TY - JOUR
T1 - Code design to optimize radar detection performance under accuracy and similarity constraints
AU - De Maio, Antonio
AU - De Nicola, Silvio
AU - Huang, Yongwei
AU - Zhang, Shuzhong
AU - Farina, Alfonso
PY - 2008
Y1 - 2008
N2 - This paper deals with the design of coded waveforms which optimize radar performances in the presence of colored Gaussian disturbance. We focus on the class of linearly coded pulse trains and determine the optimum radar code according to the following criterion: maximization of the detection performance under a control on the region of achievable Doppler estimation accuracies, and imposing a similarity constraint with a prefixed radar code. This last constraint is tantamount to requiring a similarity between the ambiguity functions of the devised waveform and of the pulse train encoded with the prefixed sequence. The resulting optimization problem is nonconvex and quadratic. In order to solve it, we propose a technique (with polynomial computational complexity) based on the relaxation of the original problem into a semidefinite program. Thus, the best code is determined through a rank-one decomposition of an optimal solution of the relaxed problem. At the analysis stage, we assess the performance of the new encoding technique in terms of detection performance, region of achievable Doppler estimation accuracies, and ambiguity function.
AB - This paper deals with the design of coded waveforms which optimize radar performances in the presence of colored Gaussian disturbance. We focus on the class of linearly coded pulse trains and determine the optimum radar code according to the following criterion: maximization of the detection performance under a control on the region of achievable Doppler estimation accuracies, and imposing a similarity constraint with a prefixed radar code. This last constraint is tantamount to requiring a similarity between the ambiguity functions of the devised waveform and of the pulse train encoded with the prefixed sequence. The resulting optimization problem is nonconvex and quadratic. In order to solve it, we propose a technique (with polynomial computational complexity) based on the relaxation of the original problem into a semidefinite program. Thus, the best code is determined through a rank-one decomposition of an optimal solution of the relaxed problem. At the analysis stage, we assess the performance of the new encoding technique in terms of detection performance, region of achievable Doppler estimation accuracies, and ambiguity function.
KW - Nonconvex quadratic optimization
KW - Radar signal processing
KW - Semidefinite programming relaxation
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U2 - 10.1109/TSP.2008.929657
DO - 10.1109/TSP.2008.929657
M3 - Article
AN - SCOPUS:54949104675
SN - 1053-587X
VL - 56
SP - 5618
EP - 5629
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 11
ER -