In this paper, we aim at improving the estimation performance of the direction of arrival (DOA) in a colocated MIMO radar through power allocation under the sparsity constraints. Specifically, by considering the sparse recovery techniques, we try to minimize the coherence of associated sensing matrix by optimally distributing the power among transmit antennas. To determine the optimal power distribution, we reformulate the coherence minimization problem and derive a convex optimization constrained by the total power budget. This helps us to efficiently evaluate and simulate the optimal power distribution policy. Simulation results confirm superiority of the proposed method compared to the existing techniques.
An approach to power allocation in MIMO radar with sparse modeling for coherence minimization / Ajorloo, A.; Amini, A.; Bastani, M. H.. - 2017-:(2017), pp. 1927-1931. ( 25th European Signal Processing Conference, EUSIPCO 2017 Kos International Convention Center, grc ) [10.23919/EUSIPCO.2017.8081545].
An approach to power allocation in MIMO radar with sparse modeling for coherence minimization
Ajorloo A.
;
2017
Abstract
In this paper, we aim at improving the estimation performance of the direction of arrival (DOA) in a colocated MIMO radar through power allocation under the sparsity constraints. Specifically, by considering the sparse recovery techniques, we try to minimize the coherence of associated sensing matrix by optimally distributing the power among transmit antennas. To determine the optimal power distribution, we reformulate the coherence minimization problem and derive a convex optimization constrained by the total power budget. This helps us to efficiently evaluate and simulate the optimal power distribution policy. Simulation results confirm superiority of the proposed method compared to the existing techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


