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  • Research Article
  • Open Access

Tracking Algorithms for Multistatic Sonar Systems

EURASIP Journal on Advances in Signal Processing20102010:461538

  • Received: 3 December 2009
  • Accepted: 23 June 2010
  • Published:


Activated reconnaissance systems based on target illumination are of high importance for surveillance tasks where targets are nonemitting. Multistatic configurations, where multiple illuminators and multiple receivers are located separately, are of particular interest. The fusion of measurements is a prerequisite for extracting and maintaining target tracks. The inherent ambiguity of the data makes the use of adequate algorithms, such as multiple hypothesis tracking, inevitable. For their design, the understanding of the residual clutter, the sensor resolution and the characteristic impact of the propagation medium is important. This leads to precise sensor models, which are able to determine the performance of the surveillance team. Incorporating these models in multihypothesis tracking leads to a situationally aware data fusion and tracking algorithm. Various implementations of this algorithm are evaluated with the help of simulated and measured data sets. Incorporating model knowledge leads to increased performance, but only if the model is in line with the physical reality: we need to find a compromise between refined and robust tracking models. Furthermore, to implement the model, which is inherently nonlinear for multistatic sonar, approximations have to be made. When engineering the multistatic tracking system, sensitivity studies help to tune model assumptions and approximations.


  • Tracking Algorithm
  • Target Track
  • Tracking Model
  • Robust Tracking
  • Sonar System

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Authors’ Affiliations

Department of Sensor Data and Information Fusion (SDF), Fraunhofer FKIE, Neuenahrer Straße 20, 53343 Wachtberg, Germany
NATO Undersea Research Centre (NURC), 19126 La Spezia, Italy


© M. Daun and F. Ehlers. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.