On the use of calibration emitters for TDOA source localization in the presence of synchronization clock bias and sensor location errors

Wang, Ding; Yin, Jianxin; Chen, Xin; Jia, Changgui; Wei, Fushan

doi:10.1186/s13634-019-0629-1

Cited by 7 publications

(6 citation statements)

References 82 publications

(181 reference statements)

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“…Eq. (40) can be restated in a matrix form as (41) [see (42), as shown at the bottom of the next page].…”

Section: B Pseudo-linear Equations Associated With Calibration Emittersmentioning

confidence: 99%

“…The use and geometric effects of multiple calibration emitters are studied in [41], which presents the analytical conditions under which sensor position errors can be completely eliminated in target localization through the use of multiple calibration emitters. A Taylor-series TDOA localization method with calibration emitters in the presence of synchronization clock bias and sensor location errors is proposed in [42]. Note that the above-mentioned approaches only consider a stationary source location using TDOA measurements.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Estimator for TDOA and FDOA Positioning of Multiple Disjoint Sources in the Presence of Calibration Emitters

et al. 2020

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Multiple-target localization is extensively applied in wireless connected networks. However, sensor location uncertainty is known to degrade significantly the target localization accuracy. Fortunately, calibration emitters such as unmanned aerial vehicles (UAV) with known location can be used to reduce the loss in localization accuracy due to sensor location errors. This paper is devoted to the use of UAV calibration emitters for time differences of arrival (TDOA) and frequency differences of arrival (FDOA) positioning of multiple targets. The study starts with deriving the Cramér-Rao bound (CRB) for TDOA/FDOA-based target location estimate when several UAV calibration signals are available. Subsequently, the paper presents an iterative constrained weighted least squares (ICWLS) estimator for multiple-target joint localization using TDOA/FDOA measurements from both target sources and UAV calibration emitters. The newly proposed method consists of two stages. In the first phase, the sensor locations are refined based on the calibration measurements as well as the prior knowledge of sensor locations. The second step provides the estimate of multiple-target locations by combining the measurements of target signals as well as the estimated values in the first phase. An efficient ICWLS algorithm is presented at each stage. Both the two algorithms are implemented by using matrix singular value decomposition (SVD), which is able to provide a closed-form solution and update the weighting matrix at every iteration. Finally, the convergence behavior and estimation mean-square-error (MSE) of the new estimator are deduced. Both theoretical analysis and simulation results show that the developed method can improve the TDOA/FDOA localization accuracy obviously with the help of UAV calibration emitters. INDEX TERMS Target localization, unmanned aerial vehicle (UAV), time difference of arrival (TDOA), frequency difference of arrival (FDOA), multiple targets, calibration emitters, constrained weighted least squares (CWLS), Cramér-Rao bound (CRB), singular value decomposition (SVD).

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“…Eq. (40) can be restated in a matrix form as (41) [see (42), as shown at the bottom of the next page].…”

Section: B Pseudo-linear Equations Associated With Calibration Emittersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Estimator for TDOA and FDOA Positioning of Multiple Disjoint Sources in the Presence of Calibration Emitters

et al. 2020

Self Cite

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“…Simulation results show a higher positioning accuracy for the proposed TDoA system (Du et al, 2020). Also, based on TDoA, Wang developed a system using a set of calibration sources as an estimator to reduce the attenuate influence of non-synchronization (Wang et al, 2019).…”

Section: Time Difference Of Arrival (Tdoa)mentioning

confidence: 99%

Review on Ultra Wide Band Indoor Localization

Chi

Liu

et al. 2020

IJoCED

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Ultra-Wide Band (UWB) is an important means of indoor positioning. Carrying out the research of UWB is of great significance to the development of indoor positioning technology. This article gives a review of the application of UWB in indoor positioning. The motivation and development status of UWB are introduced. UWB localization algorithms such as received signal strength indication, time of arrival, time difference of arrival are analyzed one by one. In this paper, the derivations of the algorithm are summarized. Several technical difficulties of UWB technology development and future development of UWB are presented. This paper provides researchers with a clear insight into the UWB indoor positioning system so that they can further develop other advanced techniques.

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“…Another class of calibration methods is under the premise of known DOAs and number of calibration sources [10][11][12]. Wang et al [10] studied the use of a set of calibration sources, whose locations are accurately known to an estimator, to reduce the loss in localisation accuracy caused by sensor location errors. Yang et al [11] considered the more general case when the calibration source locations are not exactly known to calibrate the non-uniform linear arrays.…”

Section: Introductionmentioning

confidence: 99%

“…Another class of calibration methods is under the premise of known DOAs and number of calibration sources [10–12]. Wang et al.…”

Section: Introductionmentioning

confidence: 99%

Direction of arrival estimation of unknown emitter by deep neural networks with array imperfections

Chen

Mao

Liu

2023

IET Radar Sonar & Navi

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In array signal processing, high‐resolution direction‐of‐arrival (DOA) estimation by eigendecomposition method requires knowledge of the array covariance matrix and an exact characterisation of the array. The dependence of most such methods on the array manifold substantially degrades their array performance when the actual sensors deviate from their assumed nominal values. This article aims at formulating a deep neural network framework for DOA estimation with feasible computational complexity. The two‐stage algorithm is composed of a detection network and a series of parallel DOA estimation networks: the multilayer perceptron is trained to detect the presence of one or more sources in an angular sector at the first stage, the DOA estimation networks then estimate their respective DOAs at the second stage. When a single type of array imperfection is considered, numerical results reveal that the DNN‐based method can obtain DOA estimates with much higher precision than the existing techniques for significant location errors and gain/phase perturbations, they also illustrate the potential usefulness of the proposed algorithm towards better DOA estimation accuracy for mutual coupling as the mutual coupling matrix is not simplified. Moreover, the proposed method is finally extended to deal with the DOA estimation problem when multiple types of array perturbations coexist.

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On the use of calibration emitters for TDOA source localization in the presence of synchronization clock bias and sensor location errors

Cited by 7 publications

References 82 publications

A Novel Estimator for TDOA and FDOA Positioning of Multiple Disjoint Sources in the Presence of Calibration Emitters

A Novel Estimator for TDOA and FDOA Positioning of Multiple Disjoint Sources in the Presence of Calibration Emitters

Review on Ultra Wide Band Indoor Localization

Direction of arrival estimation of unknown emitter by deep neural networks with array imperfections

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