SASA: Super-resolution and Ambiguity-free Sparse Array Geometry Optimization with Aperture Size Constraints for MIMO Radar

To improve the performance of multiple-input-multiple-output (MIMO) radar, various sparse arrays have been employed. However, the angular resolution of existing non-uniform arrays optimized by either combinatorial algorithms or heuristic ones is limited by the Rayleigh criterion, which is strictly r...

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Veröffentlicht in:IEEE transactions on antennas and propagation Jg. 71; H. 6; S. 1
Hauptverfasser: Huan, Mingsai, Liang, Junli, Wu, Yifan, Li, Yongkang, Liu, Wei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.06.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Ambiguity
angular ambiguity function
Angular resolution
Antenna arrays
Antenna radiation patterns
Apertures
Combinatorial analysis
Direction-of-arrival estimation
Heuristic algorithms
MIMO radar
non-convex optimization
Optimization
Radar antennas
Radar arrays
Radar imaging
Sidelobes
sparse array
ISSN:0018-926X, 1558-2221
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Zusammenfassung:To improve the performance of multiple-input-multiple-output (MIMO) radar, various sparse arrays have been employed. However, the angular resolution of existing non-uniform arrays optimized by either combinatorial algorithms or heuristic ones is limited by the Rayleigh criterion, which is strictly related to the aperture size. Based on the angular ambiguity function (AAF) analysis, two new models are established in this work for directly optimizing the sidelobe level (SLL) or the main lobe width (MLW) with the constraints of aperture size and element spacing. The aforementioned designs result in non-convex and nonlinear optimization problems, and solutions are derived via the alternating direction multiplier method (ADMM). Furthermore, considering a parametric trade-off between SLL and MLW, a hybrid algorithm is proposed to search for the SLL-MLW Pareto front boundary. Finally, simulations are provided to demonstrate the high angular resolution and ambiguity-free properties of the optimized sparse arrays.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2023.3262157