Abstract
Combined detection-estimation schemes for stochastic signals have been considered as early as the mid-1960s (see, e. g., [1–5]). In general three basic problems may be classified as joint detection-estimation problems: (1) It is desired to detect a signal when some or all of its parameters or model are unknown. The result is a decision-directed estimation where the ultimate interest is in the detection outcome, while the estimate of the parameters or states may only be a by-product, which need not be obtained. In many robust detection problems, these variables are not estimated explicitly, and the concern is in making the detector performance insensitive to the unknown variables. (2) It is desired to estimate a signal in the presence of several uncertainties which take on discrete (finitely many) values. In this case, the resulting estimator is concerned primarily with the estimate of the signal attributes, and the detection of the precise mode of uncertainty governing the signal model is a by-product of the estimation process. In most cases, one is satisfied with the estimation outcome without explicitly identifying or detecting the modes involved. (3) A truly joint estimation-detection scheme is concerned with detecting the presence of a signal and estimating its parameters at the same time, and the performance criterion used in such a case is a coupled one yielding a detector and estimator which depend on each other. The first problem is not discussed here, and only a brief exposition of the third problem will be given. The main part of this chapter is concerned with the joint detection- estimation schemes for estimation purposes. The discussion of the third problem will be limited to its relationship to the estimation problem.
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Haddad, A.H. (1986). On Detection-Estimation Schemes for Uncertain Systems. In: Blake, I.F., Poor, H.V. (eds) Communications and Networks. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4904-7_3
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DOI: https://doi.org/10.1007/978-1-4612-4904-7_3
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