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- Document type:
- Konferenzbeitrag
- Author(s):
- Lenz, A.; Stein, M.; Nossek, J.
- Title:
- Signal Parameter Estimation Performance Under a Sampling Rate Constraint
- Abstract:
- Recently it has been found, that the receive filter design rule 2Br < fs, known as the sampling theorem, does not necessarily lead to optimum signal parameter estimation performance. This is in particular the case if the transmit bandwidth Bt is higher than the sampling bandwidth of the receiver, i.e., 2Bt > fs. While this result has been obtained under the assumption of ideal low-pass filters, here we extend the analysis by taking into account the possibility of optimizing the filter transfer function. We formulate the problem of finding the best unconstrained analog receive filter with respect to the asymptotic estimation performance on the basis of the Fisher information. It is shown that the problem of optimizing the filter coefficients can be decomposed into N subproblems, each reducing to a binary decision rule for the spectral filter coefficients. Based on these findings we show examples of optimized ideal filters and compare their estimation performance with classical low-pass filters. The results give insights into favorable designs of realizable filters and allow to explore the theoretic performance limits of signal processing systems with sampling rate constraints.
- Book / Congress title:
- 49th Asilomar Conf. Signals, Systems and Computers
- Year:
- 2015
- Reviewed:
- ja
- WWW:
- http://ieeexplore.ieee.org/document/7421179/
- Copyright statement:
- This work is copyrighted by the IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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