Hongyang Chen

Mobile element assisted cooperative localization for wireless sensor networks with obstacles

In this paper, a cooperative localization algorithm is proposed that considers the existence of obstacles in mobility-assisted wireless sensor networks (WSNs). An optimal movement scheduling method with mobile elements (MEs) is proposed to address limitations of static WSNs in node localization. In this scheme, a mobile anchor node cooperates with static sensor nodes and moves actively to refine location performance. It takes advantage of cooperation between MEs and static sensors while, at the same time, taking into account the relay node availability to make the best use of beacon signals. For achieving high localization accuracy and coverage, a novel convex position estimation algorithm is proposed, which can effectively solve the problem when infeasible points occur because of the effects of radio irregularity and obstacles. This method is the only rangefree based convex method to solve the localization problem when the feasible set of localization inequalities is empty. Simulation results demonstrate the effectiveness of this algorithm.

Non-Line-of-Sight Node Localization Based on Semi-Definite Programming in Wireless Sensor Networks

An unknown-position sensor can be localized if there are three or more anchors making time-of-arrival (TOA) measurements of a signal from it. However, the location errors can be very large due to the fact that some of the measurements are from non-line-of-sight (NLOS) paths. In this paper, a semi-definite programming (SDP) based node localization algorithm in NLOS environments is proposed for ultra-wideband (UWB) wireless sensor networks. The positions of sensors can be estimated using the distance estimates from location-aware anchors as well as other sensors. However, in the absence of line-of-sight (LOS) paths, e.g., in indoor networks, the NLOS range estimates can be significantly biased. As a result, the NLOS error can remarkably decrease the location accuracy, and it is not easy to accurately distinguish LOS from NLOS measurements. According to the information known about the prior probabilities and distributions of the NLOS errors, three different cases are introduced and the respective localization problems are addressed. Simulation results demonstrate that this algorithm achieves high location accuracy even for the case in which NLOS and LOS measurements are not identifiable.

Multi-User Two-Way Relay Networks with Distributed Beamforming

We consider a two-way relay network consisting of multiple pairs of single-antenna users and multiple distributed single-antenna relays. The two communication peers in each pair of users transmit simultaneously to the relays in the first time slot, and the relays rebroadcast the received sum signal weighted by a complex gain, in the second time slot. For multi-user systems, the signal arriving at the users contains not only self interference from the back-propagation of user signals, but also inter-pair interferences from other pairs of users. In this paper, we use zero-forcing (ZF) to cancel the inter-user interference, assuming that channel-state information for all relay-peer connections are known at every relay, but no data exchange occurs between relays. We also derive two closed-form expressions for zero-forcing beamforming weights, corresponding to two different relay power constraints, which can be implemented in a distributed manner. The first approach uses standard ZF to null out every inter-pair interference and the second approach sets the total inter-pair interference to zero. We also derive a closed-form upper bound of the achievable sum-rate and show that both methods achieve the same multiplexing gain when the number of relays N is sufficient for perfect zero-forcing, namely 2K2 + K, where K is the number of user pairs. For the case of insufficient number of relays, we also propose two solutions for beamforming weights, i.e., based on diagonal loading and use of the pseudo-inverse, and compare their advantages and weaknesses.

An Importance Sampling Method for TDOA-Based Source Localization

We consider the source localization problem using time-difference-of-arrival (TDOA) measurements in sensor networks. The maximum likelihood (ML) estimation of the source location can be cast as a nonlinear/nonconvex optimization problem, and its global solution is hardly obtained. In this paper, we resort to the Monte Carlo importance sampling (MCIS) technique to find an approximate global solution to this problem. To obtain an efficient importance function that is used in the technique, we construct a Gaussian distribution and choose its probability density function (pdf) as the importance function. In this process, an initial estimate of the source location is required. We reformulate the problem as a nonlinear robust least squares (LS) problem, and relax it as a second-order cone programming (SOCP), the solution of which is used as the initial estimate. Simulation results show that the proposed method can achieve the Cramer-Rao bound (CRB) accuracy and outperforms several existing methods.

Asymmetrical Round Trip Based Synchronization-Free Localization in Large-Scale Underwater Sensor Networks

Underwater sensor networks (UWSNs) have been proposed for many location-dependent applications such as oceanographic data collection, pollution monitoring, mine reconnaissance, etc. Accurate node localization plays an important role in realizing the potential gains of these applications. Although many localization algorithms have been proposed for terrestrial sensor networks in recent years, it is not feasible to directly use these algorithms in UWSNs since UWSNs lack a fast and reliable communication channel. Further, due to their slow convergence speeds and high communication overhead, distributed localization algorithms designed for small-scale UWSNs are not practical for large-scale underwater sensor systems. To achieve accurate and energy efficient node localization in large-scale UWSNs, an asymmetrical round trip based localization (ARTL) algorithm is proposed in this paper. This algorithm has low computational complexity and excellent scalability. Without time synchronization, this algorithm can achieve highly accurate ranging in large-scale UWSNs. Simulation results demonstrate the effectiveness of our design in terms of both localization accuracy and energy consumption.

An Improved DV-Hop Localization Algorithm with Reduced Node Location Error for Wireless Sensor Networks

In this paper, we propose a new localization algorithm and improve the DV-Hop algorithm by using a differential error correction scheme that is designed to reduce the location error accumulated over multiple hops. This scheme needs no additional hardware support and can be implemented in a distributed way. The proposed method can improve location accuracy without increasing communication traffic and computing complexity. Simulation results show the performance of the proposed algorithm is superior to that of the DV-Hop algorithm.

Mobility-Assisted Node Localization Based on TOA Measurements Without Time Synchronization in Wireless Sensor Networks

Wireless sensor networks (WSNs) have been proposed for a multitude of location-dependent applications. To stamp the collected data and facilitate communication protocols, it is necessary to identify the location of each sensor. In this paper, we discuss the performance of two novel positioning schemes, which use two generalized geometrical localization algorithms to achieve an accurate estimation based on time-of-arrival (TOA) measurements without time synchronization. In order to improve the network performance and address the limitations of static WSNs on position estimation, a mobile anchor is utilized effectively and two attractive movement strategies for mobile anchor are designed accordingly. The effectiveness of our approaches is validated and compared with the traditional Trilateration method by extensive simulations.

Distributed Angle Estimation for Localization in Wireless Sensor Networks

In this paper, we design a new distributed angle estimation method for localization in wireless sensor networks (WSNs) under multipath propagation environment. We employ a two-antenna anchor that can emit two linear chirp waves simultaneously, and propose to estimate the angle of departure (AOD) of the emitted waves at each receiving node via frequency measurement of the local received signal strength indication (RSSI) signal. An improved estimation method is further proposed where multiple parallel arrays are adopted to provide the space diversity. The proposed methods rely only on radio transceivers and do not require frequency synchronization or precise time synchronization between the transceivers. More importantly, the angle is estimated at each sensor in a completely distributed manner. The performance analysis is derived and simulations are presented to corroborate the proposed studies.

Accurate and Efficient Node Localization for Mobile Sensor Networks

In this paper, we propose a range-free cooperative localization algorithm for mobile sensor networks by combining hop-distance measurements with particle filtering. In the hop-distance measurement step, we design a differential-error correction scheme to reduce the positioning error accumulated over multiple hops. We also introduce a backoff-based broadcast mechanism in our localization algorithm. It efficiently suppresses redundant broadcasts and reduces message overhead. The proposed localization method has fast convergence with small location estimation error. We verify our algorithm in various scenarios and compare it with conventional localization methods. Simulation results show that our proposed method has similar or superior performance when compared to other state-of-the-art localization algorithms.

Cooperative Node Localization for Mobile Sensor Networks

In this paper, we propose a range-free cooperative localization algorithm for mobile sensor networks by combining hop distance measurements and particle filtering. In the hop distance measurement step, a differential error correction scheme is devised to reduce the positioning error accumulated over multiple hops. A backoff-based broadcast mechanism is also introduced in our localization algorithm. It efficiently suppresses redundant broadcasts and reduces message overhead. The proposed localization method has fast converges with small location estimation error. We verify your algorithm in various scenarios and compare it with conventional localization methods. Simulation results show that our proposal is superior to the state-of-the-art localization algorithms for mobile sensor networks.