Pregled bibliografske jedinice broj: 377176
Second and Fourth Order Statistics -Based Reduced Polynomial Rooting Direction Finding Algorithms
Second and Fourth Order Statistics -Based Reduced Polynomial Rooting Direction Finding Algorithms // Signal Processing, 89 (2009), 6; 1050-1060 doi:10.1016/j.sigpro.2008.12.004 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 377176 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Second and Fourth Order Statistics -Based Reduced Polynomial Rooting Direction Finding Algorithms
Autori
Wasylkiwskyj, Wasyl ; Kopriva, Ivica
Izvornik
Signal Processing (0165-1684) 89
(2009), 6;
1050-1060
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
direction finding ; polynomial rooting algorithms ; second order statistics ; fourth order statistics
Sažetak
Polynomial rooting direction finding (DF) algorithms are a computationally efficient alternative to search based DF algorithms and are particularly suitable for uniform linear arrays (ULA) of physically identical elements provided mutual interaction among the array elements can be either neglected or compensated for. A popular polynomial rooting algorithm is Root MUSIC (RM) wherein, for an N-element array, the estimation of the Directions Of Arrivals (DOA) requires the computation of the roots of a 2N-2- order polynomial for a second order (SO) statistics-, and a 4N-4- order polynomial for a fourth order (FO) statistics- based approach, wherein the DOA are estimated from L pairs of roots closest to the unit circle, when L signals are incident on the array. We derive SO- and FO statistics reduced polynomial rooting (RPR) algorithms capable to estimate L DOA from L roots only. We demonstrate numerically that the RPR algorithms are at least as accurate as the RM algorithms. Simplified algebraic structure of RPR algorithms leads to better performance than afforded by RM algorithms in saturated array environment, especially in the case of fourth order methods when number of incident signals exceeds number of elements, and under low SNR and/or small sample size conditions.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Elektrotehnika
POVEZANOST RADA
Projekti:
098-0982903-2558 - Analiza višespektralih podataka (Kopriva, Ivica, MZOS ) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb
Profili:
Ivica Kopriva
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus