Detection, localization and tracking of non-collaborative objects moving inside an area is of great interest to many surveillance applications. An ultra-
wideband (UWB) multistatic radar is considered as a good infrastructure
for such anti-intruder systems, due to the high range resolution provided by
the UWB impulse-radio and the spatial diversity achieved with a multistatic
configuration.
Detection of targets, which are typically human beings, is a challenging
task due to reflections from unwanted objects in the area, shadowing, antenna
cross-talks, low transmit power, and the blind zones arised from intrinsic peculiarities of UWB multistatic radars.
Hence, we propose more effective detection, localization, as well as clutter
removal techniques for these systems. However, the majority of the thesis
effort is devoted to the tracking phase, which is an essential part for improving
the localization accuracy, predicting the target position and filling out the
missed detections.
Since UWB radars are not linear Gaussian systems, the widely used tracking filters, such as the Kalman filter, are not expected to provide a satisfactory performance. Thus, we propose the Bayesian filter as an appropriate
candidate for UWB radars. In particular, we develop tracking algorithms
based on particle filtering, which is the most common approximation of
Bayesian filtering, for both single and multiple target scenarios. Also, we
propose some effective detection and tracking algorithms based on image
processing tools.
We evaluate the performance of our proposed approaches by numerical
simulations. Moreover, we provide experimental results by channel measurements for tracking a person walking in an indoor area, with the presence of a
significant clutter. We discuss the existing practical issues and address them by proposing more robust algorithms.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:6796 |
| Date | 22 May 2015 |
| Creators | Sobhani, Bita <1981> |
| Contributors | Chiani, Marco |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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