Paper Info
Title
Multitarget Detection Strategy for Distributed MIMO Radar With Widely Separated Antennas
Abstract
In this article, we propose a novel solution to detect multiple targets using a distributed multiple-input multiple-output (MIMO) radar under the so-called "defocused transmit-defocused receive" operating mode. The proposed method employs a grid-based data matching algorithm, aiming to associate the target responses to potential target locations, solving the resulting data puzzle that evaluates the various cells under test (CUTs) in the surveillance area resulting from the intertwined range cells across all transmit-receive channels. Sketchily, the approach divides the surveillance area into identically interlocking and analytically expressible grid cells and then selects the grid cells with the best fitting multichannel data to be equivalently regarded as the CUTs. Next, the generalized likelihood ratio test (GLRT) detector is derived to test for target presence in each of the selected grid cells. A separate procedure is introduced to eliminate the spurious "shadow targets," false alarms occurring in the grid cells without a target while sharing range cells with the targets. The essence of this procedure is to find the source of the observed contributions to the grid cells whose test statistics exceed their thresholds, and simultaneously obtain the positions of the targets. The proposed method is evaluated using both numerical simulations and experimental data recorded by five small radars, demonstrating the effectiveness of the proposed technique.
Year
DOI
Venue
2022
10.1109/TGRS.2022.3175046
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Keywords
DocType
Volume
MIMO radar, Detectors, Surveillance, Radar, Radar detection, Receiving antennas, Probability density function, Distributed multiple-input multiple-output (MIMO) radar, generalized likelihood ratio test (GLRT) detector, multitarget detection
Journal
60
ISSN
Citations 
PageRank 
0196-2892
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Shixing Yang100.34
Wei Yi225236.97
Andreas Jakobsson340943.32