Sidelobe reduction in a random spherical volumetric array using frequency diversity

This paper presents a technique for reducing the average sidelobe level of a random spherical volume array using frequency diversity. The technique combines data obtained at several discrete measurement frequencies over a wide bandwidth. By using appropriate signal processing the measured data can be combined to produce an array response with an average sidelobe level that is significantly lower than that obtained at a single frequency. It is applicable to broadband blind-source location estimation and can be used to enhance holographic imaging. Experimental holographic imaging results are presented to validate the method which provides superior image resolution by reducing noise from unwanted directions. Furthermore, this technique can be used in addition to other sidelobe suppression methods such as amplitude tapers.