Synthetic aperture processing for passive co-prime linear sensor arrays

In this paper, we explore the use of synthetic aperture processing for optimizing the spatial covariance estimation capabilities of a moving linear co-prime sensor array. The linear co-prime sensor array geometry is a thinned linear array that is constructed by nesting uniform linear arrays with inter-related element spacing factors. The application of synthetic aperture processing in this setting is designed to create virtual sensors at missing half-wavelength intervals up to the degree required to produce a hole-free difference co-array across the full aperture of the synthetic array. Once a full set of spatial covariances are estimated covariance matrix based array processing methods can be applied as if the synthetic array were a uniform linear array. In this sense, the synthetic array is designed to approximate a uniform linear array while it retains a thinned linear array structure. We show simulation results examining the quality of the uniform linear array approximation afforded by this application synthetic aperture processing. (C) 2016 Elsevier Inc. All rights reserved.