S-LRLA: A New Kind of Low Redundant Linear Array

As a notable sparse array, low redundant linear array (LRLA) plays an important role in lots of areas, especially in the areas of passive synthetic aperture imaging and direction-of-arrival (DOA) estimation. The existing LRLAs have a problem that they generally contain some dense segments of unit-spaced elements, which restricts the element aperture and hence the radiometric sensitivity and simultaneously causes serious mutual coupling effect that deteriorates the array performance. To solve this problem, a new kind of sparse array named super LRLA (S-LRLA) is proposed in this article. The key characteristic of S-LRLA is that it has no unit-spaced sensor pairs but has the largest continuous difference coarray spanning from 2 to N - 2 with a redundancy of less than 2. Lots of S-LRLAs are obtained by using a differential evolution (DE) method. On this basis, two types of S-LRLAs, including seven closed-formed patterns and two semiclosed-formed patterns, are discovered. The property and designing factors of S-LRLA are analyzed. Furthermore, the adapted S-LRLA (AS-LRLA) with full difference coarray is also discussed. Comparisons with other prominent arrays are finally presented to demonstrate the superiority of AS-LRLA.

Automated summary

In this article, a new type of sparse array named super LRLA (S-LRLA) is proposed, which has no unit-spaced sensor pairs but has the largest continuous difference coarray spanning from 2 to N - 2 with a redundancy of less than 2, obtained using a differential evolution method. The characteristics and design factors of S-LRLA are analyzed, discovering seven closed-formed patterns and two semiclosed-formed patterns. Adapted S-LRLA (AS-LRLA) with full difference coarray is also discussed, with comparisons made with other prominent arrays to demonstrate the superiority of AS-LRLA.