A Multispectral Target Detection in Sonar Imagery

Guy Gubnitsky, Roee Diamant

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Detection of underwater objects in sonar imagery is a key enabling technique, with applications ranging from mine hunting and seabed characterization to marine archaeology. Due to the non-homogeneity of the sonar imagery, the majority of detection approaches are geared towards detection of features in the spatial domain to identify anomalies in the seabed's background. Yet, when the seabed is complex and includes rocks and sand ripples, spatial features are hard to discriminate, leading to high false alarm rates. With the aim of detecting man-made objects in complex environments, we utilize, as a detection metric, the expected spectral diversity of reflections to differentiate man-made objects' reflections from the relatively flat frequency response of natural objects' reflections, such as rocks. Our solution merges a set of preregistered sonar images, each of which are obtained at a different frequency band. Using the Jain's fairness as a metric to evaluate the spectral diversity of a suspected object within a low or high resolution sonar imagery, respectively, our solution detects anomalies across the spectrum domain. We tested our algorithm over simulated data and over multispectral data obtained in a designated sea experiment. The results show that, compared to benchmark schemes, our approach obtains better performance in terms of the trade-off between false alarm rate and detection capability.

Original languageEnglish
Title of host publicationOCEANS 2021
Subtitle of host publicationSan Diego - Porto
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780692935590
StatePublished - 2021
EventOCEANS 2021: San Diego - Porto - San Diego, United States
Duration: 20 Sep 202123 Sep 2021

Publication series

NameOceans Conference Record (IEEE)
ISSN (Print)0197-7385


ConferenceOCEANS 2021: San Diego - Porto
Country/TerritoryUnited States
CitySan Diego

Bibliographical note

Funding Information:
This work was funded in part by the Israeli Ministry of Energy Under Grant Number 219-17-013

Publisher Copyright:
© 2021 MTS.


  • Automatic object detection
  • Jain's fairness index
  • Multispectral sonar imagery

ASJC Scopus subject areas

  • Oceanography


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