Abstract: The performance of adaptive beamforming algorithms is known to degrade in a moving jammer environment.This degradation occurs due to the jammer motion that brings the interfering sources out of the sharp notches of the adapted pattern.In this paper, we consider a uni ed framework that allows tomake a broad class of adaptive array algorithms robust against jammer motion.The robustness is achieved by means of arti cially broadening the directional pattern null width in the jammer directions.For this purpose, we use a special type of data-dependent sidelobe derivative constraints that do not require any a priori information about the jammers. I. INTRODUCTIONThe performance of adaptive beamforming has been discussed for stationary (non-moving) jammer scenarios, [1],However, in the future fast moving platforms become more likely in various applications.The performance of adaptive arrays severely degrades if the weights are not able to adapt suf ciently fast to the changing jamming situation.Fast adaptation has therefore be the aim of research in these cases.Moving jammers represent a serious problem, because for large antennas the directional pattern nulls are extremely sharp and jammers may soon move out of the nulls, i.e. high gain antennas are very sensitive to this type of non-stationarity.Recently, a large number of robust adaptive beamforming methods has been studied [3],