Signal processing applications of oblique projection operators

Oblique projection operators are used to project measurements onto a low-rank subspace along a direction that is oblique to the subspace. They may be used to enhance signals while nulling interferences. In the paper, the authors give several basic results for oblique projections, including formulas for constructing oblique projections with desired range and null space. They analyze the algebra and geometry of oblique projections in order to understand their properties. They then show how oblique projections can be used to separate signals from structured noise (such as impulse noise), damped or undamped interfering sinusoids (such as power line interference), and narrow-band noise. In some of the problems addressed, the oblique projection provides an alternative way to implement an already known solution. Expressing these solutions as oblique projections brings geometrical insight to the study of the solution. The geometry of oblique projections enables one to compute performance in terms of angles between signal and noise subspaces. As a special case of removing impulse noise, the authors can use oblique projections to interpolate missing data samples. In array processing, oblique projections can be used to simultaneously steer beams and nulls. In communications, oblique projections can be used to remove intersymbol interference. >

[1]  Kevin Buckley,et al.  Spatial-spectrum estimation in a location sector , 1990, IEEE Trans. Acoust. Speech Signal Process..

[2]  Howard L. Weinert,et al.  Oblique projections: Formulas, algorithms, and error bounds , 1989, Math. Control. Signals Syst..

[3]  Jack K. Wolf,et al.  Redundancy, the Discrete Fourier Transform, and Impulse Noise Cancellation , 1983, IEEE Trans. Commun..

[4]  T. Marshall,et al.  Coding of Real-Number Sequences for Error Correction: A Digital Signal Processing Problem , 1984, IEEE J. Sel. Areas Commun..

[5]  Jeffrey Park,et al.  The subspace projection method for constructing coupled-mode synthetic seismograms , 1990 .

[6]  E. Lorch,et al.  On a calculus of operators in reflexive vector spaces , 1939 .

[7]  Sabri Tosunoglu,et al.  Complete accessibility of oscillations in robotic systems by orthogonal projections , 1988 .

[8]  Thomas Kailath,et al.  Linear Systems , 1980 .

[9]  T. G. Marshall Codes For Error Correction Based Upon Interpolation Of Real-number Sequences , 1985, Nineteeth Asilomar Conference on Circuits, Systems and Computers, 1985..

[10]  Ramdas Kumaresan Rank Reduction Techniques And Burst Error-correction Decoding In Real/complex Fields , 1985, Nineteeth Asilomar Conference on Circuits, Systems and Computers, 1985..

[11]  Louis L. Scharf,et al.  The SVD and reduced rank signal processing , 1991, Signal Process..

[12]  C. S. Lindquist,et al.  Comparison of Class 1 and Class 2 frequency domain matrix and vector estimation filters with adaptive FIR filters , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

[13]  Toshihiro Furukawa,et al.  Orthogonal projection algorithm for block adaptive signal processing and some of its properties , 1990 .

[14]  T. N. E. Greville,et al.  Solutions of the Matrix Equation $XAX = X$, and Relations between Oblique and Orthogonal Projectors , 1974 .

[15]  P. Mathys A Channel Model And Corresponding Map-rule For Linear Blockcodes Over The Reals , 1991, Proceedings. 1991 IEEE International Symposium on Information Theory.

[16]  R. Kumaresan,et al.  Estimation of frequencies of multiple sinusoids: Making linear prediction perform like maximum likelihood , 1982, Proceedings of the IEEE.

[17]  Louis L. Scharf,et al.  Matched subspace detectors , 1994, IEEE Trans. Signal Process..

[18]  Richard Travis Behrens Subspace signal processing structured noise , 1991 .

[19]  L.L. Scharf,et al.  Parameter Estimation In The Presence Of Low Rank Noise , 1988, Twenty-Second Asilomar Conference on Signals, Systems and Computers.

[20]  F. J. Murray,et al.  On complementary manifolds and projections in spaces _{} and _{} , 1937 .