Research On Robust Low Sidelobe Adaptive Beamforming Algorithm

Adaptive beamforming is an important part in array signal processing and has been widely used in many fields such as radar,sonar and smart antenna.However,under the circumstance of complex electromagnetic environment,there will inevitably exist model mismatch such as steering vector mismatch or covariance matrix mismatch.These mismatches seriously affect the performance of the beamformer.In addition,if the sidelobe level of the beam is too high,it will reduce the target detection performance,low interception performance and anti-interference performance.Therefore,it is of great theoretical significance and application value to study the robust adaptive beamforming with low sidelobe under various mismatch conditions.In this paper,classical robust beamforming algorithms are analyzed based on the spatial array signal processing model.However,these algorithms have different defects in solving the mismatch problem and can not accurately control the sidelobe level of the beam to meet the practical application requirement.In order to control the sidelobe level,MVDR beamforming with low sidelobe algorithm is proposed.By adding multiple quadratic inequality constraints to the MVDR optimization model and using the convex optimization method to solve the problem,the sidelobe level of the beam is precisely controlled.Because of MVDR beamforming with low sidelobe lacking robustness to steering vector mismatch,two robust beamforming with low sidelobe algorithms are researched.First one corrects the steering vector based on the iterative method and second one estimates steering vector directly.Especially the latter,it only needs to know the incidence range of the signal to estimate the desired signal steering vector directly.In order to remove the desired signal component from the received signal,an algorithm based on interference and noise covariance matrix reconstruction is proposed.The steering vector is corrected by maximizing the output power.Then the MVDR beamforming with low sidelobe is modified by the corrected covariance matrix and steering vector.In order to reduce the sidelobe level more,robust beamforming with low sidelobe algorithm based on modified objective function is proposed.The robustness against steering vector mismatch and covariance matrix mismatch is improved and the performance of the beamformer is ensured.