Roberto Morichetti

Bio: Roberto Morichetti is an academic researcher from Polytechnic University of Milan. The author has contributed to research in topics: Overhead (computing) & Ranging. The author has an hindex of 1, co-authored 1 publications receiving 11 citations.

Hybrid active and passive localization for small targets

Abstract: Ultra-Wideband (UWB) is an emerging technology for short-range wireless communications. Due to the high bandwidth of UWB signals, accurate ranging is possible, which is one of many reasons why UWB is a candidate physical layer for wireless sensor networks (WSNs). Reliable position information, obtained with a reasonable complexity overhead and possibly low energy consumption, is often paramount for a successful operation of these networks. The paper concerns a novel approach for improving the trade-off between energy consumption and performance in a localization tracking process. The scenario of application is common: a set of fixed beacons is used for tracking the position of a target that is moving in a limited indoor environment. The principle behind the proposed approach is relatively simple: tracking a small target device is realized by mixing active signal transmissions, which allow using standard techniques for deriving distances and locations, as well as passive signal receptions, which exploit scattering caused by small targets during signal propagation. The entire tracking process exploits the combination of these two types of transmissions with the advantage of possibly saving energy in the target device. The algorithm performance is highlighted by computer simulations using channel models adopted by the IEEE 802.15.4a working group.

Hybrid technique for indoor positioning system based on Wi-Fi received signal strength indication

Abstract: An indoor positioning system based on Receive Signal Strength Indication(RSSI) from wireless access equipment has become very popular in recent years. This system is very useful in many applications such as tracking service for older people or customer inside living communities, mobile robot localization, logistics systems etc. While outdoor environment using Global Navigation Satellite System(GNSS) and cellular network work well and are widespread used for navigation. However, there is a problem with signal propagation from satellites or cell site. They cannot be used effectively inside complex building areas or even in an urban environment. In general, the widely used method for indoor environment positioning based on Wi-Fi consists with two main categories, which are trilateration technique and location fingerprint technique(LF). It is already known that the explicit positioning performance of trilateration technique is more sensitive to noise effect than LF technique. Nevertheless, the accuracy of LF technique depends on training data set and it does not work well when environment changes. In this article, we propose the hybrid algorithm, the combination of the advantages of both systems, which is able to improve the accuracy stability and robustness. The performance of this algorithm is evaluated by the experimental results, which shows that our proposed scheme can achieve a certain level of positioning system accuracy.

UWB sensor radar networks for indoor passive navigation

Abstract: Localization and navigation of passive objects enables new important applications in wireless environments. Monostatic sensor radar networks generate interesting solutions for passive localization and navigation in a variety of scenarios. In particular, ultrawide band (UWB) sensing provides fine delay resolution enabling high localization accuracy even in harsh propagation environments such as indoor. We develop a framework for design and analysis of passive navigation based on UWB monostatic sensor radar networks that relies on propagation environment and time-of-arrival estimation characterized by network experiments. As a case study, an UWB monostatic sensor radar network deployed in an indoor environment is considered, and the position of moving objects is inferred. In particular, Bayesian navigation based on particle filters implementation is employed and the role of mobility model for inferring target position is shown.

UWB passive navigation in indoor environments

Abstract: Localization and navigation of passive target objects play a key role in many important applications. An interesting solution for passive localization and navigation is given by monostatic wireless sensor radar (WSR) networks. In this context, ultrawide band (UWB) radar provide fine delay resolution enabling high accuracy localization also in harsh environments such as indoor. We present a mathematical framework for analysis and design of passive navigation based on UWB monostatic WSRs that relies on environment propagation and time-of-arrival estimation characterized by network experiments. A case study where a UWB monostatic WSR network is deployed to infer the position of moving target objects is considered. In particular, Bayesian navigation based on particle filters implementation is analyzed and the role of mobility model for inferring target position is shown.

Localization method and system using non-regenerative UWB relays

Abstract: The present invention relates to a method and a system for determining the position of an object which can be a passive or an active tag (140). The system comprises a plurality of anchor nodes (111,112) and a plurality of non-regenerative relays (121,122,123) of known positions. In case of an active tag, a UWB pulse signal is emitted by the tag and received by the anchor nodes either directly or via a relay. In case of a passive tag, UWB pulse signals are sent by the anchors nodes and reflected back, either way being either a LOS path or a relayed path. A processing node (130) collects the signals received by the anchor nodes (111,112) to estimate the position of the tag.

Low-Complexity Localization and Tracking in Hybrid Wireless Sensor Networks

Abstract: Localization in Wireless Sensor Networks (WSNs) is an important research topic: readings come from sensors scattered in the environment, and most of applications assume that the exact position of the sensors is known. Due to power restrictions, WSN nodes are not usually equipped with a global positioning system—hence, many techniques have been developed in order to estimate the position of nodes according to some measurements over the radio channel. In this paper, we propose a new technique to track a moving target by combining distance measurements obtained from both narrowband IEEE 802.15.4 and Ultrawideband (UWB) radios, and then exploiting a novel speed-based algorithm for bounding the error. This process is applied to a real dataset collected during a measurement campaign, and its performance is compared against a Kalman filter. Results show that our algorithm is able to track target path with good accuracy and low computational impact.