New PDF release: Advanced radar techniques and systems

February 14, 2018 | Aerospace | By admin | 0 Comments

By Gaspare Galati

ISBN-10: 086341172X

ISBN-13: 9780863411724

This significant reference quantity includes 13 huge issues, contributed via 9 major researchers (from 6 nations around the world (including contributions from Europe, Japan and the USA). components of insurance comprise: procedure structure, layout, muddle and suppression, surveillance and artificial aperture radars, detection, rejection of jamming, aim identity, phased and paired arrays, and radar sign processing. Contributions are entire mathematically and plenty of comprise certain appendices.

Also available:

Optimised Radar Processors - ISBN 9780863411182 ideas of Space-Time Adaptive Processing, third variation - ISBN 9780863415661

The establishment of Engineering and know-how is without doubt one of the world's top 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 diverse topic components together with:

-Power & power -Renewable strength -Radar, Sonar & Navigation -Electromagnetics -Electrical dimension -History of know-how -Technology administration

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Extra info for Advanced radar techniques and systems

Example text

E. t does not depend on 0, we say that t is a sufficient statistic, and that t is sufficient for 0. Of course, if t is a sufficient statistic, any function of t is a sufficient statistic. The rationale for the name 'sufficient' is that in decision theory a sufficient statistic is one that provides enough information about the observation to make a proper decision. e. 92) where the functions A(O) and B(O) depend only on 0 and the functions h(x) and q(x) depend only on x. As an example, it is readily seen that a Gaussian density with mean ju and variance a2 is of the exponential type with respect both to the parameter// and to the parameter a2.

F It is worth noting that in the Bayesian approach the unknown parameter 6 is a random vector. 166) where the e value is small. This function gives zero penalty if all the components of the estimation error are less than £, and penalty one in the opposite case (one component or more greater than e). t. 167) since an error occurs whenever one or more than one estimated component has an error greater than £. 168) and the first integral equals 1. 169) and to minimise the cost function it is necessary to choose p(6\z) as large as possible.

This is not true of most practical cases, where more scalar or vector observations can either come from different channels, or be received in different time instants. Some cases relevant to radar are treated in the following sections. 7. 1 Detection of a known signal with additive Gaussian noise We shall now examine in more detail a decision problem that has practical applications in radar: the detection on the basis of N pulses received from a nonfluctuating target in the 'time-on-target' interval.

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Advanced radar techniques and systems by Gaspare Galati

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