Spatial Information-Theoretic Optimal LPI Radar Waveform Design

Area of Science:

• Electrical Engineering
• Information Theory
• Radar Systems Engineering

Background:

• Low Probability of Intercept (LPI) radar waveform design is crucial for modern electronic warfare.
• Existing designs often optimize for either radar performance or stealth, creating a trade-off.
• Information theory offers a robust framework for quantifying performance bounds in waveform design.

Purpose of the Study:

• To develop LPI radar waveforms that simultaneously optimize radar detection, resolution, and stealth against Passive Interception Systems (PISs).
• To apply information-theoretic metrics, specifically Kullback-Leibler divergence and joint entropy, for performance evaluation.
• To utilize optimization techniques for solving the complex waveform design problem.

Main Methods:

• Formulating an optimization model for LPI waveform design based on information-theoretic constraints.
• Employing the Kullback-Leibler divergence to measure radar and PIS detection performance.
• Using joint entropy as a metric for radar resolution performance.
• Solving the optimization model using the Sequential Quadratic Programming (SQP) method.

Main Results:

• Successfully designed LPI waveforms that meet stringent radar detection and resolution requirements.
• Demonstrated superior performance in minimizing detectability by PISs compared to conventional methods.
• Validated the effectiveness of the information-theoretic approach and SQP optimization.

Conclusions:

• The proposed information-theoretic framework enables the co-design of LPI waveforms for enhanced radar functionality and stealth.
• The SQP-solved optimization model provides a practical method for generating high-performance LPI waveforms.
• This research contributes to the advancement of radar systems with improved survivability and effectiveness in complex electromagnetic environments.