Article
Automation & Control Systems
Clement Chahbazian, Karim Dahia, Nicolas Merlinge, Benedicte Winter-Bonnet, Aurelien Blanc, Christian Musso
Summary: The paper derives a recursive formula of the Fisher information matrix on Lie groups and applies it to nonlinear Gaussian systems on Lie groups for testing. The proposed recursive CRLB is consistent with state-of-the-art filters and exhibits representative behavior in estimation errors. This paper provides a simple method to recursively compute the minimal variance of an estimator on matrix Lie groups, which is fundamental for implementing robust algorithms.
Article
Engineering, Electrical & Electronic
Michael Fauss, Alex Dytso, H. Vincent Poor
Summary: Both the classic and Bayesian Cramer-Rao bounds can be obtained by minimizing the mean square error of an estimator while constraining the underlying distribution to be within a Fisher information ball. The results allow for nonstandard interpretations of the Cramer-Rao bound and provide a template for novel bounds on the accuracy of estimators.
Article
Computer Science, Information Systems
Benjamin Siebler, Stephan Sand, Uwe D. Hanebeck
Summary: In this paper, the achievable position accuracy of magnetic localization is analyzed using Bayesian Cramer-Rao lower bounds, and deterministic inputs are accounted for. A Gaussian process is used to approximate the true analytical model based on training data. The results show that magnetic localization has a high potential accuracy.
Article
Engineering, Electrical & Electronic
Xianqing Li, Zhansheng Duan, Uwe D. Hanebeck
Summary: Joint Cramer-Rao lower bound (JCRLB) is a valuable tool for evaluating the performance of joint state and parameter estimation in non-linear systems, including those with TASD measurements. The recursive JCRLB for general and special forms of parametric systems provides insights into the effectiveness of JCRLB for TASD systems, as illustrated through radar target tracking examples.
IET SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Alex Dytso, Martina Cardone, Ian Zieder
Summary: This article analyzes the performance of the Ziv-Zakai bound in the practically relevant high-noise regime and shows that it is not tight in general.
IEEE SIGNAL PROCESSING LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Antonio Alberto D'Amico, Michele Morelli, Marco Moretti
Summary: This study investigates the estimation of sinusoidal frequency in the presence of white Gaussian noise, focusing on DFT interpolation methods and optimization. Evaluating the CRB and maximum likelihood DFT interpolator helps assess the accuracy and applicability of the methods. This is important for improving estimation accuracy and reducing computational burden.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Daniele Fontanelli, Farhad Shamsfakhr, Luigi Palopoli
Summary: This article addresses the positioning problem using weighted least square (WLS) method, examining the impact of geometric configuration of anchors on the uncertainty and introducing a refinement technique (G-WLS) to improve accuracy. The effectiveness of G-WLS is proven theoretically and demonstrated through experiments and simulations.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Computer Science, Software Engineering
Zhitao Zhuang, Kaixin Wang
Summary: This paper calculates the CRLB in a non-additive white Gaussian noise model for the affine phase retrieval (APR) and simulates the performance difference of PhaseLift in AWGN and non-AWGN cases, comparing the CRLB and mean square error for phase retrieval and APR.
INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING
(2021)
Review
Multidisciplinary Sciences
Dariya Salykina, Farid Khalili
Summary: This paper reviews various schemes of quantum-enhanced optical interferometers, including linear (SU(2)) and non-linear (SU(1,1)) schemes, as well as hybrid SU(2)/SU(1,1) options. It takes into account the practical limitations relevant to real-world interferometers. Three important cases defined by the interferometer symmetry are discussed. It is shown that the Quantum Cramer-Rao bound (QCRB) can be asymptotically saturated by standard detection schemes in all considered cases.
Article
Automation & Control Systems
Nargess Sadeghzadeh-Nokhodberiz, Mohammadreza Davoodi, Nader Meskin
Summary: This article introduces an event-triggered particle filtering method for estimating the states of stochastic nonlinear systems and addresses the non-Gaussianity issue by modifying particle weight update. The conditional posterior Cramer-Rao lower bound is obtained through Monte Carlo simulations to evaluate the performance of the proposed method, showcasing its efficiency in a networked interconnected four-tank system.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Jialin Jiang, Ji Xiong, Yuyao Wang, Pan Wang, Jialei Zhang, Yongxin Liang, Jianhui Sun, Zinan Wang
Summary: This paper investigates the relationship between the noise lower-bound (NLB) and the minimal detectable strain in a COTDR system with coherent detection, proposes the CRLB, discusses the method to achieve this lower bound, and demonstrates good consistency between experimental results and theoretical analysis.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Chemistry, Analytical
Chibuzo Joseph Nnonyelu, Meng Jiang, Jan Lundgren
Summary: This article introduces a biaxial velocity sensor consisting of two orthogonal particle velocity sensors and a collocated pressure sensor. The study analyzes the impact of skewness on the direction-finding performance and derives the hybrid Cramer-Rao bound for the directions-of-arrival in closed form, considering the stochastic loss of perpendicularity. The results show that the loss of perpendicularity affects the variation of the bound along the azimuth angle axis, independent of the skew angle.
Article
Engineering, Aerospace
Jianyu Su, Haiyan Fang, Weimin Bao, Haifeng Sun, Liang Zhao
Summary: The paper deduces the Crame r-Rao Lower Bound (CRLB) for estimating pulsar rotation parameters using X-ray pulsar observation data and presents the calculation equation. To verify the correctness of the deduced equation, X-ray pulsar observation data is used to estimate pulsar rotation parameters, and the root mean square error (RMSE) of the estimated parameters is obtained through repeated experiments. The experimental results show that the RMSE approaches the estimated CRLB as the observation time increases, with the error between the RMSE and the CRLB staying at 10-11 order of magnitude when the observation time is 2.4 x 106 s. This confirms that the deduced CRLB is the theoretical lower bound for estimating pulsar rotation parameters. The deduced CRLB in this paper helps determine the minimum variance estimator for pulsar rotation parameter estimation, providing a benchmark for comparisons with other estimators.
ADVANCES IN SPACE RESEARCH
(2023)
Article
Computer Science, Information Systems
Jiseon Moon, Christos Laoudias, Ran Guan, Sunwoo Kim, Demetrios Zeinalipour-Yazti, Christos G. Panayiotou
Summary: Crowdsourcing is an efficient and promising method for constructing large-scale signal fingerprint radio maps. However, a crowdsourced indoor positioning system (IPS) needs to handle diverse devices and the heterogeneity in received signal strength (RSS) measurements. To address device heterogeneity, differential fingerprinting methods like mean differential fingerprinting (MDF) have been explored. This article focuses on the localization performance of MDF and demonstrates its effectiveness in mitigating device diversity and other factors affecting RSS readings.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Lihua Ni, Di Zhang, Yimao Sun, Ning Liu, Jing Liang, Qun Wan
Summary: This paper proposes a one-bit Rao test (OBRT) method for target detection and localization in a multiple distributed subarray (MDS) system with one-bit ADCs. An optimal one-bit quantizer is designed to remove the performance loss caused by quantization, and a benchmark method is provided to evaluate the localization performance of OBRT. Theoretical analysis and simulation results show that the detection performance loss of OBRT can be removed by increasing 0.57 times samples or 1.5 times nodes; compared to the IBGLRT, the localization gap of OBRT is pi/2 in low-SNR scenarios.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)