| Paper: | SAM-P4.1 | ||
| Session: | Direction-of-Arrival Estimation | ||
| Time: | Wednesday, May 19, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Beamforming, direction-of-arrival estimation, and space-time adaptive processing | ||
| Title: | THE CAPON-MVDR ALGORITHM: THRESHOLD SNR PREDICTION AND THE PROBABILITY OF RESOLUTION | ||
| Authors: | Christ Richmond; MIT Lincoln Laboratory | ||
| Abstract: | The threshold region mean squared error (MSE) performance of the Capon-MVDR algorithm is predicted via an adaptation of an interval error based method referred to as the method of interval errors (MIE). MIE requires good approximations of two quantities: (i) interval error probabilities, and (ii) the algorithm asymptotic (SNR$\rightarrow \infty$) MSE performance. Exact pairwise error probabilities for the Capon (and Bartlett) algorithm are derived herein that include finite sample effects for an arbitrary colored data covariance; with the Union Bound, accurate approximations of the interval error probabilities are obtained. Combining these probabilities with the large sample MSE predictions of Vaidyanathan and Buckley, MIE accurately predicts the signal-to-noise ratio (SNR) threshold point, below which the Capon algorithm MSE performance degrades swiftly. A probability of resolution is defined for the Capon algorithm that accurately predicts the SNR at which sources of arbitrary closeness become resolvable. | ||
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