Download Adaptive Radar Signal Processing by Simon Haykin PDF

By Simon Haykin

This collaborative paintings provides the result of over 20 years of pioneering examine by means of Professor Simon Haykin and his colleagues, facing using adaptive radar sign processing to account for the nonstationary nature of our surroundings. 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 booklet relies.

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N − 1 and εk = { 1i for k even for k odd The DPSWFs can be expressed as N −1 U k ( N , W ; f ) = ε k ∑ υ(nk ) ( N , W ) e j 2 πf [n − ( N −1) 2] n=0 and the DPSSs satisfy the Toeplitz matrix eigenvalue equation N −1 ∑ m=0 ( ) sin 2 πW ( n − m ) (k ) υm ( N , W ) = λ k ( N , W ) υ(nk ) ( N , W ) π (n − m ) These two equations give a relatively straightforward way of computing the DPSSs and DPSWFs for moderate values of N. 4 Thomson’s Multi-Taper Method 21 where v (k ) = [ υ(0k ) , υ1(k ) , .

1 The Basic ANOVA Table Variation Source Regression Residuals 13 Degrees of Freedom Sum of Squares (SS) Mean SS ν1 ν2 SS1 = ||Axˆ|| SS2 = ||y − Axˆ||2 MSreg = SS1/ν1 s2 = SS2 /ν2 2 In practice, of course, we require a computed F ratio that is much larger than the tabulated one. 7 F-Test for the Line Components s2 = 37 S1 2 (n − p) is also an estimate for the squared variance for model 1. For the second model, we have respectively −1 xˆ q = ( AqH Aq ) AqH y and S2 = y − Aq xˆ q 2 where S2 has 2(n − q) degrees of freedom.

3 Spectrum Estimation Background 17 where fi are the frequencies of the periodic or line components, and μi are their amplitudes. 9) First moments are associated with the study of periodic phenomena (harmonic analysis). 4 Such parameters may be estimated using techniques based on maximum-likelihood. In classic methods of spectrum estimation —nonparametric, based on the periodogram—the resolution limit (also referred to as the Rayleigh resolution limit) is 1/T, where T is the total observation time.

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