A parametric method for determining the number of signals in narrow-band direction finding

Abstract-In this paper, a new information theoretic algorithm is proposed for signal enumeration in array processing. The approach is based on predictive description length (PDL) that is defined as the length of a predictive code for the set of observations. We assume that several models, with each model representing a certain number of sources, will compete. The PDL criterion is computed for the candidate models and is minimized over all models to select the best model and to determine the number of signals. In the proposed method, the correlation matrix is decomposed into two orthogonal components in the signal and noise subspaces. The maximum likelihood (ML) estimates of the angles-of-arrival are used to find the projection of the sample correlation matrix onto the signal and noise subspaces. The summation of the ML estimates of these matrices is the ML estimate of the correlation matrix. This method can detect both coherent and noncoherent signals. The proposed method can be used online and can be applied to time-varying systems and target tracking.

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“…Wu and Fuhrmann [6] propose an alternative approach. They use "differential residues" to formulate an information theoretic algorithm.…”

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confidence: 99%

An Information Theoretic Approach to Source Enumeration in Array Signal Processing

Valaee

Kabal

2004

IEEE Trans. Signal Process.

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“…It can he seen that the false alarm rates obtained from the simulations arc in cloae agreement with the specitied P, values. 6 show the simulation results of 500 trials each corresponding to noise with three different degrees colour. The corresponding noise covariance matrices are derived from MA models.…”

Section: Simulation Resultsmentioning

confidence: 99%

Detection of the number of signals in the presence of noise with an unknown, banded structured covariance matrix

Chen

Reilly

Wong

[1991] IEEE Pacific Rim Conference on Communications, Computers and Signal Processing Conference Proceedings

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One of the challenging problenis in modern 'array processing IS Uie detection of the number of sources in unknown noise environments. This problem is not only of theoretical importance, but also of practical significance due to the fact that the environmental noise is, for many applications, non-white and of unknown covariance.Based on an assumption that the noise is correlated only over a limited spatial range, and by applying bi-may structure combined with canonical correlation analysis, a new, statistically solid, simple approach to solving the problem of detecting the number of signals in the n~ikriovl~r~ mise environment is presented in this papcr.

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“…The number of the arriving signals are assumed to be known, that is, the detection phase is assumed to be performed accurately with the use of standard algorithms developed for this purpose [45]- [49]. Note that the number of signals arriving on the array may be more than the number of emitters in the case of multi-path propagation.…”

Section: The Data Modelmentioning

confidence: 99%

Wide-band maximum likelihood direction finding by using tree-structured EM algorithm

Cadalli

Arıkan

Proceedings of 8th Workshop on Statistical Signal and Array Processing

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A parametric method for determining the number of signals in narrow-band direction finding

Cited by 72 publications

References 18 publications

An Information Theoretic Approach to Source Enumeration in Array Signal Processing

An Information Theoretic Approach to Source Enumeration in Array Signal Processing

Detection of the number of signals in the presence of noise with an unknown, banded structured covariance matrix

Wide-band maximum likelihood direction finding by using tree-structured EM algorithm

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