Signal processing for improved detection of trapped victims using uwb radar

A Nezirovic, A Yarovoy, LP Ligthart

    Research output: Contribution to journalArticleScientificpeer-review

    125 Citations (Scopus)

    Abstract

    Detection of trapped victims using ultrawideband radar is considered a highly challenging task due to multiple unknown parameters and generally very low signal-to-noise-and-clutter ratio (SNCR) conditions. In this paper, we propose a novel detection algorithm which is designed for detection of periodic motion caused by, e.g., respiratory motion of the victim for low SNCR conditions. The aim is to separate the respiratory-motion response of a trapped victim from nonstationary clutter originating from moving objects in the scene of interest. The algorithm performs stationary-clutter removal, high-level noise, and nonstationary-clutter suppression, indicates presence of the trapped victim, and estimates its range. The performance of the algorithm is investigated, both by means of simulation and experimental verification. The results show improved detection capabilities in low SNCR over an existing algorithm proposed by Zaikov et al.
    Original languageEnglish
    Pages (from-to)2005-2014
    Number of pages10
    JournalIEEE Transactions on Geoscience and Remote Sensing
    Volume48
    Issue number4
    DOIs
    Publication statusPublished - 2010

    Keywords

    • CWTS 0.75 <= JFIS < 2.00

    Fingerprint Dive into the research topics of 'Signal processing for improved detection of trapped victims using uwb radar'. Together they form a unique fingerprint.

    Cite this