By Simon Haykin
This collaborative paintings provides the result of over 20 years 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 examine on which this publication is predicated.
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Additional resources for Adaptive Radar Signal Processing
23) Given that Zk ( f ) = and 1 W λk xk ( f ) = ∫ ∫−W Vk ( ν) dZ ( f − ν) 12 −1 2 Vk ( ν) dZ ( f − ν) we may write Z k ( f ) − dk ( f ) xk ( f ) = ⎡ 1 − d ( f )⎤ W V ( ν) dZ ( f − ν) − d ( f )= V ( ν) dZ ( f − ν) k k k ∫ k ⎦⎥ ∫−W ⎣⎢ λ k where the cut integral is deﬁned by =∫ = (∫ 12 −1 2 −∫ W −W ) The intervals(−W, W) and (−1/2, −W) ∪ (W, 1/2) are named the inner and outer bands, respectively. It is helpful here to think of the energy in the band( f − W, f + W) as a signal component and the energy outside it as a noise component.
We see these effects, both here, in the spectra and in the F-tests considered in the following section. 9 The crude spectra S¯ ( f ) for NW = 2 and 4. 10 The adaptive spectra S¯ ( f ) for NW = 2 and 4. 8W. A larger boundary results in a larger mismatch of the power levels between the known signal components. Note the detail of the composite spectrum despite the larger spectral window. 7 F-Test for the Line Components 35 features that are of interest. Thomson  recommends that W be between 1/N and 20/N, with a time–bandwidth product of 4 or 5 being a common starting point.
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). 36) k =0 and Sˆ (f0) is the adaptive spectrum developed earlier. This choice of weights imposes the constraint that Sˆ(f0) should have sufﬁcient degrees of freedom for w(f0) to have a reasonable distribution.
Adaptive Radar Signal Processing by Simon Haykin