Partially-adaptive array design using the singular value decomposition

The objective of partially-adaptive array design is to reduce the number of adaptive weights without significantly degrading the performance of the adaptive array. Previous work includes numerical techniques for approximately minimizing the average generalized sidelobe canceller (GSC) output power for a desired number of adaptive weights, where the average is over a range of jammer parameters. Our new approach also minimizes the average GSC output power, but under the constraint that the reduced-dimensional solutions for all of the scenario trials lie in the same subspace. This constraint allows us to use the singular value decomposition to get the solution, thereby simplifying the optimization problem. Although the subspace constraint yields a theoretically suboptimum solution, the solution yields lower output power in comparison with a previously reported example that used the numerical methods. Also, the simplicity of the method allows large ranges of jammer parameters to be considered. Computer simulations are given to demonstrate effectiveness.