🤖 AI Summary
This work addresses the limitations in degrees of freedom (DOF) and virtual aperture inherent in direction-of-arrival (DOA) estimation for noncircular signals. To overcome these constraints, a novel nested array configuration based on an extended coprime structure is proposed. By incorporating a sliding translation strategy to optimize sensor placement, the design achieves, for the first time, a redundancy-free fusion of sum and difference coarrays while preserving the continuity of the difference coarray. This integration effectively enlarges the virtual aperture and substantially enhances the achievable DOF. Simulation results demonstrate that the proposed array significantly outperforms conventional nested arrays and existing structures such as ESNA, yielding improved DOA estimation accuracy and an increased number of resolvable sources.
📝 Abstract
In recent years, direction of arrival estimation utilizing non-circular signals has become a focal point for scholarly research. To enhance the degrees of freedom (DOF) in receiver arrays specifically for non-circular signal DOA estimation, this study introduces a novel array configuration. This design leverages an extended coprime framework, applying a sliding translation technique to optimize sensor placement. Crucially, this rearranged structure preserves the continuity of the difference co-array (DCA). Furthermore, the sum co-array (SCA) is shifted to merge seamlessly with the DCA, eliminating redundancy and substantially expanding both the virtual aperture array (VAA) and the DOF. Consequently, the proposed array demonstrates superior performance in practical DOA estimation tasks involving non-circular signals. Simulation results and comparative analyses confirm that, relative to traditional Nested Arrays (NA), Extended Sliding Nested Array (ESNA), and other benchmark structures, the proposed array achieves better DOF and VAA, leading to enhanced estimation accuracy in practical scenarios.