Joint Aperture and Power Allocation Strategy for a Radar Network Localization System Based on Low Probability of...

Area of Science:

• Radar Systems Engineering
• Signal Processing
• Optimization Theory

Background:

• Distributed Radar Network Localization Systems (DRNLS) face limitations in survivability due to unaddressed random characteristics in Aperture Resource Allocation (ARA) and Radar Cross Section (RCS).
• These random factors significantly impact power resource allocation, which is critical for achieving Low Probability of Intercept (LPI) performance in DRNLS.

Purpose of the Study:

• To propose a joint aperture and power allocation scheme for DRNLS optimized for LPI performance.
• To address the limitations of current DRNLS by incorporating random ARA and RCS characteristics into the allocation strategy.

Main Methods:

• Development of a fuzzy random Chance Constrained Programming model for radar antenna aperture resource management (RAARM-FRCCP) to minimize elements.
• Construction of a Chance Constrained Programming model for minimizing Schleher Intercept Factor (MSIF-RCCP) to optimize LPI performance while ensuring tracking requirements.

Main Results:

• Demonstrated that uniform power distribution is not optimal when RCS exhibits randomness.
• The proposed joint allocation scheme reduces the number of required elements and power compared to uniform distribution under similar tracking performance.
• Lower confidence levels in the models allow for reduced power, enhancing LPI performance.

Conclusions:

• The joint allocation scheme effectively improves LPI performance of DRNLS by accounting for random system characteristics.
• The method provides a viable approach to optimize DRNLS power and aperture allocation for enhanced survivability and stealth.
• The findings suggest a trade-off between confidence level, power consumption, and LPI effectiveness.