A spatio-temporal model for indoor non-line-of-sight (NLOS) impulse-based ultra-wideband channels, comprising clusters of multipath components with different times and angles of arrival, is proposed. This model is a spatial extension of the fixed-cluster temporal channel model, based on clustering patterns observed both in the times and angles of arrival of multipath components. It is demonstrated that the proposed extension accurately models the spatial correlation as well as the temporal properties of measured ultra-wideband signals in an indoor NLOS environment.

In ad hoc position-location networks, location information is obtained through the sequential estimation of node locations. An unlocalized node can estimate its location based on range and location estimates of nearby localized (";anchor";) nodes, and subsequently provide range and location information to other unlocalized nodes in its vicinity. In such distributed location-estimation scenarios, the accuracy of node location estimates is degraded due to the propagation of localization errors, particularly in NLOS propagation environments. This paper discusses the use of a novel method of mitigating the propagation of localization error using the linear programming framework proposed by the authors in [1]. This method utilizes multi-hop distance estimates to create additional constraints on the feasible region for a node's location, thereby limiting the propagation of error even in NLOS propagation environments.

In this paper, we discuss the use of power control in Ultra-Wideband (UWB) Position-Location Networks (PoLoNets)1, where the goal is to periodically estimate the locations of mobile nodes that move through a network of location-aware reference nodes. The reference nodes provide Time-of-Arrival (TOA) based range estimates that are used to estimate the locations of mobile nodes at regular intervals. We examine the accuracy of location-estimation through the Cramer-Rao lower bound (CRLB) and show that the localization accuracy fluctuates or "fades" as a mobile node moves through the network of reference nodes. The use of power control is shown to improve the robustness of location-estimates and provide higher localization accuracy. Two power control approaches are presented and compared with the empirically-obtained optimal solutions.

In this paper, we propose a linear programming approach to the problem of non-line-of-sight (NLOS) error mitigation in sensor networks. The locations of sensor nodes can be estimated using range or distance estimates from locationaware “anchor ” nodes. In the absence of line-of-sight (LOS) between the sensor and anchor nodes, e.g., in indoor networks, the NLOS range estimates can be severely biased. If these biased range estimates are directly incorporated into practical location estimators such as the Least-Squares (LS) estimator without the mitigation of these bias errors, this can potentially lead to degradation in the accuracy of sensor location estimates. On the other hand, discarding the biased range estimates may not be a viable option, since the number of range estimates available may be limited. We present a novel NLOS bias mitigation scheme, based on linear programming, that (i) allows us to incorporate NLOS range information into sensor location-estimation, but (ii) does not allow NLOS bias errors to degrade sensor localization accuracy.

In this paper, we analyze the problem of medium access control (MAC) layer design for impulse-based ultra-wideband (UWB) position-location networks (PoLoNets). We focus our attention on PoLoNets in which stationary reference nodes are deployed in an ad hoc manner and determine their locations based on a small number of fixed anchors with known locations. Location and range information is propagated through the network of reference nodes in order to periodically estimate the locations of mobile nodes. The principal objective of our design is to minimize the localization error and convergence time of location estimates in the presence of node mobility and multipath. The properties of bounds on node localization accuracy in the presence range and location-estimation errors are derived. These results serve as a connection between the problem of multiple-access design and the accuracy of location estimates. A spread-spectrum based MAC protocol is developed that is shown to outperform the traditional carrier-sense multiple-access (CSMA) protocol in terms of accuracy and the convergence time of location-estimates

In this paper, we build on known bounds on localization in sensor networks and provide new insights that can be used in multiple-access design from a localization perspective. Specifically, we look at the Cramer-Rao lower bound (CRLB)for the estimation of a sensor's location given unbiased Gaussian range estimates from a set of location-aware "anchor" nodes. A novel characterization of the accuracy of sensor location-estimates is derived, which provides new insights into the design of multiple-access schemes from the perspective of sensor localization accuracy. These insights are validated through the investigation of the performance of a spread-spectrum based multiple-access scheme in an ultra-wideband sensor network

We propose and analyze a novel single channel direction finding (DF) algorithm based on phase-locked loops (PLL). The algorithm is evaluated via Matlab simulation to determine the accuracy of the estimated angle-of-arrival (AOA) of a target signal in an AWGN channel. The proposed algorithm is shown to provide exceptional accuracy. Additionally, we present results from a hardware implementation using a software radio platform and an eight-element circular array; they validate the simulation results.