A combinatorial optimization framework for subset selection in distributed multiple-radar architectures

Abstract—Widely distributed multiple radar architectures offer parameter estimation improvement for target localization. For a large number of radars, the achievable localization minimum estimation mean-square error (MSE), with full resource allocation, may extend beyond the system predetermined performance goals. In this paper, a performance driven resource allocation scheme for multiple radar systems is proposed. The number of transmit and receive radars employed in the estimation process is minimized by effectively selecting a subset of active radars such that the required MSE performance threshold is attained. As the goal is to obtain a performance level with the lowest cost, in terms of active system elements, the problem is formulated in a combinatorial optimization framework as a knapsack problem (KP). The Cramer-Rao bound (CRB) is used as a performance metric. Cost parameters, representing operational cost or any other utilization constraints on the radars, are associated wit...

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Hana Godrich, Athina P. Petropulu, H. Vincent Poor
• Keywords: ICASSP 2011, Multiple Radar, Performance, Radars, Signal Processing