This paper discusses some of the practical limitations of detection methods formulated in terms of the eigenvalues of the sample covariance matrix of the output of a sensor array. It presents an approach based on the principal eigenvectors and the measured array manifold that appears to be at least as sensitive, but apparently much more robust than methods such as AIC and MDL. Comparative performance results are given for simulation data with a variety of noise statistics and for data obtained from an experimental array.
|Original language||English (US)|
|Title of host publication||1992 IEEE 6th SP Workshop on Statistical Signal and Array Processing, SSAP 1992 - Conference Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||4|
|ISBN (Electronic)||0780305086, 9780780305083|
|State||Published - 1992|
|Event||6th IEEE SP Workshop on Statistical Signal and Array Processing, SSAP 1992 - Victoria, Canada|
Duration: Oct 7 1992 → Oct 9 1992
|Name||1992 IEEE 6th SP Workshop on Statistical Signal and Array Processing, SSAP 1992 - Conference Proceedings|
|Conference||6th IEEE SP Workshop on Statistical Signal and Array Processing, SSAP 1992|
|Period||10/7/92 → 10/9/92|
Bibliographical noteFunding Information:
This work was supported in parts by the SDIO/IST program managed by Office of Naval Resaarch under Contract N00014-86-K-0410, and by the National Science Foundation under Grant MIP-8813204
© 1992 IEEE.