sensor layouts since the positions of the sensors affect the localization; several source positions are also evaluated to make the comparison more robust. The analysis is carried out using theoretical time differences, as well as including errors due to the effect of digital sampling of the time variables.Simulations were undertaken at the Universidad Carlos III of Madrid and at the University of Strathclyde, Glasgow. The work undertaken in this paper has been funded by the Spanish Government under Contract DPI2015-66478-C2-1(MINECO/FEDER, UE) 2016–2018

Classification and localization of electromagnetic and ultrasonic pulsed emitters

Mención Internacional en el título de doctorThe localization of radiative sources is very important in many fields of work such as: sonar, radar and underwater radar, indoor localization in wireless networks, earthquake epicenter localization, defective assets localization in electrical facilities and so forth. In the process of locating radiative sources exist many issues which can provoke errors in the localization. The signals acquired may belong to different sources or they can be mixed with environmental noise, then, their separation before using localization algorithms is of great interest to be efficient and accurate in the computational process. Furthermore, the geometry and radiation characteristics of the receivers, the nature of the signal or their measuring process may cause deviations in the signal onset calculus and therefore the source localization could be displaced from the actual position. In this thesis, there are three kinds of algorithms to undertake three steps in the emitter localization: signal separation, onset and time delay estimation of the signals and source localization. For each step, in order to reduce the error in the localization, several algorithms are analyzed and compared in each application, to choose the most reliable. As the first step, to separate different kinds of signals is of interest to facilitate further processing. In this thesis, different optimization techniques are presented over the power ratio (PR) maps method. The PR uses a selective spectral signal characterization to extract the features of the analyzed signals. The technique identifies automatically the most representative frequency bands which report a great separation of the different kinds of signals in the PR map. After separating and selecting the signals, it is of interest to compare the algorithms to calculate the onset and time delay of the pulsed signals to know their performance because the time variables are inputs to the most common triangulation algorithms to locate radiative and ultrasonic sources. An overview of the algorithms used to estimate the time of flight (ToF) and time differences of arrival (TDoA) of pulsed signals is done in this thesis. In the comparison, there is also a new algorithm based on statics of high order, which is proposed in this thesis. The survey of their performance is done applied to muscle deep estimation, localization in one dimension (1D), and for the localization of emitters in three dimensions (3D). The results show how the presented algorithm yields great results. As the last step in the radiative source localization, the formulation and principle of work of both iterative and non-iterative triangulation algorithms are presented. A new algorithm is presented as a combination of two already existing improving their performance when working alone. All the algorithms, the proposed and the previous which already exist, are compared in terms of accuracy and computational time. The proposed algorithm reports good results in terms of accuracy and it is one of the fastest in computational time. Once the localization is achieved, it is of great interest to understand how the errors in the determination of the onset of the signals are propagated in the emitter localization. The triangulation algorithms estimate the radiative source position using time variables as inputs: ToF, TDoA or pseudo time of flight (pToF) and the receiver positions. The propagation of the errors in the time variables to the radiative source localization is done in two dimensions (2D) and 3D. New spherical diagrams have been created to represent the directions where the localization is more or less sensible to the errors. This study and their sphere diagrams are presented for several antenna layouts. Finally, how the errors in the positioning of the receivers are propagated to the emitter localization is analyzed. In this study, the effect in the propagation of both the relative distance from the receivers to the emitter and the direction between them has been characterized. The propagation of the error considering the direction is also represented in spherical diagrams. For a preferred direction identified in the spheres, the propagated error in the source localization has been quantified regarding both the source distance and the magnitude of the errors in the receivers positioning.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Andrea Cavallini.- Secretario: José Antonio García Souto.- Vocal: Iliana Portugués Peter

Investigations of 5G localization with positioning reference signals

TDOA is an user-assisted or network-assisted technique, in which the user equipment calculates the time of arrival of precise positioning reference signals conveyed by mobile base stations and provides information about the measured time of arrival estimates in the direction of the position server. Using multilateration grounded on the TDOA measurements of the PRS received from at least three base stations and known location of these base stations, the location server determines the position of the user equipment. Different types of factors are responsible for the positioning accuracy in TDOA method, such as the sample rate, the bandwidth, network deployment, the properties of PRS, signal propagation condition, etc. About 50 meters positioning is good for the 4G/LTE users, whereas 5G requires an accuracy less than a meter for outdoor and indoor users. Noteworthy improvements in positioning accuracy can be achievable with the help of redesigning the PRS in 5G technology. The accuracy for the localization has been studied for different sampling rates along with different algorithms. High accuracy TDOA with 5G positioning reference signal (PRS) for sample rate and bandwidth hasn’t been taken into consideration yet. The key goal of the thesis is to compare and assess the impact of different sampling rates and different bandwidths of PRS on the 5G positioning accuracy. By performing analysis with variable bandwidths of PRS in resource blocks and comparing all the analyses with different bandwidths of PRS in resource blocks, it is undeniable that there is a meaningful decrease in the RMSE and significant growth in the SNR. The higher bandwidth of PRS in resource blocks brings higher SNR while the RMSE of positioning errors also decreases with higher bandwidth. Also, the number of PRS in resource blocks provides lower SNR with higher RMSE values. The analysis with different bandwidths of PRS in resource blocks reveals keeping the RMSE value lower than a meter each time with different statistics is a positivity of the research. The positioning accuracy also analyzed with different sample sizes. With an increased sample size, a decrease in the root mean square error and a crucial increase in the SNR was observed. From this thesis investigation, it is inevitable to accomplish that two different analyses (sample size and bandwidth) done in a different way with the targeted output. A bandwidth of 38.4 MHz and sample size N = 700 required to achieve below 1m accuracy with SNR of 47.04 dB

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Performance analysis and enhancements for the music sub-space direction-finding algorithm in the presence of wideband signals

Includes supplementary materialThe collection of signals intelligence via passive direction finding and geolocation of radio frequency signals is of great concern to the military for its contribution to the development of battlespace awareness. Basic subspace direction finding techniques provide a method of determining the direction-of-arrival (DOA) of multiple signals on an array of receivers, but they have an inherent limitation in that they are narrowband by design. The impact of various signal frequencies, bandwidths, and signal to noise ratios present in the source signals received by a sparse array using the multiple signals classification (MUSIC) subspace direction-finding algorithm are evaluated in this thesis. Additionally, two performance enhancements are presented: one that reduces the MUSIC computational load and one that provides a method of utilizing collector motion to resolve DOA ambiguities.http://archive.org/details/performancenalys1094544676Lieutenant Commander, United States NavyApproved for public release; distribution is unlimited

Source localization within a uniform circular sensor array

Traditional source localization problems have been considered with linear and planar antenna arrays. In this research work, we assume that the sources are located within a uniformly spaced circular sensor array. Using a modified Metropolis algorithm and Polak-Ribière conjugate gradients, a hybrid optimization algorithm is proposed to localize sources within a two dimensional uniform circular sensor array, which suffers from far field attenuation. The developed algorithm is capable of accurately locating the position of a single, stationary source within 1% of a wavelength and 1° of angular displacement. In the single stationary source case, the simulated Cramer-Rao Lower Bound has also shown low noise susceptibility for a reasonable signal to noise ratio. Additionally, the localization of multiple stationary sources within the array is presented and tracking capabilities for a slowly moving non-stationary source is also demonstrated. In each case, results are presented, analyzed and discussed. Furthermore, the proposed algorithm has also been validated through hardware experimentation. The design and construction of four microstrip patch antennas and a wire antenna have been completed to emulate a circular sensor array and the enclosed source, respectively. Within this array, data has been collected at the four sensors from several fixed source positions and fitted into the proposed algorithm for source localization. The convergence of the algorithm with both simulated data and data collected from hardware are compared and sources of error and potential improvements are proposed

Métodos de reconstrucción en dominio temporal para tomografía por transmisión de ultrasonidos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Física Atómica, Molecular y Nuclear, leída el 06-06-2017Breast cancer (BC) is the leading cause of cancer-related death for women in Europe, and the second one after lung cancer in the US [World Cancer Report, 2008]. Early detection is very important for the survival rate of BC, because the smaller the local extension of the neoplasia, the better the output of the surgical treatments employed. Besides, early detection increases the possibility of preserving the breast and decreases the probability of needing more invasive treatments [Secretaría de Salud, 2007, Alteri et al., 2011]. Mammography is currently the standard procedure employed for breast screening programs around the world. Nevertheless, its efficiency has been questioned lately because: (i) it generates many abnormal findings not related to cancer, (ii) it requires irradiating the patient and (iii) it has low specificity with dense breasts [Santen and Mansel, 2005]. Consequently, complementary techniques to mammography are being proposed to improve the detection and characterization of BC. Among these techniques, is the Ultrasound Computed Tomography (USCT), in reflection mode (which provides qualitative maps with the concentration of scatterers in the tissue), and transmission mode (which provides quantitative maps of the sound speed (SS) and the acoustic attenuation (AA) of the tissues). The images provided by the transmission modality have been proposed for BC detection as they can improve the detectability of malignancies in the breast [Mast, 2000, Duric et al., 2009]...El cáncer de mama (CM) es el cáncer más mortal entre las mujeres europeas, y el segundo más común en Estados Unidos [World Cancer Report, 2008]. La detección temprana es un factor que condiciona en gran medida la tasa de supervivencia a esta enfermedad, ya que a menor tamaño de la neoplasia detectada, mejores resultados pueden esperarse para los tratamientos quirúrgicos que se realicen. Además, la detección temprana aumenta la posibilidad de conservar la mama después de la cirugía y disminuye la necesidad de emplear otros tratamientos más invasivos[Secretaría de Salud, 2007, Alteri et al., 2011]. La mamografía es actualmente el procedimiento estándar que se emplea para el cribado del CM. Sin embargo, en los últimas años su eficiencia está siendo muy cuestionada por varios factores: (i) alta tasa de falsos positivos, (ii) requiere la irradiación del paciente y (iii) baja especificidad en mamas densas 2. Debido a lo anterior, para mejorar la detección y caracterización del CM se han propuesto varias técnicas complementarias. Entre ellas está la tomografía ultrasónica (TU), que es una técnica en desarrollo que presenta dos modalidades principales: la reflexión (proporciona mapas cualitativos de la concentración de dispersores en el tejido) y la transmisión (proporciona mapas cuantitativos de la velocidad y atenuación del sonido en el tejido). Los mapas del modo transmisión han sido propuestos como una eficiente alternativa, libre de radiación, para la detección del CM, ya que proporcionan alto contraste y especificidad [Mast, 2000, Duric et al., 2009]...Depto. de Estructura de la Materia, Física Térmica y ElectrónicaFac. de Ciencias FísicasTRUEunpu

Inference of Room Geometry From Acoustic Impulse Responses

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