NASA Scientific and Technical Aerospace Reports

The goal of space-time adaptive processing (STAP) is to manipulate the available data to achieve high gain at the target
angle and Doppler and maximal mitigation along both the jamming and clutter lines. Because the interference covariance
matrix is unknown a priori, it is typically estimated using sample covariances obtained from averaging over a few range gates.
The authors propose a new approach for parametric modeling and estimation of STAP data, based on the two-dimensional,
Wold-like decomposition of random fields. The proposed parametric estimation algorithms of the interference components
simplify and improve existing STAP methods. The resulting modeling and processing methods provide new parametric tools
to estimate and mitigate the Doppler ambiguous clutter. The estimation algorithms the authors propose enable the estimation
of the interference signals using the observations in only a single range gate. The proposed method is particularly suitable for
non-stationary clutter and jamming environments. The approach provides a new analytical insight into the STAP problem.
DTIC
Clutter; Decomposition; Doppler Radar; Jamming; Mathematical Models; Two Dimensional Models
20040073592 Science Applications International Corp., McLean, VA
Space-Time Adaptive Matched-Field Processing (STAMP)
Lee, Yung P.; Mar. 14, 2001; 8 pp.; In English; Original contains color illustrations
Report No.(s): AD-A422436; No Copyright; Avail: CASI; A02, Hardcopy
Space-time adaptive processing (STAP) is two- dimensional adaptive filter employed for the purpose of clutter
cancellation to enable the detection of moving targets. It has been a major focus of research activity in radar applications for
which the platform is in motion (e.g., airborne or space-based systems). In this setting, an antenna sensor array provides spatial
discrimination, while a series of time returns or pulses form a synthetic array that provide Doppler (velocity) discrimination.
The application of STAP for the mobile towed-array sonar system is non-trivial because of the complex multipaths in the
underwater environment. On the other hand, Matched-field processing (MFP) that uses a propagation code to predict the
complex multipath structure and coherently combines it to provide range/depth discrimination has been studied and
demonstrated. MFP with a synthetic array (a series of snapshots) to estimate the source velocity and localize source in range
and depth also has been demonstrated. STAMP combines the adjacent-filter beam space post-Doppler STAP and MFP to
provide improved performance for the mobile multi-line-towed-array sonar applications. The processing scheme includes
transforming phone time snapshots into frequency domain, at each frequency bin forming horizontal beams in the directions
of interest for each towed line, then combining signals from multi-towed lines and adjacent Doppler bins and beams that cover
the multi-path Doppler spread due to motion using adaptive MFP. A study of STAMP performance in the towed-array
forward-looking problem is discussed. In this problem, the own-ship signal and its bottom-scattered energy can be treated as
stationary interference with a moving target at constant speed within processing interval of a few minutes. (9 figures, 3 refs.)
DTIC
Adaptive Filters; Detection; Sonar; Sound Detecting and Ranging; Target Acquisition; Targets
20040073594 Massachusetts Inst. of Tech., Lexington, MA
Beamspace Adaptive Beamforming for Hydrodynamic Towed Array Self-Noise Cancellation
Premus, Vincent E.; Kogon, Stephen M.; Ward, James; Mar. 14, 2001; 7 pp.; In English; Original contains color illustrations
Contract(s)/Grant(s): F19628-00-C-0002
Report No.(s): AD-A422438; No Copyright; Avail: CASI; A02, Hardcopy
A beamspace adaptive beamformer (ABF) implementation for the rejection of cable strum self-noise on passive sonar
towed arrays is presented. The approach focuses on the implementation of a white noise gain constraint based on the scaled
projection technique due to Cox et al. IEEE Trans. on ASSP, Vol. 35 (10), Oct. 1987. The objective is to balance the aggressive
adaptation necessary for nulling the strong mainlobe interference represented by cable strum against the conservative
adaptation required for protection against signal self-nulling associated with steering vector mismatch. Particular attention is
paid to the definition of white noise gain as the metric that reflects the level of mainlobe adaptive nulling for an adaptive
beamformer. Adaptation control is subsequently performed through the implementation of a constraint on maximum allowable
white noise gain at the output of the adaptive processor. The theoretical development underlying the scaled projection-based
constraint implementation is reviewed. Towed array data results depicting the performance gain of the new ABF algorithm
optimized for strum cancellation relative to that of a more conservative baseline ABF algorithm are presented. (8 figures, 5
refs.)
DTIC
Beamforming; Cancellation; Sonar; Sound Detecting and Ranging
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