Phenomenology Based Decomposition of Sea Clutter with a Secondary Target Classifier

Masoud Farshchian, Benjamin Cowen, Ivan Selesnick

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Sea clutter consists of three components: a mean Doppler spectrum, persistent spikes, and discrete spikes, with a random degree of relative power for each component. We propose a non-linear optimization technique designed to decompose noisy sea clutter into these three components plus a noise component using sparsity inducing norms and linear time-invariant (LTI) filtering in various domains. This novel approach is proposed for non-stationary clutter because it avoids any quasistationarity assumptions, unlike the currently proposed state-of-the-art detectors [1]. The decomposition is applied to real South African sea clutter data provided by the Council for Scientific and Industrial Research (CSIR) [2]. We additionally propose a secondary classifier stage for post-processing of potential target detections from the decomposition, and discuss some features that assist in classification between targets and persistent spikes beyond amplitude. Several such extensions are discussed in the conclusion.

Original languageEnglish (US)
Title of host publicationRadarConf23 - 2023 IEEE Radar Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665436694
StatePublished - 2023
Event2023 IEEE Radar Conference, RadarConf23 - San Antonia, United States
Duration: May 1 2023May 5 2023

Publication series

NameProceedings of the IEEE Radar Conference
ISSN (Print)1097-5764
ISSN (Electronic)2375-5318


Conference2023 IEEE Radar Conference, RadarConf23
Country/TerritoryUnited States
CitySan Antonia

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Instrumentation


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