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Modified Anderson-Darling test-based target detector in non-homogenous environments
Yang Li1, Yinsheng Wei2, Bingfei Li3
1Department of Electronic Engineering, Harbin Institute of Technology, Harbin 150001, China. li.yang@hit.edu.cn.
Sensors (Basel, Switzerland)
|September 2, 2014
Summary
A novel Modified Anderson-Darling (MAD) target detector improves radar performance in complex, non-homogenous backgrounds. This constant false alarm rate (CFAR) system effectively identifies targets where traditional methods fail.
Area of Science:
- Radar Signal Processing
- Statistical Signal Detection
Background:
- Traditional Constant False Alarm Rate (CFAR) detectors struggle with non-homogenous background clutter in radar systems.
- Estimating background statistics accurately is crucial for reliable target detection.
Purpose of the Study:
- To propose a novel CFAR target detector robust to non-homogenous backgrounds.
- To enhance target detection performance in complex radar environments.
Main Methods:
- The proposed Modified Anderson-Darling (MAD) detector utilizes K-sample Anderson-Darling (AD) tests.
- It re-arranges reference cells by merging homogenous sub-blocks around the cell under test (CUT).
- Employs a double partition test, clutter edge refinement, and outlier elimination as anti-clutter processors.
Main Results:
- Simulation results demonstrate superior performance of the MAD detector.
- It outperforms several established CFAR detectors, including CA, GO, SO, OS, VI, and CI CFAR.
- The MAD detector shows significant advantages in most non-homogenous background scenarios.
Conclusions:
- The proposed MAD detector offers a significant advancement for radar target detection in challenging environments.
- Its robust background estimation and anti-clutter processing capabilities lead to improved detection accuracy.
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