Adaptive beamforming with low sample support via indirect dominant mode rejection

IEEE Trans. Signal Process.

Rangaswamy

2007

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY) 20-08-20072. TYPE REPORT (From -To) JOURNAL ARTICLE DATES COVERED SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES)Electromagnetics Technology Division SC: 437490 SPONSOR/MONITOR'S ACRONYM(S)Sensors Directorate AFRL-SN-HS Air Force Research Laboratory 80 Scott Drive Hanscom AFB MA 01731-2909 SPONSOR/MONITOR'S REPORT NUMBER(S) AFRL-SN-HS-TP-2007-0006 DISTRIBUTION / AVAILABILITY STATEMENTApproved for public release; distribution unlimited. SUPPLEMENTARY NOTES ABSTRACTThe work developed and described in this technical report deals with the problem of providing a statistical model of the backscattering from lake surface for low-grazing angle and high resolution radar systems. First described is a statistical analysis of the amplitude of the high-resolution polarimetric data characterized by different radar looking directions with respect to the wind blowing directions. Then, based on the electromagnetic two-scale model, analyzed were both the amplitude and frequency modulations induced on the small-scale Bragg resonant waves by the large-scale surface tilt and advection, due to the swell presence. Our results confirm the lake clutter non-stationarity already found in previous analysis of other sea and lake clutter data. Moreover, the relationship between the variation of clutter spectral features, like texture, Doppler centroid and bandwidth, have been investigated by processing real recorded data. The data used for the research activity have been recorded by the IPIX radar of McMaster University in Grimsby, Ontario, Canada in 1998. SUBJECT TERMSStatistical analysis lake surface scattering, high-resolution polarimetric data characterization, small-scale Bragg resonant waves, lake clutter non-stationarity Abstract-Under conditions of low sample support, a low-rank solution of the minimum variance distortionless response (MVDR) equations can yield a higher output signal-to-interference-plus-noise ratio (SINR) than the full-rank MVDR beamformer. In this paper, we investigate several low-rank beamforming techniques, and we also propose a new beamformer that we refer to as the indirec...

Section: Introductionmentioning

confidence: 99%

Indirect Dominant Mode Rejection: A Solution to Low Sample Support Beamforming

IEEE Trans. Signal Process.

Rangaswamy

2007

“…In previous work we have proposed the IDMR beamformer [2] and shown its ability of providing higher output SINR if compared with the low-rank Conjugate Gradient (CG) and Dominant Mode Rejection (DMR) beamformers. In the previous work the IDMR beamformer was analyzed based on its performance of extracting the desired signal, i.e., the output SINR of the desired signal.…”

Section: Introductionmentioning

confidence: 99%

Power spectrum estimation with low rank beamforming

GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.

2005

Self Cite

When the size of the training samples is limited the performance of the full rank Minimum Variance Distortionless Response (MVDR) beamformer is deteriorated; and a low rank solution of the MVDR problem can yield a better performance. A new adaptive approach, Indirect Dominant Mode Rejection (IDMR), was introduced in previous work to solve the MVDR optimization problem. In the previous work the IDMR beamformer was used to extract the desired signal, while in this work we use the IDMR beamformer to estimate the power spectrum. We also introduce several modifications, which bring more robustness to the basic IDMR. These include root-music, forward/backward averaging of the sample covariance matrix and power window. 1 keywords: Adaptive beamforming, low-rank beamforming, MVDR, IDMR. 0-7803-9415-1/05/$20.00 © 2005 IEEE 0-7803-9415-1/05/$20.00 © 2005 IEEE 0-7803-9415-

“…However, the output SINR obtained with these low-rank beamformers depends on the rank of operation and there is not yet an effective rule to select the optimal rank [2]. In [3] we introduced the IDMR beamformer which uses a parametric estimate of the covariance matrix to cancel the correlation between the desired signal and the interference. Due to finite sample averaging, residual correlations between sources are present in the sample covariance matrix, causing a degradation in the performance of MVDR based beamformers.…”

Section: Introductionmentioning

confidence: 99%

IDMR Beamforming Under Direction-Independent Sterring Vector Mismatch

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings

The output SINR achieved via Indirect Dominant Mode Rejection (IDMR) beamforming is substantially higher than the achieved with other beamforming algorithms. IDMR is based on a parametric estimate of the covariance matrix which is obtained using an estimate of the directions of the dominant sources and assuming that the array manifold is available. In most applications the array manifold is not known precisely and performance of IDMR can be deteriorated. The focus of this paper is to enable the IDMR beamformer to operate in a scenario of direction-independent steering vector mismatch. A modified version of an algorithm introduced by Friedlander is employed to estimate the direction-independent mismatch. Thereafter IDMR is implemented. Simulation analysis reveals that this technique enables IDMR to operate in a scenario of direction-independent manifold mismatch.