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|Title: ||Game theoretic analysis for MIMO radars with multiple targets|
|Authors: ||Deligiannis, Anastasios|
|Issue Date: ||2016|
|Citation: ||DELIGIANNIS, A., LAMBOTHARAN, S. and CHAMBERS, J., 2016. Game theoretic analysis for MIMO radars with multiple targets. IEEE Transactions on Aerospace and Electronic Systems, 52 (4), pp. 1855 - 1865.|
|Abstract: ||This paper considers a distributed beamforming
and resource allocation technique for a radar system in the
presence of multiple targets. The primary objective of each
radar is to minimize its transmission power while attaining an
optimal beamforming strategy and satisfying a certain detection
criterion for each of the targets. Therefore, we use convex
optimization methods together with noncooperative and partially
cooperative game theoretic approaches. Initially, we consider
a strategic noncooperative game (SNG), where there is no
communication between the various radars of the system. Hence
each radar selfishly determines its optimal beamforming and
power allocation. Subsequently, we assume a more coordinated
game theoretic approach incorporating a pricing mechanism.
Introducing a price in the utility function of each radar/player,
enforces beamformers to minimize the interference induced to
other radars and to increase the social fairness of the system.
Furthermore, we formulate a Stackelberg game by adding a
surveillance radar to the system model, which will play the role of
the leader, and hence the remaining radars will be the followers.
The leader applies a pricing policy of interference charged to the followers aiming at maximizing his profit while keeping the
incoming interference under a certain threshold. We also present
a proof of the existence and uniqueness of the Nash Equilibrium
(NE) in both the partially cooperative and noncooperative games.
Finally, the simulation results confirm the convergence of the
algorithm in all three cases.|
|Description: ||This work is licensed under a Creative Commons Attribution 3.0 License.
For more information, see http://creativecommons.org/licenses/by/3.0.|
|Sponsor: ||This work was supported by the Engineering and Physical
Sciences Research Council (EPSRC) Grant number
EP/K014307/1 and the MOD University Defence Research
Collaboration (UDRC) in Signal Processing.|
|Publisher Link: ||http://dx.doi.org/10.1109/TAES.2016.150699|
|Appears in Collections:||Published Articles (Mechanical, Electrical and Manufacturing Engineering)|
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