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An Adaptive Detection Algorithm for Non-Uniform Sea Clutter Background Targets Based on Iterative Weighting and

Hang Su¹, Liang Zhang¹, Cheng Zhao¹

¹Nanjing Research Institute of Electronics Technology, Nanjing 210039, China.

Sensors (Basel, Switzerland)

|May 27, 2026

Summary

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This study introduces an enhanced Adaptive Normalized Matched Filter (IWP-ANMF) to improve radar weak target detection in complex sea clutter. The novel algorithm effectively suppresses interference from cluster targets and sea spikes, boosting detection accuracy.

Area of Science:

Radar Signal Processing
Target Detection
Sea Clutter Analysis

Background:

Nonhomogeneous sea clutter environments degrade radar weak target detection performance.
Dense cluster targets and sea-spike interference severely distort covariance matrix estimation.
Existing methods like ANMF and GIP struggle with heterogeneous contamination.

Purpose of the Study:

To propose an enhanced Adaptive Normalized Matched Filter algorithm (IWP-ANMF) for robust weak target detection.
To address performance degradation caused by cluster targets and sea-spike interference in sea clutter.
To improve the accuracy and reliability of radar detection in complex maritime environments.

Main Methods:

Developed an iterative weighting and sample purification (IWP-ANMF) framework.

Keywords:

ANMF Iterative weighting dense cluster targets nonhomogeneous sea clutter radar detection robust covariance estimation sample purification

Related Experiment Videos

Implemented a closed-loop iterative detection process to identify and purify contaminated samples (cluster targets, sea spikes).

Utilized adaptive deep-notch suppression based on statistical characteristics for sample purification and robust covariance matrix estimation.

Main Results:

The IWP-ANMF algorithm demonstrated superior robustness and detection performance compared to classical ANMF and GIP.
Validated through Monte Carlo simulations and real K-distributed sea clutter data.
Effectively mitigated performance deterioration caused by wideband masking of cluster targets.

Conclusions:

The proposed IWP-ANMF algorithm significantly enhances weak target detection capabilities in complex maritime conditions.
The iterative purification method ensures convergence to an optimal robust covariance matrix estimation.
The algorithm provides a reliable solution for challenging sea clutter scenarios with dense targets and interference.