Radar detection based on compound-Gaussian model with inverse gamma texture

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Radar detection based on compound-Gaussian model with inverse gamma texture

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The coherent radar detection against a background of compound-Gaussian clutter with inverse gamma texture is studied and three detectors: One-step generalised likelihood ratio test (1S-GLRT), maximum a posteriori GLRT (MAP-GLRT) and two-step GLRT (2S-GLRT) are proposed. The detectors have the same structure with their test statistics and modified thresholds, respectively, related to the scale and the shape parameters of the texture, which can also be formulated in a matched filter (MF) form. Subsequently, the performance assessments are given by their probability of detection and probability of false alarm. The authors find that the probability of false alarm is dependent on the shape parameter, meaning the detectors have no CFAR property. When the shape parameter and the number of the integrated radar pulses satisfy certain condition, it has no relation with the shape parameter and then the detectors have CFAR property. Finally, simulation results show that: (i) 1S-GLRT and MAP-GLRT have the same performance for fixed probability of false alarm and 2S-GLRT bears slightly bad performance; (ii) the performance of 1S-GLRT is much closer to the adaptive coherence estimator (ACE) and is better than that of the Kelly GLRT and (iii) the 1S-GLRT is robust when parameter estimation errors exist.

Inspec keywords: radar detection; radar clutter; probability; Gaussian processes

Other keywords: two-step generalised likelihood ratio test; matched filter form; detection probability; one-step generalised likelihood ratio test; coherent radar detection; performance assessment; inverse gamma texture; test statistics; false alarm probability; integrated radar pulses; compound-Gaussian clutter; maximum a posteriori generalised likelihood ratio test

Subjects: Signal detection; Radar equipment, systems and applications; Other topics in statistics

References

    1. 1)
    2. 2)
    3. 3)
      • A. Niknejad .
    4. 4)
      • S.M. Kay . (1998) Fundamentals of statistical signal processing: detection theory.
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
      • Akcakaya, M., Hurtado, M., Nehorai, A.: `MIMO radar detection of targets in compound-Gaussian clutter', Proc. 42nd Asilomar Conf. on Signals, Systems, and Computers, 2008, p. 208–212.
    10. 10)
      • Farina, A., Gini, F., Greco, M.V., Sangston, K.J.: `Optimum and sub-optimum coherent radar detection in compound-Gaussian clutter: a data-dependent threshold interpretation', Proc. 1996 IEEE National Radar Conf., May 1996, Ann Arbor, MI, p. 160–165.
    11. 11)
      • McWhorter, L.T., Scarf, L.L.: `Adaptive matched subspace detectors and adaptive coherent estimators', Proc. 30th Asilomar Conf. on Signals, Systems and Computers, November 1996, Pacific Grove, CA, p. 1114–1117.
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
    17. 17)
      • Maio, A.D., Farina, A., Foglia, G.: `Adaptive radar detection: a bayesian approach', Proc. 2007 IEEE Int. Conf. on Radar System, April 2007, Waltham, MA, p. 624–629.
    18. 18)
    19. 19)
      • Wang, J., Dogandzic, A., Nehorai, A.: `Cramer-Rao bounds for compound-Gaussian clutter and target parameters', Proc. 2005 IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP' 2005), 2005, Philadelphia, PA, p. 1101–1104.
    20. 20)
    21. 21)
    22. 22)
    23. 23)
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