A Unifying Approach to Linear and Nonlinear Array Processing: A Tutorial.
Final rept. Oct 84-Sep 85,
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The concept of linear filtering is the focus of a unifying approach to linear and nonlinear array processing methods. A number of well-known methods conventional, optimal, maximum likelihood are typically discussed within the context of linear filtering, while others maximum entropy, linear predictor, generalized eigenvector are not usually presented in this way. Through rederivation of these methods in terms of constrained filtering, we are able to relate performance of the methods to imposed or neglected constraints. Each filter discussed is linearly constrained in the look direction and then optimized using quadratic forms based on noise and sidelobe structure. Each filter is more complicated than the ones preceding it, as we consider additional aims and impose additional constraints. Stability of the methods to mismatches is considered, and techniques for improving stability are presented. Appendixes on Fourier transform approximation, array gain and detection, and complex Gaussian random variables are included. Keywords Noise suppression Robustness Data adaptive filtering. Author
- Theoretical Mathematics