Matrix analysis
Convex Optimization
Complex Matrix Decomposition and Quadratic Programming
Mathematics of Operations Research
Design of phase codes for radar performance optimization with a similarity constraint
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Code Design to Optimize Radar Detection Performance Under Accuracy and Similarity Constraints
IEEE Transactions on Signal Processing
Quality of Service and Max-Min Fair Transmit Beamforming to Multiple Cochannel Multicast Groups
IEEE Transactions on Signal Processing
Polyphase Barker sequences up to length 36
IEEE Transactions on Information Theory
Optimal transmit-receiver design in the presence of signal-dependent interference and channel noise
IEEE Transactions on Information Theory
A Near-Maximum-Likelihood Decoding Algorithm for MIMO Systems Based on Semi-Definite Programming
IEEE Transactions on Information Theory
Rank-constrained separable semidefinite programming with applications to optimal beamforming
IEEE Transactions on Signal Processing
A Doppler robust max-min approach to radar code design
IEEE Transactions on Signal Processing
Optimization of radar phase-coded signals for multiple target detection
Signal Processing
Hi-index | 35.70 |
In this paper, we deal with the problem of constrained code optimization for radar space-time adaptive processing (STAP) in the presence of colored Gaussian disturbance. At the design stage, we devise a code design algorithm complying with the following optimality criterion: maximization of the detection performance under a control on the regions of achievable values for the temporal and spatial Doppler estimation accuracy, and on the degree of similarity with a pre-fixed radar code. The resulting quadratic optimization problem is solved resorting to a convex relaxation that belongs to the semidefinite program (SDP) class. An optimal solution of the initial problem is then constructed through a suitable rank-one decomposition of an optimal solution of the relaxed one. At the analysis stage, we assess the performance of the new algorithm both on simulated data and on the standard challenging the Knowledge-Aided Sensor Signal Processing and Expert Reasoning (KASSPER) datacube.