| Paper: | SPTM-P13.9 | ||
| Session: | Detection and Classification | ||
| Time: | Friday, May 21, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Detection, Estimation, and Class. Thry & Apps. | ||
| Title: | DATA SELECTION FOR DETECTION OF KNOWN SIGNALS: THE RESTRICTED-LENGTH MATCHED FILTER | ||
| Authors: | Charles Sestok; Massachusetts Institute of Technology | ||
| Abstract: | Data selection algorithms in detection search for a small subset of the available data that is sufficient for making an accurate decision. This paper considers data selection for detection of a known signal in colored Gaussian noise. In our model, the performance of the matched filter detector for a specific subset is parameterized by a quadratic form. Selection of the best subset leads to a combinatorial optimization problem using the quadratic form as the objective function. Simulations show that heuristic search algorithms often find good solutions for the selected subset. Additionally, if the noise has a banded covariance matrix, a dynamic programming algorithm finds the optimal solution for any subset size. | ||
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