Inherent Trade-Offs Between the Conflicting Aspects of Designing the Compact Global Navigation Satellite System (GNSS) Anti-Interference Array

The Global Navigation Satellite System (GNSS) has emerged as a critical spatiotemporal infrastructure for ensuring the integrity of remote sensing data links. However, traditional GNSS antenna arrays, typically configured with the antenna spacing of half a wavelength, are constrained by the spatial...

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Veröffentlicht in:Remote sensing (Basel, Switzerland) Jg. 17; H. 10; S. 1760
Hauptverfasser: Li, Xiangjun, Zhao, Xiaoyu, Ye, Xiaozhou, Lu, Zukun, Wang, Feixue, Liu, Peiguo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.05.2025
Schlagworte:
Algorithms
antenna array design
Antenna arrays
Antennas
Antennas (Electronics)
anti-interference
Arrays
Artificial satellites
Availability
Constraints
Correlation coefficient
Correlation coefficients
Design
Eigenvectors
Electromagnetic properties
Game theory
Genetic algorithms
Global navigation satellite system
global navigation satellite system (GNSS)
Multiple objective analysis
Mutual coupling
Optimization
Pareto optimization
Receivers & amplifiers
Regulatory mechanisms (biology)
Remote sensing
Satellites
Signal processing
Signal to noise ratio
Sorting algorithms
Tradeoffs
Wavelength
ISSN:2072-4292, 2072-4292
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Zusammenfassung:The Global Navigation Satellite System (GNSS) has emerged as a critical spatiotemporal infrastructure for ensuring the integrity of remote sensing data links. However, traditional GNSS antenna arrays, typically configured with the antenna spacing of half a wavelength, are constrained by the spatial limitations of remote sensing platforms. This limitation results in a restricted number of interference-resistant antennas, posing a risk of failure in scenarios involving distributed multi-source interference. To address this challenge, this paper focuses on the multidimensional trade-off problem in the design of compact GNSS anti-interference arrays under finite spatial constraints. For the first time, we systematically reveal the intrinsic relationships and game-theoretic mechanisms among key parameters, including the number of antennas, antenna spacing, antenna size, null width, coupling effects, and receiver availability. First, we propose a novel null width analysis method based on the steering vector correlation coefficient (SVCC), elucidating the inverse regulatory mechanism between increasing the number of antennas and reducing antenna spacing on null width. Furthermore, we demonstrate that increasing antenna size enhances the signal-to-noise ratio (SNR) while also introducing trade-offs with mutual coupling losses, which degrade SNR after compensation. Building on these insights, we innovatively propose a multi-objective optimization framework based on the non-dominated sorting genetic algorithm-II (NSGA-II) model, integrating antenna electromagnetic characteristics and signal processing constraints. Through iterative generation of the Pareto front, this framework achieves a globally optimal solution that balances spatial efficiency and anti-interference performance. Experimental results show that, under a platform constraint of 1 wavelength × 1 wavelength, the optimal number of antennas ranges from 15 to 17, corresponding to receiver availability rates of 89%, 72%, and 55%, respectively.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:2072-4292
2072-4292
DOI:10.3390/rs17101760