Robust adaptive beamforming algorithms using low-complexity mismatch estimation

We develop robust adaptive beamforming algorithms using low-complexity mismatch estimation (LOCME) of the array steering vector. The new feature is combined with the worst-case optimization-based beamformer, which can be solved as a second-order cone program (SOCP). In addition, we combine LOCME with a similar approach to the worst-case design using a joint optimization strategy based on the conjugate gradient method. The algorithms are developed in accordance with the constrained minimum variance design as well as the constrained constant modulus design criterion. While the LOCME feature does not affect the complexity order, the simulation results of all proposed algorithms show a superior performance, close to the optimum. Similarly to other mismatch estimation techniques, LOCME does not require additional information about the array steering vector mismatch. All proposed algorithms outperform the conventional worst-case optimization based algorithm, whereas the complexity is more than an order of magnitude lower, in case of the joint optimization-based approach.