Implementation of Kalman Filter with Python Language

International audienceIn this paper, we investigate the implementation of a Python code for a Kalman Filter using the Numpy package. A Kalman Filtering is carried out in two steps: Prediction and Update. Each step is investigated and coded as a function with matrix input and output. These different functions are explained and an example of a Kalman Filter application for the localization of mobile in wireless networks is given

A Maximum Likelihood TOA Based Estimator For Localization in Heterogeneous Networks

International audienceIn this paper, we exploit the concept of data fusion in hybrid localization systems by combining different TOA (Time of Arrival) observables coming from different RATs (Radio Access Technology) and characterized by different precisions in order to enhance the positioning accuracy. A new Maximum Likelihood estimator is developed to fuse different measured ranges with different variances. In order to evaluate this estimator, Monte Carlo simulations are carried out in a generic environment and Cramer Rao Lower Bounds (CRLB) are investigated. This algorithm shows enhanced positioning accuracy at reasonable noise levels comparing to the typical Weighted Least Square estimator. The CRLB reveals that the choice of the number, and the configuration of Anchor nodes, and the type of RAT may enhance positioning accuracy

Taylor series method in TDOA approach for indoor positioning system

Localisation technologies have always remained in the limelight of positioning-science as researchers have ever shown keen interest to know the exact positions of things. Ultrasonic sensors are mainly used for localisation of mobile robots since they provide high accuracy. This paper presents Taylor Series Method in Time Difference of Arrival approach using ultrasonic sensors.Signals are send from the sensors periodically.The time difference of arrival of signals from the ultrasonic sensors is used by the receiver unit to estimate the location of the mobile unit. The equations formed by using Time Difference of Approach are solved using Taylor Series Method. Taylor Series Method provides a more accurate result since they give less error compared to other methods and they ignore the measurement errors

A new localization algorithm based on neural networks

Indoor localization plays a major role in a wide range of applications. To determine the location of a tag, localization algorithm is required. In the past, machine learning algorithms were difficult to implement in consumer hardware, but with the advent of tensor processing units, even smartphones are capable to use artificial intelligence to solve complex problems. In this paper, we investigate a machine learning algorithm based on neural networks and compare the result to a linear least squares estimator. We design and evaluate different neural networks. Based on our observation, the neural network delivers poor performance compared to the linear least squares estimator

Localization and Fingerprint of Radio Signals Employing a Multichannel Photonic Analog-to-Digital Converter

[EN] The fingerprint and localization of radio signals employing a multichannel photonic analog-to-digital converter (ADC) is proposed, analyzed, and demonstrated in a laboratory experiment. The photonic ADC detects the radio signals with high sensitivity in a large bandwidth without down-conversion stages. This is of special interest when processing emerging low-power wireless standards like ultra-wideband (UWB) radio. The optical processing in the multichannel photonic ADC is tailored for the localization and fingerprint of generic radio transmitters when orthogonal-frequency division multiplexing (OFDM) modulation is employed in the transmission. The photonic ADC includes engineered optical and electrical amplification. The experimental work demonstrates that detection of radio signals with -65 dBm power with signal-to-noise ratio better than 20 dB is feasible, which is in good accordance with the theoretical analysis. The multichannel photonic ADC comprises five optical channels which are precisely time-aligned in optical domain achieving 0.23-m spatial resolution (median) in the localization of radio transmitters. The experimental work also demonstrates that photonic-ADC processing is adequate for OFDM-based UWB radio-signal fingerprint including estimation of the average power, frequency band of operation, and time-frequency hopping pattern if applicable. UWB transmitter localization has been experimentally demonstrated with 0.4-m error.This work was supported in part by the European 7th Framework Program Project UCELLS FP7-IST-216785. The work of M. Morant was supported by Spain FPU MEC under Grant AP2007-01413.Llorente, R.; Morant, M.; Puche, JF.; Romme, J.; Amiot, N.; Uguen, B.; Duplicy, J. (2010). Localization and Fingerprint of Radio Signals Employing a Multichannel Photonic Analog-to-Digital Converter. IEEE Transactions on Microwave Theory and Techniques. 58(11):3304-3311. https://doi.org/10.1109/TMTT.2010.2076730S33043311581

Smart Television Services Using NFV/SDN Network Management

International audienceIntegrating joint network function virtualization (NFV) and software-defined networks (SDNs) with digital televisions (TVs) into home environments, has the potential to provide smart TV services to users, and improve their quality of experience (QoE). In this regard, this paper focuses on one of the next generation services so-called follow me service (FMS). FMS is a service offered by 5gNB to user equipments (UEs) in indoor environments (e.g., home), it enables its clients to use their smart phones to select media content from content servers, then cast it on the nearest TV set (e.g., living room) and continue watching on the next TV set (e.g., kitchen) while moving around the indoor coverage area. FMS can be provisioned by utilizing UEs geoloca-tion information and robust mechanisms for switching between multiple 5G radio access technologies (RATs), based on the intelligence of the SDN/NFV intelligent home IP gateway of the Internet of Radio Light (IoRL) project paradigm. In view that the actual IoRL system is at its early development stage, we step forward by using Mininet platform to integrate SDN/NFV virtualization into 5G multi-RAT scenario and provide performance monitoring with measurements for the identified service. Simulation results show the effectiveness of our proposal under various use case scenarios by means of minimizing the packet loss rate and improving QoE of the home users. Index Terms-Software defined networks, network function virtualisation, quality of experience, Internet of radio light, intelligent home IP gateway

Algoritmos de Radiolocalización basados en ToA, TDoA y AoA

Based on the geometric principles of Triangulation and Trilateration some location estimation techniques such as ToA (Time of Arrival), TDoA (Time Difference of Arrival) and AoA (Angle of Arrival) are presented. For these estimation techniques different algorithms are analyzed including the Analytical method, Least Squares method and Taylor Series method for ToA and TDoA, and Capon, Barttlet and MUSIC for AoA. This article pretends to present survey of location estimation techniques and their mathematical description.Partiendo de los principios geométricos de Triangulación y Trilateración se presentan algunas técnicas de estimación de ubicación como lo son ToA (Tiempo de llegada), TDoA (Diferencia en Tiempo de llegada) y AoA (Ángulo de llegada). Para estas técnicas de estimación diferentes algoritmos son analizados incluyendo el método Analítico, el método por Mínimos Cuadrados y el método por Series de Taylor para ToA y TDoA y Capon, Bartlett y MUSIC para AoA. Éste artículo pretende presentar una revisión del estado del arte sobre algunas técnicas de estimación de ubicación y su descripción matemáticamente

UWB Localization of people-accuracy aspects

Zaied, Salah: UWB Localization of people-accuracy aspects Zusammenfassung UWB-Sensoren sind durch eine sehr große Bandbreite gekennzeichnet. Diese Bandbreite ermöglicht es, Objekte mit einer sehr guten Genauigkeit zu lokalisieren. Passive Objekte, die kein Sender oder Empfänger tragen, sind mittels zurückgestreuten elektromagnetischen Wellen zu lokalisieren. Es existieren unterschiedliche Lokalisierungsmethoden. Die Masterarbeit analysiert unterschiedliche laufzeitbasierten Lokalisierungsansätze. Die Masterarbeite bietet verschiedene Lösungen von dem Lokalisierungsproblem, der mathematisch mit einem System von quadratischen Gleichungen beschrieben ist. Die Lösungen decken folgende Ansätze ab: Linearisierung mittels einer Taylor Reihe Entwicklung, Kreuzung von Ellipsen and sphärische Interpolation. Die Masterarbeit analysiert Genauigkeit von den Algorithmen in unterschiedlichen Einsatzszenarien. Die Lokalisierungsgenauigkeit war anhand der Hauptkomponentenanalyse ausgewertet.UWB sensors feature very large bandwidth. This bandwidth allows very accurate localization of tag-free targets such as people. In this case, an UWB localization system localizes tag-free by means of backscattered electromagnetic waves. There exist different localization approaches. The thesis concerns with the accuracy aspects of time-of-arrival based localization approaches. The thesis provides different solutions to the localization problem which is mathematically described by a system of two dimensional nonlinear equations of the second order like. These solutions cover: Taylor series linearization, intersection of ellipses and the spherical interpolation. The thesis analyses performance of these localization approaches in different simulation scenarios. The principal component analysis was used to evaluate precision of these localization approaches.Ilmenau, Techn. Univ., Master-Arbeit, 201