Application of the JPDA-UKF to HFSW Radars for Maritime Situational Awareness

Abstract

At the present day, growing interest is paid to the development of more reliable surveillance systems for maritime situational awareness (MSA). The purpose is to detect, track and classify cooperative and non-cooperative targets. For this reason, great interest is given to low-power/cost High-Frequency Surface-Wave (HFSW) radars as an early-warning tool for over-the- horizon (OTH) applications. However, in HFSW radars there is a trade-off in terms of quality and cost, i.e. the radar system exhibits poor azimuth resolution, high non-linearity, and significant false alarm rate. All these aspects reduce tracking performance if not properly addressed. In this context, the Joint Probabilistic Data Association (JPDA) with the Unscented Kalman Filter (UKF) is proposed. The tracking algorithm behavior is investigated by a comparison between the tracks generated by two HFSW radars, with overlapped fields of view, and Automatic Identification System (AIS) data. A discussion is provided about the possible effectiveness of HFSW radar fusion strategies.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2012
Accession Number
ADA620065

Entities

People

  • Jochen Horstmann
  • Michele Vespe
  • Paolo Braca
  • Raffaele Grasso
  • Salvatore Maresca

Organizations

  • Centre for Maritime Research and Experimentation

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Automatic Identification Systems
  • Data Association
  • Detection
  • Detectors
  • Doppler Effect
  • False Alarms
  • Filters
  • Frequency
  • Identification Systems
  • Kalman Filters
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Radar
  • Target Tracking
  • Warning Systems
  • Waves

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development
  • Radar Systems Engineering.