By Van Trees, Harry L.
ISBN-10: 047110793X
ISBN-13: 9780471107934
ISBN-10: 1601195575
ISBN-13: 9781601195579
Initially released in 1968, this booklet is among the nice time-tested classics within the box of sign processing. hugely readable and essentially geared up, it really is as significant at the present time for execs, researchers, and scholars in optimal sign processing because it used to be over thirty years in the past.
- half III specializes in radar-sonar sign processing and Gaussian signs in noise. the next themes are coated intimately:
- Detection of Gaussian signs in white Gaussian noise
- General binary detection: Gaussian procedures
- Estimation of the parameters of a random method
- The radar-sonar challenge
- Parameter estimation: slowly fluctuating aspect objectives
- Doppler-spread goals and channels
- Range-spread objectives and channels
- Doubly-spread objectives and channels
the implications are nonetheless principally appropriate to present platforms
Read or Download Detection, Estimation, and Modulation Theory - Part lll - Radar-Sonar Processing and Gaussian Signals in Noise PDF
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Extra info for Detection, Estimation, and Modulation Theory - Part lll - Radar-Sonar Processing and Gaussian Signals in Noise
Example text
The optimum realizable filter receiver (Canonical Realizations Nos. 4 and 4s). The most practical realization will depend on the particular problem of interest. 2 we considered the performance of the optimum receiver. In general, it was not possible to find the probability density of I, on the two hypotheses. By extending the techniques of Chapter 1-2, we were able to find good approximations to the error probabilities. The key function in this analysis was p(s). 4 Problems where h(s) = y = In 7.
4. Consider the special case in which Repeat part 3. 18. 17. The covariance of w(l) is K&, U) N 6(t - u)I. where N is a nonsingular matrix. 1. 17. ) 2. Why do we assume that N is nonsingular? 3. Consider the special case in which KJr, u ) = KAt, u)I and N is diagorial. Simplify the results in part 1. 19. 17. 17 are still valid.
Substituting (18) into (126) gives { [fi ,/27r(No/2) 1- 1 t=i R (- -21 2 L)) NJ2 2 exp 1-a dR, * dR,. (131) 1-1 Performing the integration, we have From our discussion on page 13, we know the first sum on the right side of (132) is well behaved as K - . 00. The convergence of the second sum follows easily. 2 Performance We now take the limit of (132) as K- co. The first sum is due to the randomness in s ( r ) , and so we denote it by p&). The second sum is due to the deterministic component in r ( t ) , and so we denote it by p&).
Detection, Estimation, and Modulation Theory - Part lll - Radar-Sonar Processing and Gaussian Signals in Noise by Van Trees, Harry L.
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