3 research outputs found
On the Use of Reciprocal Filter against WiFi Packets for Passive Radar
This paper aims at a critical review of the signal processing scheme used in WiFi-based passive radar in order to limit its complexity and enhance its suitability for short range civilian applications. To this purpose the exploitation of a reciprocal filtering strategy is investigated as an alternative to conventional matched filtering at the range compression stage. Along with the well-known advantage of a remarkable sidelobes control capability for the resulting range-Doppler response, the use of a reciprocal filter is shown to provide additional benefits for the specific sensor subject of this study. Specifically, it allows to streamline the disturbance cancellation stage and to implement a unified signal processing architecture which is capable to handle the different modulation schemes typically adopted in WiFi transmissions. Appropriate adjustments are also proposed to the theoretical reciprocal filter in order to cope with the inherent loss in term of signal-to-noise power ratio. The effectiveness of the revised signal processing scheme encompassing the reciprocal filtering strategy is proved against both simulated and experimental datasets
Wireless Localization Systems: Statistical Modeling and Algorithm Design
Wireless localization systems are essential for emerging applications that rely on
context-awareness, especially in civil, logistic, and security sectors. Accurate localization in indoor environments is still a challenge and triggers a fervent research
activity worldwide. The performance of such systems relies on the quality of range
measurements gathered by processing wireless signals within the sensors composing
the localization system. Such range estimates serve as observations for the target
position inference. The quality of range estimates depends on the network intrinsic
properties and signal processing techniques. Therefore, the system design and analysis call for the statistical modeling of range information and the algorithm design
for ranging, localization and tracking. The main objectives of this thesis are: (i) the
derivation of statistical models and (ii) the design of algorithms for different wire-
less localization systems, with particular regard to passive and semi-passive systems
(i.e., active radar systems, passive radar systems, and radio frequency identification
systems). Statistical models for the range information are derived, low-complexity
algorithms with soft-decision and hard-decision are proposed, and several wideband
localization systems have been analyzed. The research activity has been conducted
also within the framework of different projects in collaboration with companies and
other universities, and within a one-year-long research period at Massachusetts Institute of Technology, Cambridge, MA, USA. The analysis of system performance,
the derived models, and the proposed algorithms are validated considering different case studies in realistic scenarios and also using the results obtained under the
aforementioned projects
Passive Radar via LTE Signals of Opportunity
Passive radars relying on signals of opportunity enable new applications based on stealth tracking of targets without the need of radar signals emissions. Long term evolution (LTE) base stations employing orthogonal frequency division multiplexing (OFDM) signals are excellent candidates as illuminators of opportunity thanks to their wide availability. The tracking accuracy of such passive radars depends on prior knowledge (e.g., the wireless environment) and signal processing (e.g., clutter mitigation and tracking algorithm). This paper proposes passive radar systems exploiting LTE base stations as illuminators of opportunity to detect and track moving targets in a monitored environment. We analyze such systems based on a Bayesian framework for detection of moving targets and estimation of their position and velocity. A case study accounting for the LTE extended pedestrian model is presented, with various settings in terms of network configuration, wireless propagation, and signal processing