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Robust Weighted l1,2 Norm Filtering in Passive Radar Systems
Baris Satar1, Gokhan Soysal1, Xue Jiang2
1Department of Electrical and Electronics Engineering, Ankara University, Golbasi, Ankara 06830, Turkey.
Sensors (Basel, Switzerland)
|June 12, 2020
Summary
This study introduces a novel algorithm for passive radar target detection, improving performance in non-Gaussian impulsive noise. The new method offers more robust and accurate detection compared to traditional techniques.
Area of Science:
- Radar signal processing
- Statistical signal detection
- Passive bistatic radar systems
Background:
- Conventional passive radar target detection algorithms often assume Gaussian noise, which is unrealistic in real-world scenarios.
- Non-Gaussian impulsive noise significantly degrades the performance of existing algorithms like matched filtering and compressed sensing.
- Passive radars utilizing Universal Mobile Telecommunication System (UMTS) signals face challenges with impulsive noise interference.
Purpose of the Study:
- To develop a robust target detection algorithm for passive radars that performs well in the presence of non-Gaussian impulsive noise.
- To enhance the target detection performance of UMTS-based passive radars by improving resolution and suppressing sidelobes.
- To introduce a novel optimization-based approach using weighted l1 and l2 norms for improved radar signal processing.
Main Methods:
- A new optimization-based algorithm employing weighted l1 and l2 norms is proposed.
- The algorithm estimates the noise impulsiveness parameter to determine the weights for the norms.
- Performance is evaluated using simulated data with alpha-stable distributions and real data from a UMTS passive radar platform.
Main Results:
- The proposed algorithm demonstrates superior performance over conventional methods in environments with impulsive noise.
- It achieves more robust and accurate target detection across various noise impulsiveness levels.
- The method facilitates higher resolution and better sidelobe suppression in both range and Doppler domains.
Conclusions:
- The developed weighted l1/l2 norm algorithm offers a significant advancement for passive radar target detection in non-Gaussian noise.
- This approach provides a more reliable solution for real-world radar applications where impulsive noise is prevalent.
- The findings highlight the potential of advanced signal processing techniques to overcome limitations of traditional radar systems.
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