A new feature vector using selected bispectra for signal classification with application in radar target recognition

IEEE Transactions on Signal Processing

Volumn 49, Issue 9, 2001, Pages 1875-1885

  Zhang, Xian Da ^a,b,c   Shi, Yu ^c   Bao, Zheng ^a,d  

^a IEEE   (China)

^b XIDIAN UNIVERSITY   (China)

^c TSINGHUA UNIVERSITY   (China)

^d MICROSOFT RESEARCH ASIA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

AXIALLY INTEGRATED BISPECTRA (AIB);

CORRELATION METHODS; FEATURE EXTRACTION; GAUSSIAN NOISE (ELECTRONIC); INTEGRAL EQUATIONS; RADAR TARGET RECOGNITION; VECTORS;

SIGNAL PROCESSING;

EID: 0035447999     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.942617     Document Type: Article

References (16)

1. Object and texture classification using higher order statistics
2. Pattern recognition using invariants defined from higher order spectra - One-dimensional inputs
3. Detection of non-Gaussian signals using integrated polyspectrum
4. Circularly integrated bispectra: Novel shift invariant features for high-resolution radar target recognition
5. Computation and interpretation of kth order spectra
6. Bispectrum estimation: A digital signal processing framework
7. Correlation filters for aircraft identification from radar range profiles
8. Radar target classification of commercial aircraft
9. Radar target recognition using a radial basis function neural network
10. Using range profiles as feature vectors to identify aerospace objects
11. Matching score properties between range profiles of high-resolution radar targets
12. An adaptive-window-width short-time Fourier transform for visualization of radar target substructure resonances
13. Joint time-frequency analysis for radar signal and image processing
14. Radar target identification using the bispectrum: A comparative study