• DocumentCode
    184220
  • Title

    Application of the Fornasini-Marchesini first model to data collected on a complex target model

  • Author

    Piou, J.E. ; Dumanian, A.J.

  • Author_Institution
    Lincoln Lab., Massachusetts Inst. of Technol., Lexington, MA, USA
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    2279
  • Lastpage
    2284
  • Abstract
    This work describes the computation of scatterers that lay on the body of a real target which are depicted in radar images. A novelty of the approach is the target echoes collected by the radar are formulated into the first Fornasini-Marchesini (F-M) state space model [1] to compute poles that give rise to the scatterer locations in the two-dimensional (2-D) space. Singular value decomposition carried out on the data provides state matrices that capture the dynamics of the target. Furthermore, eigenvalues computed from the state transition matrices provide range and cross-range locations of the scatterers that exhibit the target silhouette in 2-D space. The maximum likelihood function is formulated with the state matrices to obtain an iterative expression for the Fisher information matrix (FIM) from which posterior Cramer-Rao bounds associated with the various scatterers are derived. Effectiveness of the 2-D state-space technique is tested on static range data collected on a complex conical target model; its accuracy to extract target length is judged and compared with the physical measurements. Validity of the proposed 2-D state-space technique and the Cramer-Rao bounds are demonstrated through data collected on the target model.
  • Keywords
    echo; eigenvalues and eigenfunctions; matrix algebra; maximum likelihood estimation; radar tracking; singular value decomposition; target tracking; Fisher information matrix; Fornasini-Marchesini first model; complex target model; eigenvalue; maximum likelihood function; posterior Cramer-Rao bound; radar image; scatterer; singular value decomposition; state space model; state transition matrix; target echo; Computational modeling; Cramer-Rao bounds; Data models; Eigenvalues and eigenfunctions; Feature extraction; Mathematical model; Matrix decomposition; Control applications; Estimation; Identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6858993
  • Filename
    6858993