Title :
Efficient robust AMF using the FRACTA algorithm
Author :
Blunt, Shannon D. ; Gerlach, Karl
Author_Institution :
Radar Div., U.S. Naval Res. Lab., Washington, DC, USA
fDate :
4/1/2005 12:00:00 AM
Abstract :
The FRACTA algorithm has been shown to be an effective space-time adaptive processing (STAP) methodology for the airborne radar configuration in which there exists nonhomogeneous clutter, jamming, and dense target clusters. Further developments of the FRACTA algorithm are presented here in which the focus is on the robust, efficient implementation of the FRACTA algorithm. Enhancements to the FRACTA algorithm include a censoring stopping mechanism, an alternative data blocking approach for adaptive power residue (APR) censoring, and a fast reiterative censoring (RC) procedure. Furthermore, a coherent processing interval (CPI) segmentation scheme for computing the adaptive weights is presented as an alternative approach to computing the adaptive matched filter (AMF) weight vector that allows for lower sample support and reduced computational complexity. The enhanced FRACTA algorithm, denoted as FRACTA.E, is applied to the KASSPER I challenge datacube which possesses dense ground target clusters that are known to have a significant deleterious effect on standard adaptive matched filtering (AMF) processors. It is shown that the FRACTA.E algorithm outperforms and is considerably more computationally efficient than both the original FRACTA algorithm and the standard sliding window processing (SWP) approach. Furthermore, using the KASSPER I datacube, the FRACTA.E algorithm is shown to have the same detection performance as the clairvoyant algorithm where the exact range-dependent clutter covariance matrices are known.
Keywords :
adaptive filters; airborne radar; covariance matrices; jamming; matched filters; radar clutter; radar detection; radar receivers; radar signal processing; radar tracking; space-time adaptive processing; target tracking; FRACTA algorithm; FRACTA.E algorithm; KASSPER I datacube; adaptive matched filter weight vector; adaptive matched filtering; adaptive power residue censoring; adaptive weights; airborne radar configuration; censoring stopping mechanism; clutter covariance matrices; coherent processing interval; computational complexity; data blocking approach; ground target clusters; jamming; reiterative censoring procedure; segmentation scheme; sliding window processing; space-time adaptive processing; Adaptive filters; Airborne radar; Clustering algorithms; Clutter; Computational complexity; Covariance matrix; Filtering algorithms; Jamming; Matched filters; Robustness;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2005.1468746