Gianni Giorgetti

Wireless localization using self-organizing maps

Localization is an essential service for many wireless sensor network applications. While several localization schemes rely on anchor nodes and range measurements to achieve fine-grained positioning, we propose a range-free, anchor- free solution that works using connectivity information only. The approach, suitable for deployments with strict cost constraints, is based on the neural network paradigm of self-organizing maps (SOM). We present a lightweight SOM- based algorithm to compute virtual coordinates that are effective for location-aided routing. This algorithm can also exploit the location information, if available, of few anchor nodes to compute absolute positions. Results of extensive simulations show improvements over the popular multi-dimensional scaling (MDS) scheme, especially for networks with low connectivity, which are intrinsically harder to localize, and in presence of irregular radio pattern or anisotropic deployment. We analytically demonstrate that the proposed scheme has low computation and communication overheads; hence, making it suitable for resource-constrained networks.

Exploiting Low-Cost Directional Antennas in 2.4 GHz IEEE 802.15.4 Wireless Sensor Networks

Motivated by recent interest in directional antennas for WSNs, we propose a four-beam patch antenna (FBPA) designed to meet the size, cost and complexity constraints of sensor nodes. We use in-field experiments with COTS motes to demonstrate substantial benefits to WSN applications. Used outdoors, the FBPA extends the communication range from 140 m to more than 350 m, while indoors it suppresses the interference due to multipath fading by reducing the signal variability of more than 70%. We also show interference suppression from IEEE 802.11 g systems and discuss the use of the antenna as a form of angular diversity useful to cope with the variability of the radio signal. Experimental data are analyzed to derive model parameters intended for use in future network simulations.

Analysis and Performance of a Smart Antenna for 2.45-GHz Single-Anchor Indoor Positioning

This paper presents the theoretical analysis and the experimental evaluation of a new switched beam antenna designed to operate at 2.45 GHz. The antenna enables direction of arrival estimation using six directional planar elements arranged to form a platonic solid geometry. It also supports polarization diversity, and it is suitable for single-anchor indoor positioning applications. We adopt the Cramer-Rao bound to study the estimation accuracy of the proposed antenna in absolute 2-D target positioning using received signal strength measurements. First, we describe the design principles for the radiators, we provide an extensive characterization of the switched antenna prototype, and we discuss positioning applications. We then report experimental data that support the results of the theoretical analysis and show consistency between theoretical expectation and the measurements. Finally, we discuss results from proof-of-concept operative indoor positioning example, showing an average localization error as low as 1.7 m.

Single-anchor indoor localization using a switched-beam antenna

We propose an RF-based localization system that works using a single anchor node. The anchor is equipped with a switched-beam directional antenna that is installed on the ceiling of a room and collects signal strength information sufficient for absolute 2D target positioning. Indoor measurements are used to show satisfactory localization results with range-free (proximity), range-based and fingerprinting schemes.

Understanding the limits of RF-based collaborative localization

RF-based localization has gained popularity as a low-cost solution to support position awareness in ad hoc networks. The received signal strength (RSS) measured by pairs of nodes can be used to obtain either range estimates or connectivity information. It is not clear, however: 1) when a range-based scheme should be used in favor of a connectivity-based one, and 2) how to optimally convert the RSS into connectivity data. This paper uses analysis of the Fisher information and the Cramér-Rao bound (CRB) to answer these questions. Solutions are found by comparing the network connectivity against two values: the critical connectivity (CC) and the optimal connectivity (OC). After discussing the properties of both values, we show how their approximation can be used to improve the performance of RF-based localization systems.

Optimal RSS threshold selection in connectivity-based localization schemes

Connectivity-based localization schemes compute the node positions using proximity information collected within the network. In many cases of practical interest, Received Signal Strength (RSS) measurements are available, and connectivity data can be obtained by comparing the RSS against a threshold. We use the Cramér-Rao bound (CRB) analysis to determine the threshold value that minimizes the localization error. The CRB is based on knowledge of the propagation models parameters and the true node positions. Since this information is not available to a localization scheme, we approximate the optimal threshold value using a function that depends only on the number of nodes in the network. We use extensive simulations and RSS data from in-field experiments to validate the results of the proposed approach.

A 2.45 GHz smart antenna for location-aware single-anchor indoor applications

This paper proposes a new switched beam array optimized for 2.45 GHz wireless indoor applications. The antenna supports directional communication to enable spatial reusability, and polarization diversity to mitigate multipath propagation. It also supports absolute 2D target localization using measurements from a single anchor node. The paper describes the antenna design, the implementation and the experimental characterization, along with its positioning applications. The localization results obtained with data collected from indoor measurements, showing an average localization error as low as 1.7 m.

Analysis of the indoor positioning performance of a switched six-beams dodecahedral antenna

In this paper we present the performance analysis of a switched six-beams dodecahedral antenna designed for indoor target localization. The localization technique is based on the estimation of the direction of arrival and makes use of the signal strenghts readings by each antenna beams. The analysis adoptes an indoor channel model by which we studied the localization accuracy varying the multipath parameters and the SNR of the radio link. The analysis has shown the impact on the localization accuracy of the mutual interaction between these two factors, and that to achieve an absolute error less than 1 m in the the 90% percentage of the area, a SNR=10 dB and Γ =.1 is required.