Sidelobe Level of an Adaptive Array Using the SMI (Sampled Matrix Inversion) Algorithm

摘要

The transient sidelobe level of an adaptive array is a function of the external noise environment, the number of adaptive antenna elements, the adaptive algorithm employed, auxiliary antenna gain margins, and the number of samples used to calculate the adaptive weights. In this report, an analytical result for the adaptive sidelobe level is formulated for when the adaptive algorithm is the open-loop Sampled Matrix Inversion (SMI) algorithm. This result is independent of whether the SMI algorithm is implemented using concurrent or nonconcurrent data processing. It is shown that the transient sidelobe level is eigenvalue dependent and increases proportionally to the gain margin of the auxiliary antenna elements with respect to the quiescent main antenna sidelobe level. Techniques that reduce this transient sidelobe level are discussed, and it is theoretically shown (as other researchers have discovered) that injecting independent noise into the auxiliary channels significantly reduces the transient sidelobe level. Also it is demonstrated that using this same technique reduces the SMI noise power residue settling time. Keywords: Electronic counter countermeasures; Adaptive filter; Radar; Adaptive cancellation.