.png){kind=icon}
.png){kind=icon}
Return
Two-Dimensional Minimum Sensor Array: A New Perspective to Array Design
.png){kind=icon}
PRE
AI
DOI：10.1109/JSEN.2023.3273401.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this article, we design/propose a new class of planar arrays sparsely located on a two-dimensional (2-D) lattice to achieve the highest degrees of freedom (DOF) for a given number of sensors. We formulate an optimization problem to search for a hole-free 2-D sparse array with the fewest possible sensors. We convert this problem into a nonlinear binary problem by changing the variables, then into a binary linear programming problem, and solve it efficiently by employing branch and bound programming. Our results show that this optimal array outperforms alternative state-of-the-art 2-D array geometries in terms of a target resolution and direction of arrival (DOA) estimation accuracy given the number of sensors. Moreover, the proposed array outperforms other geometries in terms of the resolution probability of close targets and in the presence of mutual coupling.
Keywords:
Branch and bound optimization
degree of freedom (DOF)
linear integer programming
sparse two-dimensional (2-D) planar array
Journal
IF:
4.5
Papers:
2.1W
Citations:
7.3W