New PDF release: Advanced Radar Techniques and Systems (IEE Radar, Sonar,

By Gaspare Galati

ISBN-10: 086341172X

ISBN-13: 9780863411724

This significant reference quantity comprises 13 enormous issues, contributed through 9 prime researchers (from 6 international locations world wide (including contributions from Europe, Japan and the USA). components of insurance comprise: approach structure, layout, litter and suppression, surveillance and artificial aperture radars, detection, rejection of jamming, aim identity, phased and matched arrays, and radar sign processing. Contributions are entire mathematically and lots of contain distinct appendices.Also available:Optimised Radar Processors - ISBN 9780863411182Principles of Space-Time Adaptive Processing, third version - ISBN 9780863415661The establishment of Engineering and know-how is likely one of the world's major specialist societies for the engineering and expertise group. The IET publishes greater than a hundred new titles each year; a wealthy mixture of books, journals and magazines with a again catalogue of greater than 350 books in 18 assorted topic components together with: -Power & strength -Renewable strength -Radar, Sonar & Navigation -Electromagnetics -Electrical size -History of know-how -Technology administration

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Extra info for Advanced Radar Techniques and Systems (IEE Radar, Sonar, Navigation and Avionics, No 4)

Sample text

E. an estimator which converges in probability to the unknown parameter. 95) An important theorem, generally known as the Cramer-Rao lower bound (CRLB) or Frechet inequality states that there is a lower bound to the conditional variance of any scalar estimator. Therefore, if we are able to find an unbiased estimator whose variance equals that predicted by the said theorem, we can be sure that the estimator is the best in the class: it is also known as an efficient estimator. 1. 97 a) with a probability of 1.

159) where, as before, K = 4 In 2, and where NB=0B/A0 the half-power beamwidth. 3 Bayes estimation methods In estimation theory there are no methods equivalent to Neyman-Pearson and MEP criteria, owing to the fact that we consider continuous variables, for which it is not possible to define probability values. Indeed, it is possible to define Bayesian approach methods, defining some 'cost functions' C(0\6) that assign a cost to each combination of'estimatedvalue/actual-value' for the unknown parameter.

1) that the basic difference between a decision (hypothesis testing) problem and an estimation problem is the following: in the former, we have two (generally speaking, K) alternative cases for the observed events: a case mQ representing the null hypothesis and an alternative case mx; in the latter we have an infinite number of cases corresponding to the values of the parameter to be estimated (or, from another point of view, an unknown parameter which can take infinite different values). In radar problems, the detection of a target is generally followed by the estimation of related quantities, such as its azimuthal angle, its range, its Doppler frequency and so on.

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Advanced Radar Techniques and Systems (IEE Radar, Sonar, Navigation and Avionics, No 4) by Gaspare Galati


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