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This paper concentrates on the model useful for analyzing the error performance of M-estimators of a single unknown signal parameter: that is the error intensity model. We develop the point process representation for the estimation error, the conditional distribution of the estimator, and the distribution of error candidate point process. Then the error intensity function is defined as the probability density of the estimate and the general form of the error intensity function is derived. We compute the explicit form of the intensity functions based on the local maxima model of the error generating point process. While the methods described in this paper are applicable to any estimation problem with continuous parameters, our main application will be time delay estimation. Specifically, we will consider the case where coherent impulsive interference is involved in addition to the Gaussian noise. Based on numerical simulation results, we compare each of the error intensity model in terms of the accuracy of both error probability and mean squared error (MSE) predictions, and the issue of extendibility to multiple parameter estimation is also discussed.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E83-A No.9 pp.1844-1852

- Publication Date
- 2000/09/25

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- PAPER

- Category
- General Fundamentals and Boundaries

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Joong-Kyu KIM, "Local Maxima Error Intensity Functions and Its Application to Time Delay Estimator in the Presence of Shot Noise Interference" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 9, pp. 1844-1852, September 2000, doi: .

Abstract: This paper concentrates on the model useful for analyzing the error performance of M-estimators of a single unknown signal parameter: that is the error intensity model. We develop the point process representation for the estimation error, the conditional distribution of the estimator, and the distribution of error candidate point process. Then the error intensity function is defined as the probability density of the estimate and the general form of the error intensity function is derived. We compute the explicit form of the intensity functions based on the local maxima model of the error generating point process. While the methods described in this paper are applicable to any estimation problem with continuous parameters, our main application will be time delay estimation. Specifically, we will consider the case where coherent impulsive interference is involved in addition to the Gaussian noise. Based on numerical simulation results, we compare each of the error intensity model in terms of the accuracy of both error probability and mean squared error (MSE) predictions, and the issue of extendibility to multiple parameter estimation is also discussed.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_9_1844/_p

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@ARTICLE{e83-a_9_1844,

author={Joong-Kyu KIM, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={Local Maxima Error Intensity Functions and Its Application to Time Delay Estimator in the Presence of Shot Noise Interference},

year={2000},

volume={E83-A},

number={9},

pages={1844-1852},

abstract={This paper concentrates on the model useful for analyzing the error performance of M-estimators of a single unknown signal parameter: that is the error intensity model. We develop the point process representation for the estimation error, the conditional distribution of the estimator, and the distribution of error candidate point process. Then the error intensity function is defined as the probability density of the estimate and the general form of the error intensity function is derived. We compute the explicit form of the intensity functions based on the local maxima model of the error generating point process. While the methods described in this paper are applicable to any estimation problem with continuous parameters, our main application will be time delay estimation. Specifically, we will consider the case where coherent impulsive interference is involved in addition to the Gaussian noise. Based on numerical simulation results, we compare each of the error intensity model in terms of the accuracy of both error probability and mean squared error (MSE) predictions, and the issue of extendibility to multiple parameter estimation is also discussed.},

keywords={},

doi={},

ISSN={},

month={September},}

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TY - JOUR

TI - Local Maxima Error Intensity Functions and Its Application to Time Delay Estimator in the Presence of Shot Noise Interference

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 1844

EP - 1852

AU - Joong-Kyu KIM

PY - 2000

DO -

JO - IEICE TRANSACTIONS on Fundamentals

SN -

VL - E83-A

IS - 9

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - September 2000

AB - This paper concentrates on the model useful for analyzing the error performance of M-estimators of a single unknown signal parameter: that is the error intensity model. We develop the point process representation for the estimation error, the conditional distribution of the estimator, and the distribution of error candidate point process. Then the error intensity function is defined as the probability density of the estimate and the general form of the error intensity function is derived. We compute the explicit form of the intensity functions based on the local maxima model of the error generating point process. While the methods described in this paper are applicable to any estimation problem with continuous parameters, our main application will be time delay estimation. Specifically, we will consider the case where coherent impulsive interference is involved in addition to the Gaussian noise. Based on numerical simulation results, we compare each of the error intensity model in terms of the accuracy of both error probability and mean squared error (MSE) predictions, and the issue of extendibility to multiple parameter estimation is also discussed.

ER -