Antenna designers often employ linearly constrained adaptive beamforming as an antijamming measure. With minimal a priori knowledge of the signal environment, this technique nulls out jammers while simultaneously preserving the quality of the main lobe so that a friendly look-direction signal can be received with unity gain. Unfortunately, in the absence of special strategies, linearly constrained adaptive beamforming is hypersensitive to array imperfections when the input signal-to-noise ratio exceeds a certain threshold. This hypersensitivity manifests itself as a nailing of the friendly signal as if it were a jammer. Luckily, the signal nulling problem can be easily remedied by artificial receiver noise injection. A particularly simple and general structure for linearly constrained adaptive beamforming was proposed during the 1970\´s, and is known as the generalized sidelobe canceller. A detailed analysis of the generalized sidelobe canceller in the presence of array imperfections is discussed, and two new artificial receiver noise injection algorithms are proposed. Computer simulations are included to demonstrate that use of these new algorithms alleviates the signal nailing problem without seriously compromising jammer nulling. For the special case of the Capon maximum-likelihood beamformer, simple approximations are presented for: 1) the Wiener output signal-to-interference-plus-noise ratio (

), 2) the antenna element error variance that causes a 3 dB loss of

from its value for an ideal array, and 3) the optimal artificial receiver noise that maximizes

.