Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Convex Optimization
Foundations of Electromagnetic Theory (4th Edition)
Foundations of Electromagnetic Theory (4th Edition)
Adaptive Polarized Waveform Design for Target Tracking Based on Sequential Bayesian Inference
IEEE Transactions on Signal Processing
Polarimetric Detection of Targets in Heavy Inhomogeneous Clutter
IEEE Transactions on Signal Processing
Waveform selection in radar target classification
IEEE Transactions on Information Theory
Polarimetric MIMO radar with distributed antennas for target detection
IEEE Transactions on Signal Processing
Polarimetric MIMO radar with distributed antennas for target detection
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Game theoretic design for polarimetric MIMO radar target detection
Signal Processing
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Controlling the polarization information in transmitted waveforms enables improving the performance of radar systems. We consider the design of optimal polarizations at both the radar transmitter and receiver for the estimation of target scattering embedded in clutter. The goal is to minimize the mean squared error of the scattering estimation subject to an average radar pulse power constraint. Under the condition that the target and clutter scattering covariance matrices are known a priori, we show that such a problem is equivalent to the optimal design of a radar sensing matrix that contains the polarization information. We formulate the optimal design as a nonlinear optimization problem and then recast it in a convex form and is thus efficiently solvable by semi-definite programming (SDP). We compare the sensing performance of the optimally selected polarization over conventional approaches. Our numerical results demonstrate that a significant amount of power gain is achieved in the target scattering estimation through such an optimal design.