Sensor network distributed computation for Direct Position Determination

Pourhomayoun, Mohammad; Fowler, Mark L.

doi:10.1109/sam.2012.6250445

Cited by 11 publications

(8 citation statements)

References 16 publications

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“…The simulation experiment is provided to illustrate the effectiveness of the proposed algorithm, which also has high-precision and super resolution properties. Appendix Solution of 10 …”

Section: Discussionmentioning

confidence: 99%

A Points Imaging Passive Localization Algorithm for Bistatic Stations in the Parallel Track and Squint Mode

Zhou¹,

Luo²,

Wu³

2017

Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 201

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Abstract. For passive localization of wideband signal sources, a points imaging passive localization algorithm is proposed with the information of time difference of arrival(TDOA) and frequency difference of arrival(FDOA). This method uses the principle of Synthetic Aperature Radar(SAR) imaging and the idea of direct position determination(DPD) for reference. The observing time is divided into fast time and slow time in sampling. On the basic of analyzing range difference of arrival(RDOA) walking in the parallel track and squint mode, the RDOA walking is corrected in fast time, and the FDOA spatial variation is compressed. Then joint TDOA and FDOA are estimated and mapped to the position of target. The results of simulation prove the effectiveness of the proposed algorithm. The proposed algorithm is especially applicable for the observing unresolved multiple targets localization with properties of high precision and super resolution.

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“…The simulation experiment is provided to illustrate the effectiveness of the proposed algorithm, which also has high-precision and super resolution properties. Appendix Solution of 10 …”

Section: Discussionmentioning

confidence: 99%

A Points Imaging Passive Localization Algorithm for Bistatic Stations in the Parallel Track and Squint Mode

Zhou¹,

Luo²,

Wu³

2017

Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 201

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“…Once ordinary nodes are localized, they remain passive and do not contribute toward localizing other ordinary nodes. Direct position determination (DPD) [87] is such as single-stage localization approach that processes all received signals together at a single MTC devices.…”

Section: Single-stagementioning

confidence: 99%

Localization in terrestrial and underwater sensor‐based m2m communication networks: architecture,classification and challenges

Karim

Mahmoud

Anpalagan

et al. 2015

Int J Communication

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Localizing machine-type communication (MTC) devices or sensors is becoming important because of the increasing popularity of machine-to-machine (M2M) communication networks for location-based applications. These include such as health monitoring, rescue operations, vehicle tracking, and wildfire monitoring. Moreover, efficient localization approaches for sensor-based MTC devices reduce the localization error and energy consumption of MTC devices. Because sensors are used as an integral part of M2M communication networks and have achieved popularity in underwater applications, research is being conducted on sensor localization in both underwater and terrestrial M2M networks. Major challenges in designing underwater localization techniques are the lack of good radio signal propagation in underwater, sensor mobility management, and ensuring network coverage in 3D underwater M2M networks. Similarly, predicting the mobility pattern of MTC devices, trading-off energy consumption and location accuracy pose great design challenges for terrestrial localization techniques. This article presents a comprehensive survey on the current state-of-the-art research on both terrestrial and underwater localization approaches for sensor-based MTC devices. It also classifies localization approaches based on several factors, identifies their limitations with potential solutions, and compares them.

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“…The first method applies the Gershgorin theorem (GT) at each sensor to allow a distributed computation of an approximation to the DPD location; we call this method Gershgorin theorem -DPD (GT-DPD). The preliminary results of using GT have been presented in [7]. In this paper, we expand those results by providing a detailed discussion of how data should be shared and used in the sensor network to achieve the best performance with GT-DPD.…”

Section: Introductionmentioning

confidence: 96%

“…As in[7] we assume that the delay can be approximated as being an integer multiple of the sampling instants.POURHOMAYOUN & FOWLER: DISTRIBUTED COMPUTATION FOR DIRECT POSITION DETERMINATION…”

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confidence: 99%

Distributed computation for direct position determination emitter location

Pourhomayoun

Fowler

2014

IEEE Trans. Aerosp. Electron. Syst.

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Classical geolocation based on time-difference-of-arrival (TDOA) and frequency-difference-of-arrival (FDOA) uses a two-stage estimation approach. The single-stage approach direct position determination (DPD) has been proposed to improve accuracy. However, unlike the classical two-stage method, the proposed DPD method does all processing at a single node. That is not desirable when computational capabilities are limited and makes the approach nonrobust to loss of the central sensor. We develop and assess several DPD variants that address these issues.

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Sensor network distributed computation for Direct Position Determination

Cited by 11 publications

References 16 publications

A Points Imaging Passive Localization Algorithm for Bistatic Stations in the Parallel Track and Squint Mode

A Points Imaging Passive Localization Algorithm for Bistatic Stations in the Parallel Track and Squint Mode

Localization in terrestrial and underwater sensor‐based m2m communication networks: architecture,classification and challenges

Distributed computation for direct position determination emitter location

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