Abstract
A new space-time adaptive processing algorithm is proposed for clutter suppression in phased array radar systems. In contrast to the commonly used normalized least mean square (NLMS) algorithm which uses the second order moments of the data for adaptation, the proposed method uses the lower order moments of the data to adapt the weight coefficients. The normalization is also performed based on the data sample dispersion rather than the variance. Processing results using simulated and measured data show that the proposed algorithm converges faster than the NLMS algorithms in Gaussian and non-Gaussian clutter environments. It also provides better clutter suppression than the NLMS algorithm under heavy-tailed, impulsive, non-Gaussian environments. It in turn improves the target detection performance.
Recommended Citation
Y. R. Zheng et al., "A Normalized Fractionally Lower-Order Moment Algorithm for Space-Time Adaptive Processing," Proceedings of the IEEE Military Communications Conference, 2007. MILCOM 2007, Institute of Electrical and Electronics Engineers (IEEE), Jan 2007.
The definitive version is available at https://doi.org/10.1109/MILCOM.2007.4454814
Meeting Name
IEEE Military Communications Conference, 2007. MILCOM 2007
Department(s)
Electrical and Computer Engineering
Sponsor(s)
United States. Air Force. Office of Scientific Research
United States. Army Research Office
Keywords and Phrases
Clutter Suppression; Phased Array Radar Systems; Gaussian
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2007 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2007
