Download Advanced Radar Techniques and Systems (IEE Radar, Sonar, by Gaspare Galati PDF

By Gaspare Galati

This significant reference quantity includes 13 big subject matters, contributed through 9 major researchers (from 6 international locations world wide (including contributions from Europe, Japan and the USA). components of assurance comprise: method structure, layout, muddle and suppression, surveillance and artificial aperture radars, detection, rejection of jamming, aim id, phased and matched arrays, and radar sign processing. Contributions are whole mathematically and lots of contain specified appendices.Also available:Optimised Radar Processors - ISBN 9780863411182Principles of Space-Time Adaptive Processing, third variation - ISBN 9780863415661The establishment of Engineering and expertise is likely one of the world's best expert 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 varied topic components together with: -Power & power -Renewable power -Radar, Sonar & Navigation -Electromagnetics -Electrical size -History of know-how -Technology administration

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Additional resources for Advanced Radar Techniques and Systems (IEE Radar, Sonar, Navigation and Avionics, No 4)

Example text

1 Properties of ML estimators As stated previously, it is often useful to describe the behaviour of an estimator when the number of independent observations JV approaches infinity (asymptotic behaviour). It is possible to prove, under general conditions, the following properties: (a) The ML estimate is consistent: this means that, under certain regularity conditions, the ML estimate converges in probability to the correct value as Attends to infinity (see above for the rigorous definition of consistency).

158) When the pattern has a Gaussian shape (expr. 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.

But in most practical applications the mathematical relationships are much more complicated. Typical applications of the ML criterion, leading to complex mathematical expressions, are: (a) Estimation of the time delay (determination of the range in radar systems). g. g. of the azimuth angle of a target). In these cases and in many others, by applying the ML criterion, one obtains a system of non-linear equations that can be resolved numerically with iterative f This section may be omitted from a first reading.

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