Multi-Node Small Radar Network Deployment Optimization in 3D Terrain.

Area of Science:

• Electrical Engineering
• Signal Processing
• Geospatial Analysis

Background:

• Radar network deployment in urban and mountainous regions is challenged by terrain.
• Existing optimization methods use simplified propagation models, neglecting height-based coverage variations.
• Accurate radio wave propagation modeling considering 3D terrain is essential for effective radar deployment.

Purpose of the Study:

• To introduce the parabolic equation model (PEM) for radar network deployment considering terrain.
• To propose the Layered Effective Coverage Rate (LECR) as an optimization objective.
• To optimize multi-node small radar networks in complex terrains.

Main Methods:

• The parabolic equation model (PEM) was adapted for radar propagation in 3D terrain.
• Layered Effective Coverage Rate (LECR) was defined to evaluate coverage across altitude layers.
• The nondominated sorting genetic algorithm III (NSGA-III) was utilized for multi-objective optimization.

Main Results:

• The parabolic equation model (PEM) provides more accurate coverage predictions than simpler models in varied terrain.
• The Layered Effective Coverage Rate (LECR) effectively guides the optimization process.
• NSGA-III successfully optimized radar network deployment considering terrain constraints.

Conclusions:

• Incorporating the parabolic equation model (PEM) significantly improves radar network deployment strategies in complex terrains.
• The proposed Layered Effective Coverage Rate (LECR) and NSGA-III offer an effective approach for optimizing radar network performance.
• This research enhances the reliability and efficiency of radar networks in challenging geographical environments.