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10. A Constrained Hybrid Cramér-Rao Bound for Parameter Estimation

Author

Ren, Chengfang, Le Kernec, Julien, Galy, Jerome, Chaumette, Eric, Larzabal, Pascal, Renaux, Alexandre, Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), University of Nottingham Ningbo [China], Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO), Systèmes et Applications des Technologies de l'Information et de l'Energie (SATIE), École normale supérieure - Cachan (ENS Cachan)-Université Paris-Sud - Paris 11 (UP11)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École normale supérieure - Rennes (ENS Rennes)-Université de Cergy Pontoise (UCP), and Université Paris-Seine-Université Paris-Seine-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Equality constraints, Parameter estimation, Hybrid Cramér-Rao bounds
Abstract

International audience; In statistical signal processing, hybrid parameter estimation refers to the case where the parameters vector to estimate contains both non-random and random parameters. Numerous works have shown the versatility of deterministic constrained Cramér-Rao bound for estimation performance analysis and design of a system of measurement. However in many systems both random and non-random parameters may occur simultaneously. In this communication, we propose a constrained hybrid lower bound which take into account of equality constraint on deterministic parameters. The usefulness of the proposed bound is illustrated with an application to radar Doppler estimation.

Published
2015

16. MSE lower bounds for deterministic parameter estimation

Author

Chaumette, Eric, Renaux, Alexandre, Larzabal, Pascal, Galy, Jerome, Vincent, François, Quinlan, Angela, Conservatoire National des Arts et Métiers - CNAM (FRANCE), Centre National de la Recherche Scientifique - CNRS (FRANCE), Ecole Normale Supérieure de Cachan - ENS Cachan (FRANCE), Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE), Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE), Ecole Supérieure d'Electricité - SUPELEC (FRANCE), Université de Cergy-Pontoise (FRANCE), Université de Montpellier 2 (FRANCE), and Trinity College Dublin - TCD (IRELAND)

Subjects
Traitement du signal et de l'image, Estimation, Signal detection
Abstract

This paper presents a simple approach for deriving computable lower bounds on the MSE of deterministic parameter estimators with a clear interpretation of the bounds. We also address the issue of lower bounds tightness in comparison with the MSE of ML estimators and their ability to predict the SNR threshold region. Last, as many practical estimation problems must be regarded as joint detection-estimation problems, we remind that the estimation performance must be conditional on detection performance.

Published
2010

26. Joint Detection Estimation Problem of Monopulse Angle Measurement

Author

Pascal Larzabal, Jerome Galy, Eric Chaumette, Conception et Test de Systèmes MICroélectroniques (SysMIC), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), ONERA - The French Aerospace Lab [Palaiseau], ONERA-Université Paris Saclay (COmUE), Systèmes et Applications des Technologies de l'Information et de l'Energie (SATIE), École normale supérieure - Cachan (ENS Cachan)-Université Paris-Sud - Paris 11 (UP11)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École normale supérieure - Rennes (ENS Rennes)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Centre National de la Recherche Scientifique (CNRS), IEEE, and Galy, Jerome

Subjects
Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Maximum likelihood, Amplitude-Comparison Monopulse, Aerospace Engineering, 02 engineering and technology, 0203 mechanical engineering, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Detection theory, Electrical and Electronic Engineering, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, 020301 aerospace & aeronautics, Radar tracker, Noise (signal processing), Estimation theory, business.industry, Detector, Estimator, Direction of arrival, 020206 networking & telecommunications, Tracking system, Amplitude, Monopulse radar, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

Estimation of the direction of arrival (DOA) of a signal source by means of a monopulse estimation scheme is one of the oldest and most widely used high-precision techniques in operational tracking systems. Although the statistical performance of this estimation technique has been extensively investigated, it has never been analyzed from the viewpoint of the joint detection-estimation problem. As a consequence the historical form of the (detector-angle estimator) solution has become the usual form implemented in operational tracking systems and may restrict their accessible performance. Indeed, the application of the optimal detection theory reveals alternative (detector-angle estimator) solutions providing other relevant trade-offs in detection-estimation performances that are worth considering to optimize the performance of the tracking system according to the scenario. Both stochastic signal model (Rayleigh-type signal source) and deterministic signal model (signal source of unknown amplitude) have been investigated, leading to a novel but equally simple (detector-angle estimator) solution through which analytical statistical prediction has been derived. Comparison of detection-estimation performances of new and usual solutions is presented.

Published
2010

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