Adaptive calibration in UWB radar

Gashinova, Marina; Djigan, Victor I.; Daniel, Liam; Cherniakov, M.

doi:10.1109/radar.2008.4720913

Cited by 4 publications

(4 citation statements)

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“…The effect of the transmitter and receiver response, A can be removed by an appropriate deconvolution with a calibration signal, for example the reflection from a metal plate [17], giving,…”

Section: Theoretical Discussionmentioning

confidence: 99%

A Comparison of Ultra Wide Band Conventional and Direct Detection Radar for Concealed Human Carried Explosives Detection

Harmer¹,

Bowring²,

Rezgui³

et al. 2013

PIER Letters

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This paper describes how information about the electromagnetic structure of targets can be obtained from direct detection radar techniques, where the relative phase of the transmitted and received signals is not measured. A comparison is made between the resolved structure of a simple test target from an ultra wide band, pulse synthesis direct detection radar system at 14-40 GHz and an equivalent heterodyne radar receiver where phase information is recorded. The test targets employed are wax sheet of thickness 20 mm and 80 mm which are illuminated alone and in contact with the human body. A vector network analyser is used as the radar system. The simplicity of constructing ultra wide band direct detection radar systems combined with their cost makes the use of such radar systems appealing for applications such as concealed threat detection and non-destructive testing, where absolute range to the target, if required, can be determined by other methods.

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Section: Theoretical Discussionmentioning

confidence: 99%

A Comparison of Ultra Wide Band Conventional and Direct Detection Radar for Concealed Human Carried Explosives Detection

Harmer¹,

Bowring²,

Rezgui³

et al. 2013

PIER Letters

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“…However, in this work, we assume a digital frequency equalization mechanism at the receiver as suggested by works such as [52]. The calculation for the time delay τ range at the receiver for the UWB-MIMO radar is as follows:…”

Section: Appendix a Key Signal Model Assumptions And Limitationsmentioning

confidence: 99%

“…It is evident from this expression that the estimated delay τ range can be obtained by detection of the maximum of the output of the matched filter. For the UWB case, this cross-correlation operation can be carried out following the digital-frequency-equalization-based calibration described in [52]. Such an approach is based on UWB radar channel calibration, which compensates for the frequency-selective distortion on distinct UWB channels, thus making the convolution h m,n * x m (t) dependent only on the frequency-independent complex constant h m,n .…”

Section: Appendix a Key Signal Model Assumptions And Limitationsmentioning

confidence: 99%

“…Such an approach is based on UWB radar channel calibration, which compensates for the frequency-selective distortion on distinct UWB channels, thus making the convolution h m,n * x m (t) dependent only on the frequency-independent complex constant h m,n . Such a calibration is carried out prior to operating it within the target scene [52]. Other works utilizing UWB-MIMO radars [53,54] have made similar assumptions that allow us to approximate h m,n by a frequency-independent complex constant.…”

Section: Appendix a Key Signal Model Assumptions And Limitationsmentioning

confidence: 99%

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Cognitive chaotic UWB-MIMO radar based on nonparametric Bayesian technique

Nijsure

Kaddoum

Leung

2015

IEEE Trans. Aerosp. Electron. Syst.

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This work presents a cognitive waveform selection mechanism for chaotic ultra-wideband multiple-input multiple-output (MIMO) radars. It utilizes the target discrimination capability of a Dirichlet process mixture model (DPMM)-based clustering approach to discriminate individual extended targets and applies a mutual information (MI)-based mechanism to select the best transmission waveform. This joint DPMM-MI cognitive mechanism aims at enhancing target discrimination and detection, showing a 3-dB performance gain in achieving 0.9 target detection probability over conventional MIMO radar waveforms. . His research interests include cognitive radar network design, Bayesian nonparametric methods, UWB radar systems, robust ADS-B multilateration systems, cognitive radio networks, information theory, radar signal processing, electronic warfare, and software-defined radio systems. Georges Kaddoum is an assistant professor of electrical engineering at Ecole de technologie superieure (ETS), University of Quebec, Montreal, Quebec, Canada. He received his bachelor's degree in electrical engineering from Ecole nationale superieure de techniques avancees, Bretagne, and his M.S. degree in telecommunications and signal processing (circuits, systems, and signal processing) from the Universite de Bretagne Occidentale and Telecom Bretagne, Brest, France, in September 2005. In December 2008, he earned his Ph.D. degree in signal processing and telecommunications with honors from the National Institute of Applied Sciences, University of Toulouse, France. He was a scientific researcher at ETS in 2012 and then promoted to assistant professor in November 2013. In 2014, he was awarded the ETS research chair in physical layer security for wireless networks. In addition, he was a recipient of the Best Paper Award at the IEEE International conference Wireless and Mobile Computing, Networking and Communications (WiMob 2014) with three other coauthors. His recent research activities cover wireless communication systems, chaotic modulations, secure transmissions, and space communications and navigation. He has published over 60 journal and conference papers and has held two pending patents. Since 2010, has has been working as a scientific consultant in the field of space and wireless telecommunications with several companies (Intelcan Techno-systems, MDA Corporation, and Radio-IP companies). Henry Leung (F'15) received his Ph.D. degree in electrical and computer engineering from McMaster University, Hamilton, Ontario, Canada. He is now a professor of the Before that, he was with the Defence Research Establishment, Ottawa, Ontario, Canada, where he was involved in the design of automated systems for air and maritime multisensor surveillance. His research interests include chaos, computational intelligence, information fusion, data mining, robotics, sensor networks, and wireless communications.

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