By S. Uṇṇikrishṇa Pillai, C. S. Burrus (auth.), S. Uṇṇikrishṇa Pillai, C. S. Burrus (eds.)

ISBN-10: 1461236320

ISBN-13: 9781461236320

ISBN-10: 1461281865

ISBN-13: 9781461281863

This ebook is meant as an creation to array sign method ing, the place the imperative goals are to use the to be had a number of sensor details in a good demeanour to observe and possi bly estimate the indications and their parameters found in the scene. the benefits of utilizing an array in preference to a unmarried receiver have prolonged its applicability into many fields together with radar, sonar, com munications, astronomy, seismology and ultrasonics. the first emphasis here's to target the detection challenge and the estimation challenge from a sign processing perspective. many of the contents are derived from available resources within the literature, even if a cer tain quantity of unique fabric has been integrated. This e-book can be utilized either as a graduate textbook and as a reference publication for engineers and researchers. the fabric offered right here should be effectively understood by way of readers having a again flooring in simple likelihood thought and stochastic approaches. A prelim inary path in detection and estimation idea, even though no longer crucial, could make the studying effortless. in truth this publication can be utilized in a one semester path following likelihood idea and stochastic processes.

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**Additional info for Array Signal Processing**

**Sample text**

Further, we also analyze an improved spatial smoothing scheme and prove that at most [3K /2] elements are enough to estimate any K directions of arrival [33]. ) In addition to the forward subarrays, this scheme makes use of complex conjugated backward subarrays of the original array to achieve superior performance. A special case of the general situation, where the multipath coefficients are treated to be real, is proved in [34]. However, this is an unrealistic assumption, as in practice all multipath coefficients will be invariably complex numbers and in that case it is necessary to reason differently.

3 Eigenvector-Based Techniques Consider a linear array consisting of M identical sensors and receiving signals from K narrowband signals uI(t), uit), ... •. , OK with respect to the line of array (Fig. 8). Let Pk; k = 1, 2, ... ,K represent the signal powers and P;j; i ,j = 1, 2, ... 47) and E[u;(t)u/(t)] , i ,j = 1, 2, ... ,K; I Pjj I ~ 1. 48) - 29- uit ) u 1(t) Refe

K +1 from the array output covariances. In what follows, we demonstrate a scheme that is applicable for noise fields of unequal intensity at different array elements. Toward this purpose define - 40- rei) = E[xo(t)x;*(t)], i = 0, 1,'" ,M-I. 48) we have K+l [ E + k=K+l K +1 =E bk e K+l E y'PkP1P~ y'P1PkP:lb o + 1e j1rd cos/l I t 2 +0'000; I=K+l j1rd cos/l I t 2 + 0"0 00;' i = 0, 1,' .. 85) k = K + 1, ... ,K +1 . Notice that the constants, bk , in general, are complex numbers (except in special cases).

### Array Signal Processing by S. Uṇṇikrishṇa Pillai, C. S. Burrus (auth.), S. Uṇṇikrishṇa Pillai, C. S. Burrus (eds.)

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