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 non cooperative games. Finally, the simulation results confirm the convergence of the algorithm in all three cases.
Highlights
Multiple-input multiple-output (MIMO) radar is an innovative technology that has raised expectations over the last decade that it will provide substantial improvements to the currently used radar systems
There are two principal MIMO radar schemes considered in the literature, the systems incorporating colocated antennas and those that consist of widely separated antennas [2, 3]
In this paper, inspired by the aforementioned game theoretic methods applied in communications [10,11,12,13,14], reinvestigated to adapt to the radar case, we have developed a broad game theoretic analysis for the optimal beamforming and resource allocation problem in a MIMO tracking radar system with multiple targets
Summary
Multiple-input multiple-output (MIMO) radar is an innovative technology that has raised expectations over the last decade that it will provide substantial improvements to the currently used radar systems. The main characteristic that allows MIMO radar to offer superior capabilities as compared with other radar regimes is its waveform diversity, which implies that MIMO radar can use multiple antennas to simultaneously transmit several orthogonal waveforms and multiple antennas to receive the reflected signals from the targets [1]. The leading fields of research within MIMO radar technology are beamformer and waveform design, detection optimization, and radar imaging [4,5,6]. Succeeding the advances in those fields, the main advantages offered by MIMO radar are higher angular resolution, direct applicability of adaptive array techniques, multiple target detection, and the ability to obtain spatial diversity in the target’s radar cross section (RCS). Game theory is a natural and effective tool for modeling this kind of interactions, as it offers a mathematical framework of conflict and cooperation between intelligent, self-interested, and rational players
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Aerospace and Electronic Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
