Browse by author
Lookup NU author(s): Yogesh Nijsure, Dr Yifan Chen, Dr Zhiguo Ding, Professor Said Boussakta
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
A novel approach to optimizing the waveforms of an adaptive distributed multiple-input multiple-output (MIMO) radar is developed. The research work aims at improving the target detection and feature extraction performance by maximizing the mutual information (MI) between the target impulse response and the received echoes in the first step, and then minimizing the MI between successive backscatter signals in the second step. These two stages correspond to the design of the ensemble of excitations and the selection of a suitable signal out of the ensemble, respectively. The waveform optimization algorithm is based upon adaptive learning from the radar scene, which is achieved through a feedback loop from the receiver to the transmitter. This feedback includes vital information about the target features derived from the reflected pulses. In this way the transmitter adjusts its probing signals to suit the dynamically changing environment. Simulation results demonstrate better target response extraction using the proposed two-step algorithm as compared with each single-step optimization method. This approach also results in improved target detection probability and delay-Doppler resolution as the number of iterations increases.
Author(s): Nijsure Y, Chen Y, Yuen C, Chew YH, Ding Z, Boussakta S
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Aerospace and Electronic Systems
Year: 2013
Volume: 49
Issue: 2
Pages: 1374-1385
Print publication date: 01/04/2013
Online publication date: 16/11/2012
Acceptance date: 23/06/2012
ISSN (print): 0018-9251
ISSN (electronic): 1557-9603
Publisher: IEEE
URL: http://dx.doi.org/10.1109/TAES.2013.6494422
DOI: 10.1109/TAES.2013.6494422
Altmetrics provided by Altmetric
