Target tracking with line-of-sight identification in sensor networks under unknown measurement noises

Abstract—Tracking a target is a fundamental and crucial problem in wireless sensor networks. It is well known that non-line-of-sight (NLOS) propagation will significantly degrade the tracking accuracy if its effects are ignored. In this paper, a line-of-sight (LOS) identification approach for range-based tracking systems is developed to discard the NLOS measurements. Based on Lp-norm LOS identification strategy, a novel target tracking method is devised with the use of costreference particle filter, which does not require the knowledge of the measurement noise distribution. Computer simulations are included to verify the effectiveness of the proposed approach under different noise distributions. 1

Mobile Location with NLOS Identification and Mitigation Based on Modified Kalman Filtering

In order to enhance accuracy and reliability of wireless location in the mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environments, a robust mobile location algorithm is presented to track the position of a mobile node (MN). An extended Kalman filter (EKF) modified in the updating phase is utilized to reduce the NLOS error in rough wireless environments, in which the NLOS bias contained in each measurement range is estimated directly by the constrained optimization method. To identify the change of channel situation between NLOS and LOS, a low complexity identification method based on innovation vectors is proposed. Numerical results illustrate that the location errors of the proposed algorithm are all significantly smaller than those of the iterated NLOS EKF algorithm and the conventional EKF algorithm in different LOS/NLOS conditions. Moreover, this location method does not require any statistical distribution knowledge of the NLOS error. In addition, complexity experiments suggest that this algorithm supports real-time applications

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

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

Investigation of Time-Difference-Of-Arrival Localization Method for Non-Line-Of-Sight Scenarios

A novel localization concept, which considers non-line-of-sight (NLOS) propagation, is proposed in this dissertation. By introducing a transfer function that relates the field at a given receiver to the source as a function of frequency and position, the NLOS effects can be mitigated and the propagation channel can be calibrated back to free space. The conventional Time Difference of Arrival (TDOA) method under Line-of-Sight (LOS) and noisy conditions is implemented first, and then the theory is extended to the proposed method, which de-embeds the transfer function and extends the TDOA method to account for NLOS effects. A global search method and an iterative method are both introduced, based on the concept of de-embedding the transfer function. This involves using processed received signals (received signals after de-embedding the corresponding transfer functions). The localization accuracy achieved using the iterative method for various NLOS scenarios is investigated, including a refraction problem, a near field problem, and a scattering problem. Subsequently, the study is further extended to allow for multiple reflection effects. Three different models are provided. First, a parallel-wall model considers the case when the reflections are basically coming from a single horizontal direction. A 3D localization model and 2D enclosed wall model are then also presented to illustrate cases when the reflections come from either the vertical or the two horizontal directions. A hybrid iterative method, combining the iterative method and the global search method, is proposed to solve the problem of convergence that occurs when the transmitted signal is operating at high frequencies (so that the enclosed area of interest is large compared with a wavelength), especially with a narrow frequency bandwidth. Simulation results demonstrate that the proposed algorithm performs much better than the usual TDOA localization method, and the accuracy is only limited by the sampling frequency. An experiment (performed at Sandia National Laboratories) is set up to verify the improvement in using the proposed method vs. the usual TDOA method.Electrical and Computer Engineering, Department o

Interface air pour systèmes de navigation en bande S : étude détaillée des signaux OFDM

Positioning in urban or indoor environment is a hot topic, either due to regulations such as the E911 requiring US mobile telecommunication operators to be able to locate their subscribers in case of emergency, or due to the market development, with the extension of location - based services targeting the mass market concentrated in metropolitan areas. In urban or indoor areas, it is generally recognized that satellite - based positioning systems are not suitable (alone) to provide a continuous, reliable and accurate position to the user. Therefore, alternative positioning techniques may be useful to complement or replace satellite positioning in these environments. This PhD study ha s studied the possibility of using a mobile TV system based on the DVB - SH standard as system of opportunity for positioning. The advantage s of using a DVB - SH system for positioning are multiple. First, such system has a good availability in metropolitan areas, including indoor. Secondly, the emitters are synchronized and their density should be sufficient to track signals from several emitters simultaneously. This opens the possibility of using timing measurements from several emitters to find a position by trilateration . Also, the large bandwidth of the TV signal, required for the transmission of video content, should be beneficial for the accuracy of the timing measurements and for the robustness against multipath . Therefore, DVB - SH system seems to be an interesting candidate as system of opportunity for positioning. However, several challenges are to be solved for such a solution to be relevant. First, the signals propagate in the urban environment, which creates challenging conditions for positioning su ch as strong power fading, blockage of the desired line - of - sight signal or large echoes. Secondly, the DVB - SH standard uses an OFDM modulation, which has not been studied for positioning purpose. Therefore, techniques for fine tracking of the first receive d signal replica will have to be developed. Finally, a particularity of modern broadcast system is the use of a Single Frequency Network, in which all emitters send the same signal on the same carrier frequency. Therefore emitter identification in a Single Frequency will be another issue to be solved. This PhD study has proved the feasibility of positioning using DVB - SH signals. The main contributions of this work are the propositions of (1) an OFDM signal delay tracking method working in urban propagation channels, and (2) a modification to the network deployment permitting emitter identification and (3) a first assessment of the position accuracy using the proposed algorithms. These two methods have very low impact on the initial TV broadcasting service if the right set of signal parameters is chosen: no signal modification is required and the network deployment modification uses a feature already present in the DVB - SH standard. The positioning method was simulated using real urban propagation channel measurements. The obtained position has root mean square error of 4 0m. The main error contribution comes from tracking a non - line - of - sight signal. Further work would be required to deal with this issue, which would lower the position root mean square error to 7 m, which has been locally observed in the simulation for good tracking conditionsLe positionnement en environnement urbain est un domaine de recherche actif, de par la croissance des services grand public liées à la localisation, et à cause de réglementations émergentes liées aux situations d'urgence (E911). En environnement urbain ou à l'intérieur des bâtiments, il est communément admis que les systèmes de positionnement basés sur des satellites ne sont pas suffisants pour fournir une position précise, fiable et de manière continue. Des techniques de positionnement alternatives sont donc développées afin de remplacer ou compléter les systèmes de positionnement par satellite. Cette thèse étudie la possibilité de fournir un service de positionnement utilisant un futur système de diffusion de télévison vers les mobiles basé sur le standard DVB-SH. Le principal attrait de ce système pour du positionnement est sa bonne couverture en milieu urbain, ainsi que l'utilisation d'un réseau d'émetteurs synchronisés. Il est donc possible d'employer des mesures de temps d'arrivée des signaux afin de réaliser une triangulation pour calculer la position d'un récepteur. Afin de fournir ce service innovant, des techniques spécifiques d'estimation de pseudo-distance et d'identification d'émetteurs ont été développées dans le cadre de cette thèse. Le principal résultat de cette étude est d'avoir montré la faisabilité du positionnement utilisant un système DVB-SH, ne nécessitant que de légères modifications du système qui n'apportent aucune dégradation auservice de diffusion TV. De premières simulations ont montré une précision de positionnement autour de 40m en utilisant des mesures réalistes de canal de propagation urbain

Non-Line-of-Sight Error Mitigation in Mobile Location

The location of mobile terminals has received considerable attention in the recent years. The performance of mobile location systems is limited by errors primarily caused by non-line-of-sight (NLOS) propagation conditions. In this paper, we investigate the NLOS error identification and correction techniques for mobile user location in wireless cellular systems. Based on how much a priori knowledge of the NLOS error is available, two NLOS mitigation algorithms are proposed. Simulation results demonstrate that, with the prior information database, the location estimate can be obtained with good accuracy even in severe NLOS propagation conditions