Impacto del modelo de error en distancia en la simulación de sistemas de localización

Las redes inalámbricas han favorecido enormemente el interés de los usuarios, proveedores de servicio y operadores de red en el posicionamiento geográfico. Como consecuencia, se han propuesto mecanismos en la mayor parte de tecnologías de red inalámbrica con los que soportar la localización de usuarios. La evaluación de calidad ofrecida por dichas técnicas de localización, normalmente en términos de precisión, latencia y escalabilidad, recae en herramientas de simulación. Es esencial por tanto, que los modelos de error empleados en estas herramientas estén acordes a la realidad. Este hecho es si cabe más importante en el caso de emplear técnicas de localización basadas en medida de la distancia a partir de métricas temporales, como son el tiempo de llegada (TOA) o la diferencia entre tiempos de llegada (TDOA). Estas técnicas son especialmente sensibles a no disponer de visión directa entre los distintos elementos involucrados en la localización, por lo que la evaluación de sus capacidades suele hacerse bajo esas condiciones. El presente artículo compara bajo un mismo escenario, diversos modelos de error para las métricas empleadas en técnicas como TOA o TDOA. Los resultados concluyen que los modelos que no tienen en cuenta las distancias reales (que son los más habituales) tienden a proporcionar una estimación optimista el error de posicionamiento, cosa que no ocurre en el caso de modelos más complejos que sí tienen en cuenta esa información.Postprint (published version

Artificial Neural Network for Location Estimation in Wireless Communication Systems

In a wireless communication system, wireless location is the technique used to estimate the location of a mobile station (MS). To enhance the accuracy of MS location prediction, we propose a novel algorithm that utilizes time of arrival (TOA) measurements and the angle of arrival (AOA) information to locate MS when three base stations (BSs) are available. Artificial neural networks (ANN) are widely used techniques in various areas to overcome the problem of exclusive and nonlinear relationships. When the MS is heard by only three BSs, the proposed algorithm utilizes the intersections of three TOA circles (and the AOA line), based on various neural networks, to estimate the MS location in non-line-of-sight (NLOS) environments. Simulations were conducted to evaluate the performance of the algorithm for different NLOS error distributions. The numerical analysis and simulation results show that the proposed algorithms can obtain more precise location estimation under different NLOS environments

Applying Rprop Neural Network for the Prediction of the Mobile Station Location

Wireless location is the function used to determine the mobile station (MS) location in a wireless cellular communications system. When it is very hard for the surrounding base stations (BSs) to detect a MS or the measurements contain large errors in non-line-of-sight (NLOS) environments, then one need to integrate all available heterogeneous measurements to increase the location accuracy. In this paper we propose a novel algorithm that combines both time of arrival (TOA) and angle of arrival (AOA) measurements to estimate the MS in NLOS environments. The proposed algorithm utilizes the intersections of two circles and two lines, based on the most resilient back-propagation (Rprop) neural network learning technique, to give location estimation of the MS. The traditional Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) have convergence problems, and even if the measurements are fairly accurate, the performance of these algorithms depends highly on the relative position of the MS and BSs. Different NLOS models were used to evaluate the proposed methods. Numerical results demonstrate that the proposed algorithms can not only preserve the convergence solution, but obtain precise location estimations, even in severe NLOS conditions, particularly when the geometric relationship of the BSs relative to the MS is poor

Middleware-Controlled Resource consumption for Location Traffic in Cellular Networks

Location is valuable information for services implemented in wireless networks. Location systems often use the infrastructure of cellular networks that have already been deployed. Accordingly, location systems spend resources of the network they use. This paper proposes a middleware to reduce the consumption of network resources and optimize the location traffic that is being carried. This middleware, called MILCO (Middleware for Location Cost Optimization), selects the optimum location technique depending on the request, i.e. the location technique that satisfies the quality of service (QoS) required and minimizes the resource operating expense. In addition, MILCO takes advantage of ongoing and carried location processes to reduce the overall expenditure of resources. Our results show that MILCO can reduce location-process failures and improve latency figures for location provisioning and resource use in cellular networks such as UMTS

AML algorithm and NLOS localization by AoA measurements.

Tao Suyi.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 51-53).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.2Chapter 1.1.1 --- Mobile Phone Applications --- p.3Chapter 1.1.2 --- Location Methods --- p.4Chapter 1.1.3 --- Location Algorithms --- p.9Chapter 1.2 --- AoA Localization --- p.10Chapter 1.3 --- The NLOS Problem --- p.11Chapter 2 --- AoA Localization --- p.13Chapter 2.1 --- Conventional Approach to AoA Localization --- p.14Chapter 2.2 --- Least Squares Approach to AoA Localization --- p.16Chapter 2.2.1 --- Ordinary Least Squares Approach (OLS) by Pages-Zamora --- p.16Chapter 2.2.2 --- The Weighted Least Squares Approach (WLS) --- p.18Chapter 2.3 --- Approximate Maximum Likelihood Method (AML) for AoA Localization --- p.19Chapter 2.4 --- Simulations --- p.21Chapter 3 --- Analysis and Mitigation of NLoS Effects --- p.26Chapter 3.1 --- The Non-Line-of-Sight (NLoS) Effects --- p.26Chapter 3.2 --- NLoS Mitigation in AoA Localization --- p.27Chapter 3.2.1 --- A Selective Model to Suppress NLOS Errors --- p.27Chapter 3.2.2 --- Dimension Determination and LOS Identification --- p.29Chapter 3.3 --- Simulations --- p.34Chapter 3.3.1 --- Experiment 1 --- p.34Chapter 3.3.2 --- Experiment 2 --- p.38Chapter 4 --- Conclusions and Suggestions for Future Work --- p.42Chapter 4.1 --- Conclusions --- p.42Chapter 4.2 --- Suggestions for future work --- p.44Chapter A --- Derivation of the Cramer Rao Lower Bound (CRLB) for AoA Localization --- p.45Chapter A.1 --- CRLB for all LoS --- p.45Chapter A.2 --- CRLB for both LoS and NLoS --- p.46Chapter B --- Derivation of the Error Covariance for OLS and WLS Estima- tors --- p.48Chapter B.1 --- Error Covariance for OLS Estimator --- p.49Chapter B.2 --- Error Covariance for WLS Estimator --- p.50Bibliography --- p.5

Multi-node TOA-DOA cooperative LOS-NLOS localization : enabling high accuracy and reliability

This dissertation investigates high performance cooperative localization in wireless environments based on multi-node time-of-arrival (TOA) and direction-of-arrival (DOA) estimations in line-of-sight (LOS) and non-LOS (NLOS) scenarios. Here, two categories of nodes are assumed: base nodes (BNs) and target nodes (TNs). BNs are equipped with antenna arrays and capable of estimating TOA (range) and DOA (angle). TNs are equipped with Omni-directional antennas and communicate with BNs to allow BNs to localize TNs; thus, the proposed localization is maintained by BNs and TNs cooperation. First, a LOS localization method is proposed, which is based on semi-distributed multi-node TOA-DOA fusion. The proposed technique is applicable to mobile ad-hoc networks (MANETs). We assume LOS is available between BNs and TNs. One BN is selected as the reference BN, and other nodes are localized in the coordinates of the reference BN. Each BN can localize TNs located in its coverage area independently. In addition, a TN might be localized by multiple BNs. High performance localization is attainable via multi-node TOA-DOA fusion. The complexity of the semi-distributed multi-node TOA-DOA fusion is low because the total computational load is distributed across all BNs. To evaluate the localization accuracy of the proposed method, we compare the proposed method with global positioning system (GPS) aided TOA (DOA) fusion, which are applicable to MANETs. The comparison criterion is the localization circular error probability (CEP). The results confirm that the proposed method is suitable for moderate scale MANETs, while GPS-aided TOA fusion is suitable for large scale MANETs. Usually, TOA and DOA of TNs are periodically estimated by BNs. Thus, Kalman filter (KF) is integrated with multi-node TOA-DOA fusion to further improve its performance. The integration of KF and multi-node TOA-DOA fusion is compared with extended-KF (EKF) when it is applied to multiple TOA-DOA estimations made by multiple BNs. The comparison depicts that it is stable (no divergence takes place) and its accuracy is slightly lower than that of the EKF, if the EKF converges. However, the EKF may diverge while the integration of KF and multi-node TOA-DOA fusion does not; thus, the reliability of the proposed method is higher. In addition, the computational complexity of the integration of KF and multi-node TOA-DOA fusion is much lower than that of EKF. In wireless environments, LOS might be obstructed. This degrades the localization reliability. Antenna arrays installed at each BN is incorporated to allow each BN to identify NLOS scenarios independently. Here, a single BN measures the phase difference across two antenna elements using a synchronized bi-receiver system, and maps it into wireless channel’s K-factor. The larger K is, the more likely the channel would be a LOS one. Next, the K-factor is incorporated to identify NLOS scenarios. The performance of this system is characterized in terms of probability of LOS and NLOS identification. The latency of the method is small. Finally, a multi-node NLOS identification and localization method is proposed to improve localization reliability. In this case, multiple BNs engage in the process of NLOS identification, shared reflectors determination and localization, and NLOS TN localization. In NLOS scenarios, when there are three or more shared reflectors, those reflectors are localized via DOA fusion, and then a TN is localized via TOA fusion based on the localization of shared reflectors

Impacto del modelo de ranging en sistemas TOA/TDOA. Propuestas de mejora

Castellano: Debido a la creciente popularidad de las redes ad hoc, ha habido un incremento en el interés por sus problemas asociados, especialmente el de posicionamiento de sus nodos. Por eso surgen en los últimos tiempos numerosas técnicas de posicionamiento. Dado que la simulación es la forma más común de evaluar el funcionamiento de las técnicas de posicionamiento, es vital la utilización de un modelo apropiado del entorno, con el fin de obtener evaluaciones realistas. Una característica de los entornos wireless de interior es el efecto provocado por la falta de visibilidad directa entre terminales (Non- Line-of-Sight), el cual deteriora la estimación de la posición en esquemas basados en estimaciones de la distancia (ranging) a través de medidas del tiempo de llegada (Timeof- Arrival). En este estudio se comparan mediante simulaciones de Monte Carlo varios modelos del error de ranging para entornos de interior y se investiga su impacto en los resultados de dos técnicas de localización. Los resultados muestran que el valor eficaz del error de posicionamiento sufre un incremento de hasta el 18% del valor eficaz del error de ranging cuando se usan modelos dependientes de la distancia en vez de sus homólogos independientes. Esto indica que la utilización de modelos dependientes de la distancia puede ser útil para evitar evaluaciones demasiado optimistas. El passive-TDOA (passive Time Difference Of Arrival) es una técnica de posicionamiento recientemente publicada, la cual tiene la interesante propiedad de no inyectar tráfico en la red. En este estudio se ha propuesto una serie de modificaciones sobre la técnica original, al objeto de mejorar la precisión obtenida. Dichas modificaciones consisten en la ponderación de las ecuaciones del sistema resultante de aplicar la técnica passive-TDOA, con el objetivo de penalizar aquellas ecuaciones que se suponen menos fiables. Para ello se han tenido en cuenta dos aspectos. Por un lado, se ha considerado que aquellas ecuaciones provenientes de puntos de acceso lejanos incurren en una mayor imprecisión. Por otro lado, se ha asumido que puntos de acceso cercanos entre si se verán afectados por errores de magnitud similar, puesto que las trayectorias seguidas por la señal se vean salpicadas por las mismas fuentes de error. En contra de lo esperado, los resultados obtenidos muestran que no se ha producido una mejora significativa

Impacto del modelo de ranging en sistemas TOA/TDOA. Propuestas de mejora

Castellano: Debido a la creciente popularidad de las redes ad hoc, ha habido un incremento en el interés por sus problemas asociados, especialmente el de posicionamiento de sus nodos. Por eso surgen en los últimos tiempos numerosas técnicas de posicionamiento. Dado que la simulación es la forma más común de evaluar el funcionamiento de las técnicas de posicionamiento, es vital la utilización de un modelo apropiado del entorno, con el fin de obtener evaluaciones realistas. Una característica de los entornos wireless de\ud interior es el efecto provocado por la falta de visibilidad directa entre terminales (Non- Line-of-Sight), el cual deteriora la estimación de la posición en esquemas basados en estimaciones de la distancia (ranging) a través de medidas del tiempo de llegada (Timeof- Arrival). En este estudio se comparan mediante simulaciones de Monte Carlo varios modelos del error de ranging para entornos de interior y se investiga su impacto en los resultados de dos técnicas de localización. Los resultados muestran que el valor eficaz del error de posicionamiento sufre un incremento de hasta el 18% del valor eficaz del error de ranging cuando se usan modelos dependientes de la distancia en vez de sus homólogos independientes. Esto indica que la utilización de modelos dependientes de la distancia puede ser útil para evitar evaluaciones demasiado optimistas. El passive-TDOA (passive Time Difference Of Arrival) es una técnica de posicionamiento recientemente publicada, la cual tiene la interesante propiedad de no inyectar tráfico en la red. En este estudio se ha propuesto una serie de modificaciones sobre la técnica original, al objeto de mejorar la precisión obtenida. Dichas modificaciones consisten en la ponderación de las ecuaciones del sistema resultante de aplicar la técnica passive-TDOA, con el objetivo de penalizar aquellas ecuaciones que se suponen menos fiables. Para ello se han tenido en cuenta dos aspectos. Por un lado, se ha considerado que aquellas ecuaciones provenientes de puntos de acceso lejanos incurren en una mayor imprecisión. Por otro lado, se ha asumido que puntos de acceso cercanos entre si se verán afectados por errores de magnitud similar, puesto que las trayectorias seguidas por la señal se vean salpicadas por las mismas fuentes de error. En contra de lo esperado, los resultados obtenidos muestran que no se ha producido una mejora significativa

Desenvolvimento de sistema de localização indoor de baixo consumo

Mestrado em Engenharia Eléctrónica e TelecomunicaçõesActualmente, os sistemas de localização apresentam-se como uma área em forte expansão. Os sistemas de localização possibilitam inúmeras vantagens para o controlo e gestão a nível empresarial como a nível residencial. Sendo o consumo energético um factor de tremenda importância destes. Esta dissertação propõe um sistema de localização indoor de baixo consumo energético baseado na plataforma CC2431ZDK utilizando a tecnologia ZigBee. Foi também desenvolvida uma interface gráfica em linguagem Java de fácil utilização onde é possível ao utilizador configurar e seleccionar o modo de localização desejado. Esta poderá ser baseada em proximidade, maior nível de potência detectado por sensores de referência ou numa localização de maior exactidão através de uma rede neuronal. Por fim, foi proposto o uso de uma antena com diagrama de radiação mais adequado para uma localização por proximidade comparativamente às antenas fornecidas na plataforma CC2431ZDK, deste modo foi desenhada e analisada uma antena impressa.Nowadays, the location systems appears as an area in strong expansion. The location systems enable advantage for the control and management at the enterprise residential level. One of the most important factors in their implementation is the energy consumption. This dissertation proposes a system for indoor location of low power consumption based on CC2431ZDK platform using ZigBee technology. It was also developed a graphical interface in Java language, easy to use where the user can configure and select the desired mode of detection. This can be based in proximity, higher level of power detected by reference nodes or a location of higher precision through a neural network. Finally, was proposed the use of an antenna with more appropriate radiation diagram for a location by proximity, comparatively to the antennas provided by the CC2431ZDK platform, thus was designed and analyzed a microstrip antenna