Power Allocation Strategies for Target Localization in Distributed Multiple-Radar Architectures

• Published in: IEEE transactions on signal processing Vol. 59; no. 7; pp. 3226 - 3240
• Main Authors: Godrich, H, Petropulu, A P, Poor, H V
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.07.2011; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Allocations; Applied sciences; Architecture; Budgeting; Cramer-Rao bound (CRB); Detection, estimation, filtering, equalization, prediction; Estimation; Exact sciences and technology; Information, signal and communications theory; Localization; multiple-input multiple-output (MIMO) radar; multistatic radar; nonconvex optimization; Optimization; Parameter estimation; Position (location); Radar; Radar antennas; Radar cross section; Resource allocation; Resource management; Signal and communications theory; Signal, noise; Studies; target localization; Telecommunications and information theory; Performance evaluation; Parameter estimation; Non convex programming; Resource allocation; Decomposition method; nonconvex optimization; Power allocation; Optimization; Mean square error; Relaxation; Distributed processing; target localization; Localization; Target detection; Antenna; Cramer Rao inequality; MIMO system; multiple-input multiple-output (MIMO) radar; Cramer-Rao bound (CRB); Multistatic radar; Algorithm; Signal processing; Metric; Resource management; Domain decomposition

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 predetermined system performance...