In this paper, two resource allocation schemes for multiple radar systems are proposed. The first approach fully utilizes all available infrastructure in the localization process, i.e., all transmit and receive radars, while minimizing the total transmit energy. The power allocation among the transmit radars is optimized such that a predefined estimation mean-square error (MSE) objective is met, while keeping the transmitted power at each station within an acceptable range. The second scheme minimizes the number of transmit and receive radars employed in the estimation process by effectively choosing a subset of radars such that the required MSE performance threshold is attained. In the latter, the transmit antennas are assumed to fully utilize the admissible power range. The Cramer-Rao bound (CRB), which is known to be asymptotically tight to the maximum likelihood estimator (MLE) MSE at high signal-to-noise ratio (SNR), is used as an optimization metric for the estimation MSE. Subset selection is implemented through a heuristic algorithm, offering reduced computational cost compared with an exhaustive search.
[1]
Stephen P. Boyd,et al.
Convex Optimization
,
2004,
Algorithms and Theory of Computation Handbook.
[2]
H. Vincent Poor,et al.
An Introduction to Signal Detection and Estimation
,
1994,
Springer Texts in Electrical Engineering.
[3]
M. Skolnik,et al.
Introduction to Radar Systems
,
2021,
Advances in Adaptive Radar Detection and Range Estimation.
[4]
Kristine L. Bell,et al.
Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
,
2007
.
[5]
Victor S. Chernyak,et al.
Fundamentals of multisite radar systems
,
1998
.
[6]
Alexander M. Haimovich,et al.
Target Localization Accuracy Gain in MIMO Radar-Based Systems
,
2008,
IEEE Transactions on Information Theory.
[7]
Rick S. Blum,et al.
Concepts and Applications of a MIMO Radar System with Widely Separated Antennas
,
2009
.