Partitioning of long linear arrays into a number of smaller subsections, termed subarrays, is a common form of processing used both to compensate for irregularity in array shape and to localize near-field sources. While this manner of processing is applicable to uniform linear arrays, as the subarrays are similarly uniform and possess the same minimum element spacing, subarray methods cannot always be applied to sparse arrays with uneven spacing along their length. One sparse array design of interest is the extended coprime array, an array composed of two uniformly spaced component arrays, each undersampled by integer factors which are selected to be coprime. By exploiting the regularity of spatial lag repetitions in extended coprime arrays, we show that appropriately selected subsections of a coprime array can be used as subarrays to determine distance to a near-field source. The performance of the coprime array processed in this manner will be compared to similar processing performed on alternative sparse array designs and the baseline performance of a uniform linear array of equal aperture.