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MUSIC-Based Multi-Channel Forward-Scatter Radar Using OFDM Signals.
Yihua Qin1, Abdollah Ajorloo1, Fabiola Colone1
1Department of Information, Electronics and Telecommunications Engineering (DIET), Sapienza University of Rome, 00184 Rome, Italy.
Sensors (Basel, Switzerland)
|December 31, 2025
Summary
This study introduces an advanced signal processing framework for multi-channel forward-scatter radar (MC-FSR) using the MUSIC algorithm. It significantly improves target detection and resolution, especially for low-cost systems with limited antennas.
Area of Science:
- Radar Systems Engineering
- Signal Processing
- Electromagnetics
Background:
- Existing Fast Fourier Transform (FFT)-based methods in multi-channel forward-scatter radar (MC-FSR) suffer from limited angular resolution and poor detection of weak or close targets.
- These limitations are exacerbated in low-cost FSR systems that utilize small antenna arrays.
- The need for enhanced spatial processing in hardware-constrained radar applications is critical.
Purpose of the Study:
- To develop an advanced signal processing framework for MC-FSR systems.
- To overcome the limitations of traditional FFT-based approaches in angular resolution and target detectability.
- To adapt the Multiple Signal Classification (MUSIC) algorithm for real-valued data in non-coherent MC-FSR systems.
Main Methods:
- Adapted the MUSIC algorithm for real-valued data from non-coherent MC-FSR by reformulating steering vectors and adjusting degrees of freedom.
- Focused on Orthogonal Frequency Division Multiplexing (OFDM) signals, analyzing their autocorrelation properties for target detection.
- Implemented strategies like sub-band processing and spatial smoothing to mitigate target signature decay and manage signal correlation.
Main Results:
- The MUSIC-based framework significantly enhances angular resolution in MC-FSR systems.
- Achieved reliable discrimination of closely spaced targets even with limited receiving channels.
- Simulation and experimental results validated the framework's effectiveness with cooperative targets (people, drones) using an S-band MC-FSR prototype.
Conclusions:
- The proposed MUSIC-based MC-FSR framework offers superior performance over FFT-based methods.
- It is suitable for low-cost, hardware-constrained environments and emerging Integrated Sensing and Communication (ISAC) systems.
- The method demonstrates practical effectiveness for real-world radar applications.
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