Improving the MODEX algorithm for direction estimation

Lopes, Amauri; Bonatti, Ivanil Sebastião; Peres, Pedro L. D.; Alves, Carlos Augusto Barnabé

doi:10.1016/s0165-1684(03)00146-4

Cited by 29 publications

(23 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Our proposal is based on the method of direction estimation (MODE) [17][18][19][20] and higher-order singular value decomposition (HOSVD) technique, which is referred to as Tensor-MODE (T-MODE). Generally speaking, tensor-based algorithms are superior to the matrix-based methods in terms of estimation performance in handling multi-dimensional signals, although the former have a higher computational load.…”

Section: Introductionmentioning

confidence: 99%

Tensor-MODE for multi-dimensional harmonic retrieval with coherent sources

Wen

2015

Signal Processing

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Tensor-MODE for multi-dimensional harmonic retrieval with coherent sources

Wen

2015

Signal Processing

View full text Add to dashboard Cite

“…To still get acceptable results, the DOA estimator has to be as good as possible. There are many papers covering DOA algorithms using a huge amount of antennas, samples per antenna or a high SNR, respectively (Ottersten et al, 1992;Li et al, 1998;Xin and Sano, 2004;Viberg et al, 1991b;Lopes et al, 2003;Stoica and Sharman, 1990b;Gershman and Stoica, 1999), to make use of statistical asymptotic analysis. Yet, there are few papers which deal with the single snapshot case.…”

Section: Introductionmentioning

confidence: 99%

Single snapshot DOA estimation

Häcker

Yang

2010

Adv. Radio Sci.

View full text Add to dashboard Cite

Abstract. In array signal processing, direction of arrival (DOA) estimation has been studied for decades. Many algorithms have been proposed and their performance has been studied thoroughly. Yet, most of these works are focused on the asymptotic case of a large number of snapshots. In automotive radar applications like driver assistance systems, however, only a small number of snapshots of the radar sensor array or, in the worst case, a single snapshot is available for DOA estimation.In this paper, we investigate and compare different DOA estimators with respect to their single snapshot performance. The main focus is on the estimation accuracy and the angular resolution in multi-target scenarios including difficult situations like correlated targets and large target power differences. We will show that some algorithms lose their ability to resolve targets or do not work properly at all. Other sophisticated algorithms do not show a superior performance as expected. It turns out that the deterministic maximum likelihood estimator is a good choice under these hard conditions.

show abstract

“…We have also used a new extra root generator, recently proposed [6]. This generator takes into account that some of the MODEX extra roots model the noise subspace of the sample covariance matrix.…”

Section: Introductionmentioning

confidence: 99%

“…However, in our simulations we used another root generation process, which was proposed in [6]. This new generator produces better candidates, reduces the computational effort and improves the MODEX performance.…”

mentioning

confidence: 99%

Modified MODEX method for direction finding with improved threshold performance

Krummenauer

Silva

Lopes

2006

2006 International Telecommunications Symposium

Self Cite

View full text Add to dashboard Cite

We propose to modify the MODEX algorithm for estimating direction of arrival (DOA) of plane waves using array of sensors. The MODEX algorithm is a Method Of Direction Estimation (MODE) based estimator that conveniently increases the number of MODE estimates, increasing the order of the polynomial, whose roots (candidates) estimate the DOA parameters. To select the better set of candidates, MODEX employs a maximum likelihood (ML) procedure.The proposed method affects the candidate selection process and improves its performance. This performance gain is achieved by replacing the original sample covariance matrix by a new one computed after a noise reduction filtering on the snapshot vectors. The modified selection procedure improves the MODEX performance and reduces significantly the threshold signal-tonoise ratio.

show abstract

Improving the MODEX algorithm for direction estimation

Cited by 29 publications

References 6 publications

Tensor-MODE for multi-dimensional harmonic retrieval with coherent sources

Tensor-MODE for multi-dimensional harmonic retrieval with coherent sources

Single snapshot DOA estimation

Modified MODEX method for direction finding with improved threshold performance

Contact Info

Product

Resources

About