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Bayesian Compress Sensing Based Countermeasure Scheme Against the Interrupted Sampling Repeater Jamming.
Sha Huan1, Gane Dai2, Gaoyong Luo1
1School of Physics and Electronic Engineering, Guangzhou University, Guangzhou 510006, China.
Sensors (Basel, Switzerland)
|July 28, 2019
Summary
This study introduces a new Bayesian compressive sensing (BCS) method to counter interrupted sampling repeater jamming (ISRJ) in radar systems. The BCS approach effectively reconstructs weak target signals, improving detection accuracy even with high jammer power.
Area of Science:
- Radar signal processing
- Electronic warfare and countermeasures
- Statistical signal detection
Background:
- Interrupted Sampling Repeater Jamming (ISRJ) poses a significant challenge to coherent radar detection.
- Existing countermeasures struggle with weak echo detection, especially against high-power jammers.
- The need for robust anti-jamming techniques in radar systems is critical.
Purpose of the Study:
- To propose a novel countermeasure scheme against ISRJ using Bayesian compressive sensing (BCS).
- To enable stable reconstruction of target signals across a wide range of signal-to-noise ratios (SNR) for single and multi-target scenarios.
- To enhance radar detection performance under ISRJ conditions.
Main Methods:
- Deriving the ISRJ jamming strategy to identify unjammed time segments.
- Utilizing discontinuous time segments to construct a sparse target model.
- Applying an efficient alternating iterative method to optimize the Maximum A Posteriori (MAP) estimate of the sparse target model.
Main Results:
- The proposed BCS-based scheme demonstrates robustness in low SNR and high jammer ratio scenarios.
- Stable target signal reconstruction is achieved for both single and multi-target situations.
- Significant improvements in grating lobe level and target detection/false detection probability compared to FFT and SAMP algorithms.
Conclusions:
- The BCS-based countermeasure scheme offers a robust solution against ISRJ interference.
- The method effectively reconstructs weak target signals, enhancing radar detection capabilities.
- This approach outperforms traditional methods in critical performance metrics for radar anti-jamming.
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