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Proceedings Paper

SIRE: a MIMO radar for landmine/IED detection
Author(s): Ode Ojowu; Yue Wu; Jian Li; Lam Nguyen
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Paper Abstract

Multiple-input multiple-output (MIMO) radar systems have been shown to have significant performance improvements over their single-input multiple-output (SIMO) counterparts. For transmit and receive elements that are collocated, the waveform diversity afforded by this radar is exploited for performance improvements. These improvements include but are not limited to improved target detection, improved parameter identifiability and better resolvability. In this paper, we present the Synchronous Impulse Reconstruction Radar (SIRE) Ultra-wideband (UWB) radar designed by the Army Research Lab (ARL) for landmine and improvised explosive device (IED) detection as a 2 by 16 MIMO radar (with collocated antennas). Its improvement over its SIMO counterpart in terms of beampattern/cross range resolution are discussed and demonstrated using simulated data herein. The limitations of this radar for Radio Frequency Interference (RFI) suppression are also discussed in this paper. A relaxation method (RELAX) combined with averaging of multiple realizations of the measured data is presented for RFI suppression; results show no noticeable target signature distortion after suppression. In this paper, the back-projection (delay and sum) data independent method is used for generating SAR images. A side-lobe minimization technique called recursive side-lobe minimization (RSM) is also discussed for reducing side-lobes in this data independent approach. We introduce a data-dependent sparsity based spectral estimation technique called Sparse Learning via Iterative Minimization (SLIM) as well as a data-dependent CLEAN approach for generating SAR images for the SIRE radar. These data-adaptive techniques show improvement in side-lobe reduction and resolution for simulated data for the SIRE radar.

Paper Details

Date Published: 31 May 2013
PDF: 8 pages
Proc. SPIE 8714, Radar Sensor Technology XVII, 87140O (31 May 2013); doi: 10.1117/12.2015618
Show Author Affiliations
Ode Ojowu, Univ. of Florida (United States)
Yue Wu, Univ. of Florida (United States)
Jian Li, Univ. of Florida (United States)
Lam Nguyen, U.S. Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 8714:
Radar Sensor Technology XVII
Kenneth I. Ranney; Armin Doerry, Editor(s)

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