Robust statistical feature based aircraft identification

被引:73
作者
Mitchell, RA [1 ]
Westerkamp, JJ [1 ]
机构
[1] USAF, Res Lab, SNAT, Automat Target Recognit Branch, Wright Patterson AFB, OH 45433 USA
关键词
D O I
10.1109/7.784076
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The statistical feature based (StaF) classifier is presented for robust high range resolution HRR radar aircraft identification (ID). HRR signature peak features are selected "on the fly" with no a priori assumptions about the number or location of the features. Features extracted depends on the information content of the observed signature making the number, location, and amplitude of features random variables. A primary goal for this research is to increase classifier robustness by maintaining high known target ID while minimizing unknown target errors. Results are presented demonstrating that the StaF classifier can significantly reduce errors associated with unknown targets while maintaining a high probability of correct classification.
引用
收藏
页码:1077 / 1094
页数:18
相关论文
共 20 条
  • [1] BECKNER F, 1990, AUTOMATIC RADAR TARG
  • [2] DEWALL R, 1994, P COMB ID SYST C
  • [3] DEWITT MR, 1992, THESIS AIR FORCE I T
  • [4] EOM K, 1995, NONCOOPERATIVE TARGE
  • [5] Fukunaga K., 1990, INTRO STAT PATTERN R
  • [6] JAYNES ET, 1991, THEORY RADAR TARGET
  • [7] KOSIR P, 1995, P NAT AER EL C DAYT
  • [8] KOUBA ET, 1992, THESIS AIR FORCE I T
  • [9] Sequence comparison techniques for multisensor data fusion and target recognition
    Libby, EW
    Maybeck, PS
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1996, 32 (01) : 52 - 65
  • [10] MIERAS H, 1991, NONCOOPERATIVE TARGE