基于先验知识及其定量评估的自适应杂波抑制研究

doi:10.7527/S1000-6893.2013.0078

Abstract

Abstract:

To overcome the limitation on the number of homogeneous samples in heterogeneous clutter environments, an algorithm is proposed for suppressing clutter based on a priori knowledge and its accuracy evaluation. First, the spectral norm of the priori clutter covariance matrix, which is whitened by the true clutter covariance matrix and then subtracted by an identity matrix, is computed as a measure for the accuracy of the priori knowledge. Given that the true clutter covariance matrix is unknown, a method for adaptively estimating the spectral norm is proposed. Then with the evaluation result of the accuracy of the priori knowledge, a maximum likelihood estimation of the true clutter covariance matrix is obtained under a knowledge constraint. Finally, after constructing the clutter model of the coherent-pulse radar and space time adaptive radar respectively, the proposed algorithm is analyzed through numerical simulation. Simulation results show that the performance of the proposed algorithm is superior to the method in which the adaptive weight is formulated either by the sample covariance matrix or the priori covariance matrix.

Key words: heterogeneous clutter environments, clutter suppression, knowledge aided signal processing, priori knowledge evaluation, maximum likelihood estimation

CLC Number:

TANG Bo, ZHANG Yu, LI Ke. Adaptive Clutter Suppression Research Based on Priori Knowledge and Its Accuracy Evaluation[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013, 34(5): 1174-1180.

References

[1] Brennan L E, Reed I S. Theory of adaptive radar. IEEE Transactions on Aerospace and Electronic Systems, 1973, 9(2): 237-252.

[2] Ward J. Space-time adaptive processing for airborne radar. MIT Lincoln Laboratory Technical Report 1015, 1994.

[3] Guerci J R. Space-time adaptive processing for radar. Norwood: Artech House, 2003.

[4] Tang B, Tang J, Peng Y N. Clutter model and space time adaptive processing for truncated cone array. Acta Aeronautica et Astronautica Sinica, 2010, 31(3): 587-592. (in Chinese) 唐波, 汤俊, 彭应宁. 圆台阵列杂波模型及空时二维自适应处理. 航空学报, 2010, 31(3): 587-592.

[5] Reed S, Mallett J D, Brennan L E. Rapid convergence rate in adaptive arrays. IEEE Transactions on Aerospace and Electronic Systems, 1974, 10(6): 853-863.

[6] Melvin W L. Space-time adaptive radar performance in heterogeneous clutter. IEEE Transactions on Aerospace and Electronic Systems, 2000, 36(2): 621-633.

[7] Guerci J R, Baranoski E J. Knowledge-aided adaptive radar at DARPA: an overview. IEEE Signal Processing Magazine, 2006, 23(1): 41-50.

[8] Wicks M C, Rangaswamy M, Adve R, et al. Space-time adaptive processing: a knowledge-based perspective for airborne radar. IEEE Signal Processing Magazine, 2006, 23(1): 51-65.

[9] Melvin W L, Guerci J. Knowledge-aided signal processing: a new paradigm for radar and other advanced sensors. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(3): 983-996.

[10] Bergin J S, Teixeira C M, Techau P M, et al. Improved clutter mitigation performance using knowledge-aided space-time adaptive processing. IEEE Transactions on Aerospace and Electronic Systems, 2006, 42(3): 997-1009.

[11] Stoica P, Li J, Zhu X M, et al. On using a priori knowledge in space-time adaptive processing. IEEE Transactions on Signal Processing, 2008, 56(6): 2598-2602.

[12] Besson O, Bidon S, Tourneret J Y. Covariance matrix estimation with heterogeneous samples. IEEE Transactions on Signal Processing, 2008, 56(3): 909-920.

[13] Bidon S, Besson O, Tourneret J Y. A Bayesian approach to adaptive detection in nonhomogeneous environments. IEEE Transactions on Signal Processing, 2008, 56(1): 205-217.

[14] de Maio A, Farina A, Foglia G. Knowledge-aided Bayesian radar detectors & their application to live data. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(1): 170-183.

[15] de Maio A, de Nicola S, Landi L, et al. Knowledge-aided covariance matrix estimation: a MAXDET approach. IET Radar, Sonar & Navigation, 2009, 3(4): 341-356.

[16] Zhu X M, Li J, Stoica P. Knowledge-aided space-time adaptive processing. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(2): 1325-1336.

[17] Tang B, Tang J, Peng Y N. Performance of knowledge aided space time adaptive processing. IET Radar, Sonar & Navigation, 2011, 5(3): 331-340.

[18] Horn R A, Johnson C R. Matrix analysis. New York: Cambridge University Press, 1985.

[19] Bhatia R. Matrix analysis. New York: Springer, 1997.

[20] Löfberg J. YALMIP: a toolbox for modeling and optimization in MATLAB. 2004 IEEE International Symposium on Computer Aided Control Systems Design, 2004: 1-4.

[21] Toh K C, Todd M J, Tutuncu R H. SDPT3—a MATLAB software for semidefinite programming. Optimization Method Software, 1999, 11(1-4): 545-581.

[22] Robey F C, Fuhrmann D R, Kelly E J, et al. A CFAR adaptive matched filter detector. IEEE Transactions on Aerospace and Electronic Systems, 1992, 28(1): 208-216.

Adaptive Clutter Suppression Research Based on Priori Knowledge and Its Accuracy Evaluation

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