Sea-Spike Discrimination in Maritime Radars Based on Polarimetric Doppler Offset Differences

For maritime radars to detect low-velocity small targets, it is always difficult to exclude false alarms from sea spikes in observation time of the order of subsecond. This article investigates the characteristics of sea spikes in full-polarimetric maritime radars and proposes a sea-spike discrimination method based on polarimetric Doppler offset differences (DoDs). As the first contribution, an improved sea spike identification method is presented. In the method, the generalized Pareto intensity distribution (GPID) is used to model Bragg scattering background at each polarization and GPID-dependent amplitude threshold, the minimum time width, and range-time connected support are combined to extract sea spikes with range-time supports. As the second contribution, the deep analysis of sea spikes in 70 full-polarimetric IPIX datasets shows that sea spikes synchronously occur at HH-, HV-, and VV-polarizations as a large-scale scattering phenomenon from breaking waves and sea spikes has different Doppler offsets at the three polarizations. Two new indexes of the polarimetric repeatability rate and amplitude peak-mean ratio (APMR) and the concept of full-polarimetric sea spikes are introduced to analyze polarimetric characteristics of sea spikes. As the third contribution, a method of detection of low-velocity small targets and discrimination of sea spikes based on polarimetric DoDs is developed for full-polarimetric maritime radars. It realizes effective detection of low-velocity small targets and exclusion of false alarms from sea spikes in a short coherent processing interval (CPI) of about one-tenth of 1 s.

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Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2024-12-25
DOI
https://doi.org/10.1109/tgrs.2024.3522576
Citations
2
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.96

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article

Sea-Spike Discrimination in Maritime Radars Based on Polarimetric Doppler Offset Differences

Hang Wen, Peng‐Lang Shui, Xiao‐Jun Zhang, Ting-Yu Duan
2 citations
IEEE Transactions on Geoscience and Remote Sensing
Ocean Waves and Remote Sensing
0.96
article

Sea-Spike Discrimination in Maritime Radars Based on Polarimetric Doppler Offset Differences

Hang Wen, Peng‐Lang Shui, Xiao‐Jun Zhang, Ting-Yu Duan
article en
2 citations

Abstract

For maritime radars to detect low-velocity small targets, it is always difficult to exclude false alarms from sea spikes in observation time of the order of subsecond. This article investigates the characteristics of sea spikes in full-polarimetric maritime radars and proposes a sea-spike discrimination method based on polarimetric Doppler offset differences (DoDs). As the first contribution, an improved sea spike identification method is presented. In the method, the generalized Pareto intensity distribution (GPID) is used to model Bragg scattering background at each polarization and GPID-dependent amplitude threshold, the minimum time width, and range-time connected support are combined to extract sea spikes with range-time supports. As the second contribution, the deep analysis of sea spikes in 70 full-polarimetric IPIX datasets shows that sea spikes synchronously occur at HH-, HV-, and VV-polarizations as a large-scale scattering phenomenon from breaking waves and sea spikes has different Doppler offsets at the three polarizations. Two new indexes of the polarimetric repeatability rate and amplitude peak-mean ratio (APMR) and the concept of full-polarimetric sea spikes are introduced to analyze polarimetric characteristics of sea spikes. As the third contribution, a method of detection of low-velocity small targets and discrimination of sea spikes based on polarimetric DoDs is developed for full-polarimetric maritime radars. It realizes effective detection of low-velocity small targets and exclusion of false alarms from sea spikes in a short coherent processing interval (CPI) of about one-tenth of 1 s.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Xidian University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 23%
Ocean Waves and Remote Sensing
0.96
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