Non-line-of-sight Conditions Research Articles

Cooperative volunteer protocol to detect non-line of sight nodes in vehicular ad hoc networks

A vehicular Ad hoc Network (VANET) is a special type of Mobile Ad hoc Network (MANET) application that impacts wireless communications and Intelligent Transport Systems (ITSs). VANETs are employed to develop safety applications for vehicles to create a safer and less cluttered environment on the road. The many remaining challenges relating to VANETs have encouraged researchers to conduct further investigation in this field to meet these challenges. For example, issues pertaining to routing protocols, such as the delivery of warning messages to vehicles facing Non-Line of Sight (NLOS) situations without causing a broadcasting storm and channel contention are regarded as a serious dilemma, especially in congested environments. This prompted the design of an efficient mechanism for a routing protocol capable of broadcasting warning messages from emergency vehicles to vehicles under NLOS conditions to reduce the overhead and increase the packet delivery ratio with reduced time delay and channel utilisation. This work used the cooperative approach to develop the routing protocol named the Co-operative Volunteer Protocol (CVP), which uses volunteer vehicles to disseminate the warning message from the source to the target vehicle experiencing an NLOS situation. A novel architecture has been developed by utilising the concept of a Context-Aware System (CAS), which clarifies the OBU components and their interaction with each other to collect data and make decisions based on the sensed circumstances. The simulation results showed that the proposed protocol outperformed the GRANT protocol with regard to several metrics such as packet delivery ratio, neighbourhood awareness, channel utilisation, overhead, and latency. The results also showed that the proposed CVP could successfully detect NLOS situations and solve them effectively and efficiently for both the intersection scenario in urban areas and the highway scenario.

A mobile localization strategy for wireless sensor network in NLOS conditions

The problem of mobile localization for wireless sensor network has attracted considerable attention in recent years. The localization accuracy will drastically grade in non-line of sight (NLOS) conditions. In this paper, we propose a mobile localization strategy based on Kalman filter. The key technologies for the proposed method are the NLOS identification and mitigation. The proposed method does not need the prior knowledge of the NLOS error and it is independent of the physical measurement ways. Simulation results show that the proposed method owns the higher localization accuracy when compared with other methods.

A multi-step Gaussian filtering approach to reduce the effect of non-Gaussian distribution in aerial localization of an RF source in NLOS condition

The hybrid localization using Angle Of Arrival (AOA) and Di erential Received Strength Signal Indicator (DRSSI) of an RF source with unknown power and Non- Line-Of-Sight (NLOS) condition has been proven to be advantageous compared to using each method separately. In this paper, the initial hybrid method, which was implemented using particle lters due to the multi-modal/non-Gaussian nature of localization in NLOS condition, has been replaced by a multi-step Gaussian ltering approach which provides similar accuracy with better performance. This has been done using DRSSI input in the rst step of the ltering to determine the linearization point, and then using AOA and DRSSI inputs together in the second step of the ltering to improve the localization accuracy. The proposed method has been implemented using Extended Kalman lter and Unscented Kalman lter. The simulation results show that the accuracy of the multi-step Gaussian ltering is comparable to the particle ltering approach with much lower computational load that is important for online localization of several RF sources. Furthermore, the e ects of uncertainty on the propagation parameters have been studied to show that the robustness of the multi-step Gaussian ltering to the uncertainties is comparable to the particle lter approach.

A Positioning System Based on Low-Frequency Magnetic Fields

This paper describes the design and the realization of a low-frequency ac magnetic-field-based indoor positioning system (PS). The system operation is based on the principle of inductive coupling between wire loop antennas. Specifically, due to the characteristics of the ac artificially generated magnetic fields, the relation between the induced voltage and the distance is modeled with a linear behavior in a bilogarithmic scale when a configuration with coplanar, thus equally oriented, antennas is used. In this case, the distance between a transmitting antenna and a receiving one is estimated using measurements of the induced voltage in the latter. For a high operational range, the system makes use of resonant antennas tuned at the same nominal resonant frequency. The quality factors act as antenna gain increasing the amplitude of the induced voltage. The low-operating frequency is the key factor for improving robustness against nonline-of-sight (NLOS) conditions and environment influences with respect to other existing solutions. The realized prototype, which is implemented using off-the-shelf components, exhibits an average and maximum positioning error, respectively, lower than 0.3 and 0.9 m in an indoor environment over a large area of 15 m × 12 m in NLOS conditions. Similar performance is obtained in an outdoor environment over an area of 30 m × 14 m. Furthermore, the system does not require any type of synchronization between the nodes and can accommodate an arbitrary number of users without additional infrastructure.

RSS-based indoor localization with PDR location tracking for wireless sensor networks

Traditional indoor localization techniques typically rely on a single communication source such as RF signals, ultrasound, inertial sensors, and geomagnetic fields. In wireless sensor network (WSN), received signal strength (RSS) based approach is one of the most commonly used localization techniques. It is simple to implement and costly efficient, but the estimation accuracy is significantly reduced in non-line-of-sight (NLOS) conditions. pedestrian dead reckoning (PDR) uses inertial measurement unit (IMU) for location tracking. Its tracking accuracy is not affected by the interference in NLOS conditions, but the location error is accumulated in long distance tracking. We propose the RSS-based indoor localization algorithm combined with PDR location tracking for wireless sensor networks. The objective is to compensate the NLOS localization error by using PDR, while mitigating the accumulated error of PDR by using RSS-based localization method in LOS conditions. Lab scale experiment and large scale simulation results show that the proposed algorithm significantly reduce the location estimation errors in wireless sensor networks.

Robust NLOS Error Mitigation Method for TOA-Based Localization via Second-Order Cone Relaxation

The existence of non-line-of-sight (NLOS) errors can significantly degrade the localization performance. In this letter, we address the time-of-arrival (TOA) based localization problem under NLOS conditions. To accurately localize a source, we propose a novel robust second-order cone relaxation (SOCR) method, which is not sensitive to NLOS errors. The proposed method does not require one to know any statistics of the NLOS errors, and instead, it only requires to know the upper bound on the magnitudes of the NLOS errors, which is relatively easy to obtain in practice. Simulation results show that the proposed robust SOCR method has good performance in various NLOS scenarios, and also it has a relatively lower computational complexity than the existing methods.

Indoor Mobile Localization in Mixed Environment with RSS Measurements

Mobile localization is a significant issue for wireless sensor networks (WSNs). However, it is a problem for the indoor localization using received signal strength (RSS) measurements that the signal is contaminated by the anisotropy fading and interference due to walls and furniture. Standard schemes such as Kalman filter are inadequate as the random transition of line-of-sight (LOS)/non-line-of-sight (NLOS) conditions occurs frequently. This paper proposes an indoor mobile localization scheme with RSS measurements in a mixed LOS and NLOS environment. First, a new efficient composite measurement model is induced and validated, which approximates the complex effects of LOS and NLOS channels. Second, a greedy anchor sensor selection strategy is adopted to break through the constraints of hardware consistency and the multipath interference. Third, for the Markov transition between LOS and NLOS conditions, an effective unscented Kalman filter (UKF) based interactive multiple model (IMM) is proposed to estimate not only the posterior model probabilities but also a weighted-sum position estimation with the aid of likelihood function. To evaluate the proposed algorithm, a complete hardware and software platform for mobile localization has been constructed. The numerical study, relying on the actual experiments, illustrates that the proposed UKF based IMM achieves a substantial gain in precision and robustness, compared with other works.

Transmit Beamforming Analysis for MIMO Systems in Indoor Residential Environment Based on 3D Ray Tracing

In this paper, an evaluation of transmit beamforming (TxBF) contribution is analyzed in the context of an indoor residential environment. Using an optimized 3D ray tracing tool, the multiple-input multiple-output (MIMO) propagation channel is simulated. The algorithm of singular value decomposition is applied and a new transmission scheme is considered. Comparisons of cases with/without TxBF are realized by analyzing the received power, the signal to noise ratio of each spatial stream and the channel capacity. It is shown that the TxBF capacity gain increases when the MIMO channel correlation at the transmit side reaches high values, especially when only the dominant eigen mode is selected. The main result concerns the antenna spacing: a judicious choice of the transmitting antenna spacing can improve the effective transmission range by more than 45 % in non-line of sight conditions. Several MIMO configurations (number of antennas and spatial streams) are also compared to determine the relevance of a possible activation of TxBF. The interference influence is studied and it is shown that under some conditions, TxBF improves the signal to interference ratio.

On geometric upper bounds for positioning algorithms in wireless sensor networks

This paper studies the possibility of upper bounding the position error for range-based positioning algorithms in wireless sensor networks. In this study, we argue that in certain situations when the measured distances between sensor nodes have positive errors, e.g., in non-line-of-sight (NLOS) conditions, the target node is confined to a closed bounded convex set (a feasible set) which can be derived from the measurements. Then, we formulate two classes of geometric upper bounds with respect to the feasible set. If an estimate is available, either feasible or infeasible, the position error can be upper bounded as the maximum distance between the estimate and any point in the feasible set (the first bound). Alternatively, if an estimate given by a positioning algorithm is always feasible, the maximum length of the feasible set is an upper bound on position error (the second bound). These bounds are formulated as nonconvex optimization problems. To progress, we relax the nonconvex problems and obtain convex problems, which can be efficiently solved. Simulation results show that the proposed bounds are reasonably tight in many situations, especially for NLOS conditions.

Physical layer secret key generation scheme used in 60 GHz band

The technology of 60 GHz radio is considered promising for providing fast connectivity and gigabit data rate. One of the main challenges to its secure indoor transmission is how to generate secret keys between communication devices. To investigate this issue, The authors develop an efficient mechanism of secret key generation exploiting multipath relative delay based on 60 GHz standard channel models. The comparison of key-mismatch probability between line-of-sight (LOS) and non-line-of-sight (NLOS) environments is considered. Verification of the proposed scheme is conducted. Simulation shows that the number of extracted multipath components proportionally did affect key generation rate and key-mismatch probability. It also indicates that communicating transceivers have a slightly lower key-mismatch probability in NLOS condition than in LOS condition. Moreover, in comparison to the existing approach of using received signal amplitude as a common random source, the mechanism can achieve better performance in key agreement.

Transmission Power Controlled Localization with Topology Building for NLOS Environments

The network which knows location of all nodes can improve the network capacity and lifetime in location-aware networks. However, localization algorithm of the network has to update its target node location due to mobility of target nodes and intermittent occurrence of interference. The update procedures cause frequent broadcasting and calculation for relocalization; therefore, maintaining the transmission power control (TPC) in the wireless sensor networks (WSNs) is valuable to the network. This paper proposes a new algorithm of transmission power controlled localization for indoor environment. Firstly, we propose minimum spanning tree (MST) based topology control with location error compensation algorithm to improve location accuracy and prevent target nodes from connecting to unstable links in non-line-of-sight (NLOS) condition. Secondly, we use TPC algorithm to improve the network lifetime. Each target node dynamically adjusts the power and the received signal strength (RSS) target by using the TPC algorithm. Experimental results show that the proposed algorithm compensates for location errors in NLOS condition while reducing the transmission power.

Relay selection with feedback beamforming information through designed sector sweep report frame for mmWave WPANs

This paper proposes a novel relay selection strategy based on the feedback beamforming (BF) information through designed sector sweep (SSW) report frame for millimeter-wave (mmWave) wireless personal networks (WPANs). First, an SSW report frame compatible with IEEE 802.11ad standard is designed. Second, an approach collecting instantaneous channel state information (CSI) overheard during BF is devised. Third, with the aim of minimizing the outage probability and maximizing the overall network throughput capacity, the optimal relay selection issue for non-line-of-sight (NLoS) links is formulated as a bipartite graph, and Kuhn Munkres (KM) algorithm is provided to resolve it. Both theoretical analysis and simulation results show, with CSI considering NLoS conditions and selected relays according to the overall network throughput capacity maximization principle, the improvements achieved over opportunistic relay selection strategy in terms of overall network throughput capacity and outage probability with minimal modifications to IEEE 802.11ad.

Mobile Localization in Non-Line-of-Sight Using Constrained Square-Root Unscented Kalman Filter

Localization and tracking of a mobile node (MN) in non-line-of-sight (NLOS) scenarios, based on time of arrival (TOA) measurements, is considered in this work. To this end, we develop a constrained form of square root unscented Kalman filter (SRUKF), where the sigma points of the unscented transformation are projected onto the feasible region by solving constrained optimization problems. The feasible region is the intersection of several discs formed by the NLOS measurements. We show how we can reduce the size of the optimization problem and formulate it as a convex quadratically constrained quadratic program (QCQP), which depends on the Cholesky factor of the \textit{a posteriori} error covariance matrix of SRUKF. As a result of these modifications, the proposed constrained SRUKF (CSRUKF) is more efficient and has better numerical stability compared to the constrained UKF. Through simulations, we also show that the CSRUKF achieves a smaller localization error compared to other techniques and that its performance is robust under different NLOS conditions.

MST-based topology control with NLOS location error compensation for location-aware networks

The topology control algorithms can improve the network capacity and network lifetime in location-aware networks. The topology control algorithms require accurate locations of mobile nodes or distances between each of the mobile nodes. The IEEE 802.15.4a-based location-aware networks can provide precise ranging distance between two mobile nodes. The mobile nodes can obtain their accurate locations by using accurate ranging distances. However, in the IEEE 802.15.4a networks, the ranging distance has a large measurement error in non-line-of-sight (NLOS) conditions. In this paper, we propose MST-based topology control with NLOS location error compensation algorithm to improve location accuracy and prevent mobile nodes from connecting to unstable links in NLOS condition. Performance evaluation shows the proposed algorithm constructs a topology map which has low location errors with considering the instability of NLOS links in NLOS condition.

Moving target localization in indoor wireless sensor networks mixed with LOS/NLOS situations

Indoor target localization is an essential and fundamental issue for wireless sensor networks (WSN). However, it is rather difficult for WSN to maintain the localization accuracy in line-of-sight (LOS) and non-line-of-sight (NLOS) mixed environment. NLOS propagation always leads to larger ranging error than LOS does. When the target moves in the rooms and corridors, the signal transmission state will switch frequently between LOS and NLOS. It is a challenging task to deal with this situation because the ranging error characteristics under LOS and NLOS conditions are quite different. In this paper, we propose an interacting multiple model-extended Kalman filter (IMM-EKF) algorithm to improve the localization accuracy for moving target in indoor environment. In the IMM structure, two Kalman filters (KF) are adopted in parallel to accurately smoothen the distance measurement. The proposed algorithm can adapt to the dynamically changing condition between LOS and NLOS due to the two KFs' interaction so that large NLOS ranging errors are further reduced. Once the estimated ranges are obtained, the EKF is employed to estimate the target's location. Empirical measurement results are obtained from typical office environment to verify the effectiveness of the proposed algorithm. Experimental results illustrate that the IMM smoother can efficiently mitigate the NLOS effects on ranging errors and achieve high localization accuracy.

Algebraic Approach for Robust Localization with Heterogeneous Information

We offer a redesigned form of the classical multidimensional scaling (C-MDS) algorithm suitable to handle the localization of multiple sources under line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. To do so we propose to modify the kernel matrix used in the MDS algorithm to allow for both distance and angle information to be processed algebraically (without iteration) and simultaneously. In so doing we also show that the new formulation overcomes two well known limitations of the C-MDS approach, namely the propagation error problem and the possibility to weight the dissimilarities used as measurement information, including, for the case of binary weights, the data erasure problem. Due to the increased size of the proposed edge kernel matrix KE used in the algorithm, the Nystrom approximation is applied to reduce the overall computational complexity to few matrix multiplications. Range only scenarios are also dealt with by approximating the matrix KE. Simulations in range-angle as well as range-only scenarios demonstrate the superiority of our solution under both LOS and NLOS conditions versus semidefinite programming (SDP) formulations of the problem specifically designed to exploit the heterogeneity of the information available.

MST 토폴로지를 이용한 실내 환경에서의 위치측정에러의 보상기법

무선 센서 네트워크를 위한 다양한 위치 추적 알고리즘들이 제안되고 있다. IEEE 802.15.4a 기반의 위치인식 시스템은 두 노드간의 정밀한 거리측정 기능을 제공하며 이를 기반으로 정확도가 높은 위치 추정 서비스를 제공한다. 하지만 실내 환경에서는 다양한 장해물들로 인하여 Non-line-of-sight (NLOS) 경로가 발생한다. 이로 인하여 IEEE 802.15.4a 기반의 위치 인식 시스템에서는 위치 추정 시 추정된 위치 좌표의 정확도가 떨어지는 문제가 발생한다. 이를 해결하기 위하여 본 논문에서는 MST 토폴로지를 이용한 실내 환경에서의 위치측정에러를 보상하는 알고리즘을 제안한다. NanoPAN 5375 모트를 이용한 실내 환경에서의 실험 및 시뮬레이션 결과, 제안한 알고리즘은 기존에 제안된 위치 추정 알고리즘에 비하여 위치 정확도가 개선되었음을 확인하였다. Many localization algorithms have been proposed for Wireless Sensor Networks (WSNs). The IEEE 802.15.4a-based location-aware-system can provide precise ranging distance between two mobile nodes. The mobile nodes can obtain their exact locations by using accurate ranging distances. However, the indoor environments contain various obstacles which cause non-line-of-sight (NLOS) conditions. In NLOS condition, the IEEE 802.15.4a-based location-aware system has a large scale location error. To solve the problem, we propose location error compensation in indoor environment by using MST-based topology control. Experimental and simulation results show that the proposed algorithm improves location accuracy in NLOS conditions.

Indoor Wireless Localization-hybrid and Unconstrained Nonlinear Optimization Approach

In this study, a hybrid TOA/RSSI wireless localization is proposed for accurate positioning in indoor UWB systems. The major problem in indoor localization is the effect of Non-Line of Sight (NLOS) propagation. To mitigate the NLOS effects, an unconstrained nonlinear optimization approach is utilized to process Time-of-Arrival (TOA) and Received Signal Strength (RSS) in the location system.TOA range measurements and path loss model are used to discriminate LOS and NLOS conditions. The weighting factors assigned by hypothesis testing, is used for solving the objective function in the proposed approach. This approach is used for describing the credibility of the TOA range measurement. Performance of the proposed technique is done based on MATLAB simulation. The result shows that the proposed technique performs well and achieves improved positioning under severe NLOS conditions.

A Comparative Study of Localization Methods in Indoor Environments

A comparative study, based on three different measurements (direction of ray arrival, time difference of arrival and received signal strength), to compute the unknown position of mobile stations in indoor environments is presented in this paper. The comparison is carried out considering the results of analyses in a real building in Madrid. To overcome the problems that arise in indoor areas due to the presence of non line of sight conditions, the fingerprinting technique is applied in each of the cases. Data for computations are provided by a simulation tool based on the uniform theory of diffraction and ray-tracing techniques. This information is stored in the fingerprinting database and contains information related to every mobile station, every reference node and every access point located inside the environment under analysis. Experimental results compare the mean error when localizing several mobile stations by using the three different approaches. The goal is to obtain high precision in the localization by means of alternative methods to the received signal strength classical measurement. These techniques will be useful in critical environments where high operational security requirement are demanded.

A Self-Calibrated Localization System using Chirp Spread Spectrum in a Wireless Sensor Network

To achieve accurate localization information, complex algorithms that have high computational complexity are usually implemented. In addition, many of these algorithms have been developed to overcome several limitations, e.g., obstruction interference in multi-path and non-line-of-sight (NLOS) environments. However, localization systems those have complex design experience latency when operating multiple mobile nodes occupying various channels and try to compensate for inaccurate distance values. To operate multiple mobile nodes concurrently, we propose a localization system with both low complexity and high accuracy and that is based on a chirp spread spectrum (CSS) radio. The proposed localization system is composed of accurate ranging values that are analyzed by simple linear regression that utilizes a Big-O(n 2 ) of only a few data points and an algorithm with a self-calibration feature. The performance of the proposed localization system is verified by means of actual experiments. The results show a mean error of about 1 m and multiple mobile node operation in a 100×35 m² environment under NLOS condition.