On the effect of nuisance parameters on the threshold SNR value of the Barankin bound

Reuven, I.; Messer, H.

doi:10.1109/78.740136

Cited by 9 publications

(3 citation statements)

References 7 publications

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“…In contrast, the BTB-based criterion yields a configuration with less antennas concentrated at the edges, and thus a synthesized beam with lower sidelobes. It is also worth noting that assuming the source intensity S is unknown does not affect the SNR threshold value on the DOA estimation, compared with a situation where S would be known [25].…”

Section: Numerical Resultsmentioning

confidence: 99%

A comparison of antenna placement criteria based on the Cramér–Rao and Barankin bounds for radio interferometer arrays

Wang,

Bacharach,

Larzabal

et al. 2024

Signal Processing

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Section: Numerical Resultsmentioning

confidence: 99%

A comparison of antenna placement criteria based on the Cramér–Rao and Barankin bounds for radio interferometer arrays

Wang,

Bacharach,

Larzabal

et al. 2024

Signal Processing

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“…In contrast to the CRLB, the BLB does not require the existence of the partial derivative of the parameterized pdf p (y|θ), and hence it can also be used for scenarios with the prevalence of NLOS conditions. It has been shown that the BLB is tight not only at high SNR but also at low and medium SNR [51][52][53].…”

Section: ) Barankin Lower Bound Familymentioning

confidence: 99%

Fundamental Limitations and State-of-the-art Solutions for Target Node Localization in WSNs

Najarro¹,

Song²,

Kim³

2021

Preprint

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With the advances in new technological trends and the reduction in prices of sensor nodes, wireless sensor networks (WSNs) and their applications are proliferating in several areas of our society such as healthcare, industry, farming, and housing. Accordingly, in recent years attention on localization has increased significantly since it is one of the main facets in any WSN. In a nutshell, localization is the process in which the position of any sensor node is retrieved by exploiting measurements from and between sensor nodes. Several techniques of localization have been proposed in the literature with different localization accuracy, complexity, and hence different applicability. The localization accuracy is limited by fundamental limitations, theoretical and practical, that restrict the localization accuracy regardless of the technique employed in the localization process. In this paper, we pay special attention to such fundamental limitations from the theoretical and practical points of view and provide a comprehensive review of the state-of-the-art solutions that deal with such limitations. Additionally, discussion on the theoretical and practical limitations together with their recent solutions, remaining challenges, and perspectives are presented.

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“…Finally (49) As for the Bobrovsky-Zakaï bound, since is a parameter vector left to the user, the highest bound that can be obtained with (49) is given by (50) which is a particular case 1 of the Reuven-Messer bound [41].…”

Section: D) Bobrovsky-zakaï Boundmentioning

confidence: 99%

A Fresh Look at the Bayesian Bounds of the Weiss-Weinstein Family

Renaux

Forster

Larzabal³

et al. 2008

IEEE Trans. Signal Process.

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Abstract-Minimal bounds on the mean square error (MSE) are generally used in order to predict the best achievable performance of an estimator for a given observation model. In this paper, we are interested in the Bayesian bound of the Weiss-Weinstein family. Among this family, we have Bayesian Cramér-Rao bound, the Bobrovsky-MayerWolf-Zakaï bound, the Bayesian Bhattacharyya bound, the Bobrovsky-Zakaï bound, the Reuven-Messer bound, and the Weiss-Weinstein bound. We present a unification of all these minimal bounds based on a rewriting of the minimum mean square error estimator (MMSEE) and on a constrained optimization problem. With this approach, we obtain a useful theoretical framework to derive new Bayesian bounds. For that purpose, we propose two bounds. First, we propose a generalization of the Bayesian Bhattacharyya bound extending the works of Bobrovsky, Mayer-Wolf, and Zakaï. Second, we propose a bound based on the Bayesian Bhattacharyya bound and on the Reuven-Messer bound, representing a generalization of these bounds. The proposed bound is the Bayesian extension of the deterministic Abel bound and is found to be tighter than the Bayesian Bhattacharyya bound, the Reuven-Messer bound, the Bobrovsky-Zakaï bound, and the Bayesian Cramér-Rao bound. We propose some closed-form expressions of these bounds for a general Gaussian observation model with parameterized mean. In order to illustrate our results, we present simulation results in the context of a spectral analysis problem.Index Terms-Bayesian bounds on the MSE, Weiss-Weinstein family.

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On the effect of nuisance parameters on the threshold SNR value of the Barankin bound

Cited by 9 publications

References 7 publications

A comparison of antenna placement criteria based on the Cramér–Rao and Barankin bounds for radio interferometer arrays

A comparison of antenna placement criteria based on the Cramér–Rao and Barankin bounds for radio interferometer arrays

Fundamental Limitations and State-of-the-art Solutions for Target Node Localization in WSNs

A Fresh Look at the Bayesian Bounds of the Weiss-Weinstein Family

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