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Information-theoretic algorithm for waveform optimization within ultra wideband cognitive radar network

Information-theoretic algorithm for waveform optimization within ultra wideband cognitive radar network

Nijsure, Y., Chen, Y., Rapajic, P., Yuen, C., Chew, Y.H. and Qin, T.F. (2010) Information-theoretic algorithm for waveform optimization within ultra wideband cognitive radar network. In: International Conference on Ultra-Wideband (ICUWB). IEEE International Conference on Ultra-Wideband (ICUWB) . IEEE Xplore Digital Library, Nanjing, pp. 1-4. ISBN 978-1-4244-5305-4 (print) ISSN 978-1-4244-5306-1 (online) (doi:https://doi.org/10.1109/ICUWB.2010.5616308)

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Abstract

A novel information-theoretic approach for designing the excitation ultra wideband (UWB) waveforms within a cognitive radar network is developed. This method utilizes the mutual information (MI) between subsequent radar returns to extract desired information from the radar scene. With this approach, the radar system constantly learns about its surroundings and adopts its operational mode accordingly based upon the MI minimization criterion. Subsequently, the positioning algorithm makes use of this information about the radar scene to generate more accurate location estimates. Numerical results demonstrate an improvement in the probability of target detection even at low values of receive signal-to-noise ratio (SNR). The proposed algorithm also promises a better delay-Doppler resolution of the target, which can be analyzed through the radar ambiguity function (AF). Simulation data show an improvement in the target discrimination ability in the presence of noise and clutter.

Item Type: Conference Proceedings
Title of Proceedings: International Conference on Ultra-Wideband (ICUWB)
Uncontrolled Keywords: information-theoretic approach, excitation ultra wideband (UWB) waveforms, cognitive radar network, mutual information (MI), positioning algorithm, signal-to-noise ratio (SNR), delay-Doppler resolution, ambiguity function (AF)
Subjects: Q Science > Q Science (General)
Q Science > QC Physics
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Pre-2014 Departments: School of Engineering
School of Engineering > Department of Civil Engineering
Related URLs:
Last Modified: 14 Oct 2016 09:19
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/7609

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