Combinatorics

Physics

Aerospace engineering

Topology (electrical circuits)

Degrees of freedom (physics and chemistry)

Subspace topology

Mathematics

Evolutionary biology

Biology

Algorithm

Statistics

Engineering

Coupling (piping)

Mathematical analysis

Function (biology)

Sparse array

Political science

Artificial intelligence

Element (criminal law)

Direction of arrival

Antenna (radio)

Control (management)

Range (aeronautics)

Coprime integers

Computer science

Quantum mechanics

Control theory (sociology)

Sensor array

Telecommunications

Mechanical engineering

IEEE Transactions on Aerospace and Electronic Systems

Owing to the large degrees of freedom and reduced mutual coupling by generating difference coarrays, nonuniform linear arrays have aroused great interest in direction of arrival estimation. Previous works have shown some improved sparse arrays, while few find the common features hidden within these structures. In this paper, we define a generic-coarray concept to reveal the impacts of variable ranges and element spacing on the uniform degrees of freedom (uDOFs), by which the sufficient condition for the connected coarrays is derived. We then propose an enhanced and generalized coprime array (EGCA) structure from the generic-coarray perspective. We show that the closed-form expression for the range of uDOFs is a function of sensor numbers and inter-element spacing. We prove that, by coarray extension and hole filling, the optimized EGCA possesses more uDOFs than the previous coprime arrays. Furthermore, EGCA also provides the minimum number of sensor pairs with small separation. Simulations verify the superiority of EGCA using the subspace-based algorithm.

Enhanced and Generalized Coprime Array for Direction of Arrival Estimation