On the use of calibration sensors in source localization using TDOA and FDOA measurements

Li, Jinzhou; Guo, Fei; Yang, Le; Wen-li, Jiang; Pang, Hongwei

doi:10.1016/j.dsp.2013.12.011

Cited by 34 publications

(27 citation statements)

References 25 publications

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“…Similar assumption was also utilized in [17]- [19], [24], [29]. However, as pointed out in the previous subsection, the algorithm implementation uses the estimated source position instead to produce D. The amount of error introduced is dependent on the TDOA and FDOA noise as well as satellite location errors.…”

Section: B Performance Analysismentioning

confidence: 99%

“…As in [17]- [19], it is assumed that ∆y is a zero-mean Gaussian random vector with covariance matrix Q y and ∆y is also independent of the satellite location error ∆β.…”

Section: Problem Formulationmentioning

confidence: 99%

“…T , which is assumed to be zeromean Gaussian distributed with covariance matrix Q β [14], [17]- [19], [24], [29].…”

Section: Problem Formulationmentioning

confidence: 99%

“…It is assumed that the source and calibration TDOAs and FDOAs are obtained within a short interval such that they are subject to the same time and frequency offsets and the same satellite location errors [17]- [19]. A new closed-form source geolocation algorithm is proposed for the above problem.…”

Section: Introductionmentioning

confidence: 99%

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Dual-satellite source geolocation with time and frequency offsets and satellite location errors

Liu

Yang

Mihaylova

2017

2017 20th International Conference on Information Fusion (Fusion)

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Abstract-This paper considers locating a static source on Earth using the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements obtained by a dualsatellite geolocation system. The TDOA and FDOA from the source are subject to unknown time and frequency offsets because the two satellites are imperfectly time-synchronized or frequencylocked. The satellite locations are not known accurately as well. To make the source position identifiable and mitigate the effect of satellite location errors, calibration stations at known positions are used. Achieving the maximum likelihood (ML) geolocation performance usually requires jointly estimating the source position and extra variables (i.e., time and frequency offsets as well as satellite locations), which is computationally intensive. In this paper, a novel closed-form geolocation algorithm is proposed. It first fuses the TDOA and FDOA measurements from the source and calibration stations to produce a single pair of TDOA and FDOA for source geolocation. This measurement fusion step eliminates the time and frequency offsets while taking into account the presence of satellite location errors. The source position is then found via standard TDOA-FDOA geolocation. The developed algorithm has low complexity and performance analysis shows that it attains the Cramér-Rao lower bound (CRLB) under Gaussian noises and mild conditions. Simulations using a challenging scenario with a short-baseline dual-satellite system verify the theoretical developments and demonstrate the good performance of the proposed algorithm.

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Section: B Performance Analysismentioning

confidence: 99%

“…As in [17]- [19], it is assumed that ∆y is a zero-mean Gaussian random vector with covariance matrix Q y and ∆y is also independent of the satellite location error ∆β.…”

Section: Problem Formulationmentioning

confidence: 99%

“…T , which is assumed to be zeromean Gaussian distributed with covariance matrix Q β [14], [17]- [19], [24], [29].…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dual-satellite source geolocation with time and frequency offsets and satellite location errors

Liu

Yang

Mihaylova

2017

2017 20th International Conference on Information Fusion (Fusion)

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“…Generally, the conventional localization approach employs a two-step processing. In the first step, the measurement parameters (e.g., direction of arrival (DOA) [1], time of arrival (TOA) [2], time difference of arrival (TDOA) [3], Doppler shifts [4][5][6], and frequency difference of arrival (FDOA) [7]) are extracted from the received signal. In the second step, the transmitter position is determined by these estimated parameters via maximum likelihood criterion [8] of subspace data fusion criterion [9].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Single-Step Localization Method Based on Matrix Eigen-Perturbation Theory with System Errors

Qin

Wang

2019

Electronics

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Direct position determination (DPD) is a novel technique in passive localization field recently, receiving superior localization performance compared with the conventional two-step method. The DPD estimator using Doppler shifts is first proposed by Weiss, but it is not suitable for antenna arrays. Additionally, the performance analysis of this method with system errors is absent. This study discusses the single-step localization problem based on moving arrays and exhibits the performance analysis via matrix eigen-perturbation theory with system errors. First, the DPD method using angle of arrival and Doppler shifts is introduced. Then, by adding the eigenvalue perturbations to the estimated Hermitian matrix, the asymptotic linear formulation of localization errors is derived. Consequently, the mean square error of the DPD method is available. Finally, Cramér–Rao bound without system errors is presented, providing a benchmark for the best localization precision and revealing the influence of system errors on the localization precision. Simulation results demonstrate the theoretical analysis in this study.

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Joint TDOA and FDOA Estimation Based on Keystone Transform and Chirp-Z Transform

Chen

Qiu

et al. 2022

Lecture Notes in Electrical Engineering

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On the use of calibration sensors in source localization using TDOA and FDOA measurements

Cited by 34 publications

References 25 publications

Dual-satellite source geolocation with time and frequency offsets and satellite location errors

Dual-satellite source geolocation with time and frequency offsets and satellite location errors

Performance Analysis of Single-Step Localization Method Based on Matrix Eigen-Perturbation Theory with System Errors

Joint TDOA and FDOA Estimation Based on Keystone Transform and Chirp-Z Transform

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