Yiyin Wang

Robust Time-Based Localization for Asynchronous Networks

Time-based localization approaches attract a lot of interest due to their high accuracy and potentially low cost for wireless sensor networks (WSNs). However, time-based localization is tightly coupled with clock synchronization. Thus, the reliability of timestamps in time-based localization becomes an important yet challenging task to deal with. In this paper, we propose robust time-based localization strategies to locate a target node with the help of anchors (nodes with known positions) in asynchronous networks. Two kinds of asynchronous networks are considered: one only with clock offsets, labeled quasi-synchronous networks, whereas the other with not only clock offsets but also clock skews, labeled fully asynchronous networks. A novel ranging protocol is developed for both networks, namely asymmetric trip ranging (ATR), to reduce the communication load and explore the broadcast property of WSNs. Regardless of the reliability of the timestamp report from the target node, closed-form least-squares (LS) estimators are derived to accurately estimate the target node position. As a result, we counter the uncertainties caused by the target node by ignoring the timestamps from this node. Furthermore, in order to simplify the estimator in fully asynchronous networks, localization and synchronization are decoupled. A simple yet efficient method is proposed to first Calibrate the Clock Skews of the anchors, and then Estimate the Node Position (CCS-ENP). Finally, Cramér-Rao bounds (CRBs) and simulation results corroborate the efficiency of our localization schemes.

Extending the Classical Multidimensional Scaling Algorithm Given Partial Pairwise Distance Measurements

We consider the problem of node localization given partial pairwise distance measurements. Current solutions first complete the missing distances and then apply the classical multidimensional scaling (MDS) algorithm. Instead, we extend the classical MDS to a setup where the sensor network is composed of a fully connected group of nodes that communicate with each other (e.g., beacons), and a group of nodes that cannot communicate with each other, but each one of them communicates with each node in the first group. The positions of all nodes are unknown. We localize the fully connected nodes by exploiting their distance measurements to the disconnected nodes. At the same time, the positions of the disconnected nodes are obtained up to a translation relative to the positions of the connected nodes. Recovering this translation, can be obtained with an additional step. Simulation results show that the proposed algorithm outperforms current MDS-like solutions to the problem.

Reference-free time-based localization for an asynchronous target

Low-complexity least-squares (LS) estimators based on time-of-arrival (TOA) or time-difference-of-arrival (TDOA) measurements have been developed to locate a target node with the help of anchors (nodes with known positions). They require to select a reference anchor in order to cancel nuisance parameters or relax stringent synchronization requirements. Thus, their localization performance relies heavily on the reference selection. In this article, we propose several reference-free localization estimators based on TOA measurements for a scenario, where anchor nodes are synchronized, and the clock of the target node runs freely. The reference-free LS estimators that are different from the reference-based ones do not suffer from a poor reference selection. Furthermore, we generalize existing reference-based localization estimators using TOA or TDOA measurements, which are scattered over different research areas, and we shed new light on their relations. We justify that the optimal weighting matrix can compensate the influence of the reference selection for reference-based weighted LS (WLS) estimators using TOA measurements, and make all those estimators identical. However, the optimal weighting matrix cannot decouple the reference dependency for reference-based WLS estimators using a nonredundant set of TDOA measurements, but can make the estimators using the same set identical as well. Moreover, the Cramér-Rao bounds are derived as benchmarks. Simulation results corroborate our analysis.

TOA estimation using UWB with low sampling rate and clock drift calibration

In this paper, a time-of-arrival (TOA) estimation scheme with clock drift calibration is proposed using an impulse-radio (IR) ultra-wideband (UWB) signal. We adopt low-rate stroboscopic sampling, which can achieve an equivalent sampling rate as high as the Nyquist sampling rate. The clock drift is one of the main error sources in TOA estimation for the stroboscopic sampling IR-UWB system, since a long preamble is required to collect sufficient data samples. Therefore, the drift is taken into account in our system model. First, the maximum-likelihood estimate of the drift is computed. Then, we employ the peak selection or the leading edge detection to estimate the TOA using the averaged data samples calibrated for the drift. Simulation results corroborate that the drift calibration significantly reduces the TOA estimation errors due to the drift, and that stroboscopic sampling can achieve the same estimation resolution as Nyquist sampling.

Cramér-Rao bound for range estimation

In this paper, we derive the Cramér-Rao bound (CRB) for range estimation, which does not only exploit the range information in the time delay, but also in the amplitude of the received signal. This new bound is lower than the conventional CRB that only makes use of the range information in the time delay. We investigate the new bound in an additive white Gaussian noise (AWGN) channel with attenuation by employing both narrowband (NB) signals and ultra-wideband (UWB) signals. For NB signals, the new bound can be 3dB lower than the conventional CRB under certain conditions. However, there is not much difference between the new bound and the conventional CRB for UWB signals. Further, shadowing effects are added into the data model. Several CRB-like bounds for range estimation are derived to take these shadowing effects into account.

Time-based localization for asynchronous wireless sensor networks

In this paper, we propose time-based localization approaches for asynchronous wireless sensor networks (WSNs), where not only clock skews but also clock offsets are present at all nodes. We first propose a joint synchronization and localization approach using the two-way ranging (TWR) protocol. Furthermore, a novel ranging protocol, namely asymmetric trip ranging (ATR), is employed and a two-step joint synchronization and localization approach is developed. As a result, we achieve efficient closed-form least-squares (LS) estimators. We compare these two proposed approaches. Moreover, simulation results corroborate the efficiency of our time-based localization schemes.

An UWB ranging-based localization strategy with internal attack immunity

The two-way ranging (TWR) protocol has been adopted in the IEEE 802.15.4a standard for wireless networks. However, it is vulnerable to malicious attacks (e.g., internal attacks). An internal ranging attack here refers to a fraudulent timestamp report. For example, a compromised sensor node tampers its timestamp report to spoof its processing time in order to malignly decrease or enlarge distance measurements, or a sensor node submits an inaccurate timestamp report due to the clock drift. In this paper, we propose an UWB ranging-based localization strategy, which is immune to the internal ranging attack. Regardless of the honesty of the timestamp report from a sensor node, we could still estimate the position of the sensor node accurately. We show how to defeat a ranging attack by taking it into account in the development of a localization algorithm.

Digital receiver design for transmitted reference ultra-wideband systems

A complete detection, channel estimation, synchronization, and equalization scheme for a transmitted reference (TR) ultra-wideband (UWB) system is proposed in this paper. The scheme is based on a data model which admits a moderate data rate and takes both the interframe interference (IFI) and the intersymbol interference (ISI) into consideration. Moreover, the bias caused by the interpulse interference (IPI) in one frame is also taken into account. Based on the analysis of the stochastic properties of the received signals, several detectors are studied and evaluated. Furthermore, a data-aided two-stage synchronization strategy is proposed, which obtains sample-level timing in the range of one symbol at the first stage and then pursues symbol-level synchronization by looking for the header at the second stage. Three channel estimators are derived to achieve joint channel and timing estimates for the first stage, namely, the linear minimum mean square error (LMMSE) estimator, the least squares (LS) estimator, and the matched filter (MF). We check the performance of different combinations of channel estimation and equalization schemes and try to find the best combination, that is, the one providing a good tradeoff between complexity and performance.

Acquisition for a transmitted reference UWB receiver

An acquisition algorithm for a transmitted reference (TR) ultra wideband (UWB) receiver is developed that uses the statistical properties of TR-UWB signals to distinguish between noise and data, achieve acquisition and ignores or decodes the incoming samples accordingly. Unknown parameters, like noise power and arriving time, are estimated and continuously updated once new data is acquired, enabling the receiver to adapt to changing environments. The acquisition is a detection problem with unknown arriving time and noise power. It is split into two steps, chip level and symbol level acquisition. Only segments that pass the first step are considered for the second step. This approach reduces the computational complexity and the implementationspsila resource demands.

Tracking a mobile node by asynchronous networks

In this paper, we propose a Kalman filter (KF) based tracking approach to track a target node with the assistance of anchors in an asynchronous network with clock offsets. We employ the asymmetric trip ranging (ATR) protocol to obtain TOA measurements and facilitate clock offset cancellation, and further derive a linear measurement model from the TOA measurements. Thus, the KF based on this linear measurement model does not have the modeling errors inherently contained in the Extended Kalman filter (EKF). Furthermore, low computational complexity makes the proposed KF a promising solution for practical use. We compare the proposed KF with the EKF. The simulation results corroborate its efficiency.