Ιδρυματικό Αποθετήριο [SANDBOX]
Πολυτεχνείο Κρήτης
EN  |  EL

Αναζήτηση

Πλοήγηση

Ο Χώρος μου

Realified L1-PCA for direction-of-arrival estimation: theory and algorithms

Markopoulos, Panos, Tsagkarakis Nicholas, Pados Dimitris A., Karystinos Georgios

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/2165F4BF-BC5E-4654-868A-7DCADA560F6B
Έτος 2019
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά P.P. Markopoulos, N. Tsagkarakis, D.A. Pados and G.N. Karystinos, "Realified L1-PCA for direction-of-arrival estimation: theory and algorithms," EURASIP J. Adv. Signal Process., vol. 2019, no. 1, Dec. 2019. doi: 10.1186/s13634-019-0625-5 https://doi.org/10.1186/s13634-019-0625-5
Εμφανίζεται στις Συλλογές

Περίληψη

Subspace-based direction-of-arrival (DoA) estimation commonly relies on the Principal-Component Analysis (PCA) of the sensor-array recorded snapshots. Therefore, it naturally inherits the sensitivity of PCA against outliers that may exist among the collected snapshots (e.g., due to unexpected directional jamming). In this work, we present DoA-estimation based on outlier-resistant L1-norm principal component analysis (L1-PCA) of the realified snapshots and a complete algorithmic/theoretical framework for L1-PCA of complex data through realification. Our numerical studies illustrate that the proposed DoA estimation method exhibits (i) similar performance to the conventional L2-PCA-based method, when the processed snapshots are nominal/clean, and (ii) significantly superior performance when the snapshots are faulty/corrupted.

Διαθέσιμα αρχεία

Υπηρεσίες

Στατιστικά