By Simon Haykin
This collaborative paintings offers the result of over two decades of pioneering examine via Professor Simon Haykin and his colleagues, facing using adaptive radar sign processing to account for the nonstationary nature of our environment. those effects have profound implications for defense-related sign processing and distant sensing. References are supplied in every one bankruptcy guiding the reader to the unique study on which this e-book is predicated.
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Extra info for Adaptive Radar Signal Processing
The low-pass response approximates the ideal rectangular ﬁlter for spectrum estimation, while the high-pass one shows the leakage that occurs from outside the analysis window W. , in ﬁlter design), a smaller number of windows should be used. The top part of the ﬁgure shows the complete frequency response −8W ≤ f ≤ 8W, scaled in units of the window W, while the lower part expands on the range 0 ≤ f ≤ 2W. to the complex domain of the famous real dataset given in reference 15, where 11 modern methods of spectrum estimation were tested.
Since spectrum estimation is essentially the estimation of signal power within a certain analysis window and this can ideally be done with a narrow rectangular ﬁlter, we see that the baseband ﬁlter is the best possible approximation of such a window. The fact that more than one window is used makes for a smaller variance in the estimator. Also, since the signal power concentration within the analysis band is large (eigenvalues close to one), the bias introduced from the multiplicity of windows is kept small.
These subsets are used to form estimates of a given parameter, which are then combined to give estimates of bias and variance for this parameter, valid under a wide range of parent distributions. Thomson and Chave  discuss the extension of this concept to spectra, coherences, and transfer functions. 2 Angle-of-Arrival Estimation in the Presence of Multipath The Composite Spectrum The use of adaptive weighting as developed above provides superior protection against leakage and bias. Thomson also offers a further reﬁnement to achieve higher resolution by considering each speciﬁc frequency point f0 as a free parameter in (f − W ≤ f0 ≤ f + W).
Adaptive Radar Signal Processing by Simon Haykin