Optimal Joint Target Detection and Parameter Estimation By MIMO Radar
Ali Tajer, Guido H. Jajamovich, Xiaodong Wang, and George V., Moustakides

TL;DR
This paper introduces a novel MIMO radar framework that jointly detects targets and estimates their parameters, specifically time-delays, demonstrating significant advantages over phased-array radars for extended targets.
Contribution
It proposes a new composite hypothesis testing approach for joint detection and parameter estimation in MIMO radar systems with limited observations.
Findings
MIMO radars outperform phased-array radars for extended targets.
Detection and estimation accuracies are comparable for point targets.
The framework effectively balances detection and estimation performance.
Abstract
We consider multiple-input multiple-output (MIMO) radar systems with widely-spaced antennas. Such antenna configuration facilitates capturing the inherent diversity gain due to independent signal dispersion by the target scatterers. We consider a new MIMO radar framework for detecting a target that lies in an unknown location. This is in contrast with conventional MIMO radars which break the space into small cells and aim at detecting the presence of a target in a specified cell. We treat this problem through offering a novel composite hypothesis testing framework for target detection when (i) one or more parameters of the target are unknown and we are interested in estimating them, and (ii) only a finite number of observations are available. The test offered optimizes a metric which accounts for both detection and estimation accuracies. In this paper as the parameter of interest we…
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