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    Square root Gaussian mixture PHD filter for multi-target bearings only tracking

    Access Status
    Fulltext not available
    Authors
    Wong, S.
    Vo, Ba Tuong
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Wong, S. and Vo, B.T. 2011. Square root Gaussian mixture PHD filter for multi-target bearings only tracking, pp. 520-525.
    Source Title
    Proceedings of the 2011 7th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2011
    DOI
    10.1109/ISSNIP.2011.6146607
    ISBN
    9781457706738
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/55189
    Collection
    • Curtin Research Publications
    Abstract

    Bearings-only tracking is a challenging estimation problem due to the variable observability of the underlying targets. In the presence of false alarms and missed detections, the difficulty of the estimation problem is further compounded by the presence of ghost targets. This paper presents a solution to the bearings only tracking problem based on the theory of random finite sets or Finite Sets Statistics. We adopt the Gaussian-Mixture Probability Hypothesis Density filter as a basis for performing multi-sensor multi-target tracking. A corresponding square root implementation is derived to ensure numerical stability of the filter and applied to a bearings only scenario. The proposed solution is a simple, computationally inexpensive and numerically stable method for fusing multi-sensor bearings information. © 2011 IEEE.

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