Enhanced Passive GNSS-Based Radar Imaging Based on Coherent Integrated Multi-Satellite Signals

Area of Science:

• Remote Sensing Technology
• Signal Processing
• Radar Imaging

Background:

• Passive GNSS-based radar (GNSS radar) faces challenges with weak reflected signals, limiting its effectiveness.
• Existing imaging schemes struggle with signal strength and computational efficiency.

Purpose of the Study:

• To propose an enhanced GNSS radar imaging scheme to overcome weak reflected signal issues.
• To improve imaging gain and reduce computational complexity in passive GNSS radar systems.

Main Methods:

• Utilizes a backscattering geometry model with multiple satellites to avoid direct signal interference.
• Employs paralleled range compressions followed by a coordinates alignment operator to align PRN code phases.
• Coherently integrates range-compressed signals along the azimuth domain for improved imaging and processing.

Main Results:

• The proposed scheme achieves higher imaging gain compared to conventional bistatic and state-of-the-art multi-image fusion schemes.
• Demonstrates less computational complexity and faster algorithm speed than the state-of-the-art multi-image fusion scheme.
• Field proof-of-concept experiments validate the theoretical analysis and performance improvements.

Conclusions:

• The enhanced GNSS radar imaging scheme effectively addresses the weak signal problem in passive GNSS radar.
• Offers superior imaging gain and computational efficiency, making it a promising advancement for remote sensing.
• The method enables azimuth processing in a single operation, streamlining data analysis.