Cognitive Radar Waveform Design with Low PSL Against Out-of-Band Interference in Spectrally Crowded Environments

To improve the weak target detection capability and suppress the scattering energy in out-of-band spectrum as well as congestion spectrum of cognitive radar, the radar waveform needs to possess good autocorrelation properties and ideal frequency energy distribution. Therefore, we established a min-max biobjective function optimization problem. To solve this problem, we employed <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$l_{p}$</tex>-norm to convert the min-max problem into a min problem. The simplified optimization function remains nonconvex and difficult to solve, so we designed an alternating direction multiplier method based on iterative majorization minimization (MM-ADMM). Numerical simulation results show that the proposed algorithm has good convergence characteristics and has advantages over existing algorithm.