Sparse sensor arrays can match the performance of fully populated arrays in many tasks, such as direction-of-arrival estimation, using substantially fewer elements. However, finding the sparse array configuration that uses the smallest number of elements is generally a hard problem. Consequently, several closed-form, but sub-optimal solutions have been developed in the past. These designs are typically specified for a given number of elements, although when the area occupied by the array is the main limitation, it is more convenient to compare arrays of similar aperture instead. This paper outlines procedures for synthesizing three sparse linear array geometries for a specified aperture, namely the Wichmann, Nested and Super nested array. These configurations are compared to the optimal Minimum-redundancy array and their deviation from optimality is quantified in the limit of large apertures.