arrow
Return

Higher order direction finding from rectangular cumulant matrices: The rectangular 2q-MUSIC algorithms

delete2017-04-01
delete8
PRE
AI
H
Hanna Becker
P
Pascal Chevalier *
M
Martin Haardt
DOI:10.1016/j.sigpro.2016.10.020delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Fourth-order (FO) high resolution direction finding methods such as 4-MUSIC have been developed for more than two decades for non-Gaussian sources mainly to overcome the limitations of second order (SO) high resolution methods such as MUSIC. In order to increase the performance of 4-MUSIC in the context of multiple sources, the MUSIC method has recently been extended to an arbitrary even order 2q (q >= 2), for square arrangements of the 2qth-order data statistics, giving rise to the 2q-MUSIC algorithm. To further improve the performance of 2q-MUSIC, the purpose of this paper is to extend the latter to rectangular arrangements of the data statistics, giving rise to rectangular 2q-MUSIC algorithms. Two kinds of rectangular arrangements, corresponding to redundant and non-redundant arrangements are considered. In particular, it is shown that rectangular arrangements of the higher order (HO) data statistics achieve a trade-off between performance and maximal number of sources to be estimated. These rectangular arrangements also lead to a complexity reduction for a given level of performance, which is still increased by non-redundant arrangements of the statistics. These results, completely new, open new perspectives in HO array processing.
Keywords:
Cumulants
Virtual array
Direction finding
2q-MUSIC
Rectangular arrangements
Non-Redundant
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Signal Processing cover
Signal Processing
IF:
3.6
Papers:
9.9K
Citations:
1.7W

Organization

H
hesam universite
Scholars:
3.6K
Papers: 3.0K
Citations: 16
T
Technische Universitat Ilmenau
Scholars:
2.4K
Papers: 2.0K
Citations: 20
T
technicolor sa
Scholars:
106
Papers: 73
Citations: 0
researcher View more organizations