1D and 2D algorithmically optimized sparse arrays

A new criterion, minimization of maximal weighted sidelobe, is applied together with a genetic search algorithm to the problem of element placement in a discrete linear lattice. By processing RF-data the resulting 1D sparse arrays are compared experimentally with sparse periodic arrays and arrays found with a least square optimization criterion The images show that algorithmically optimized layouts can be found with lateral resolution and contrast comparable to sparse periodic arrays. The approach has been extended to 2D arrays. An example is given without overlap between elements on transmit and receive. The layout is optimized for both the visible and invisible region to assure a controlled behavior when steering is applied. Advantages of this approach are that it gives flexibility in the choice of beamwidth, the potential to trade off beamwidth, maximum sidelobe level and sidelobe energy, no need for apodization, and possibility to require e.g. no overlap between receive and transmit elements.