Asynchronous 2D-TDOA Localization Method

Malcic, Boris; Sajic, Slavko; Trifunović, Milan; Jovanovic, Vedran

doi:10.1109/telfor52709.2021.9653271

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…In another paper, [13], the asynchronous positioning problem is actually reduced to the problem of wireless synchronization of two separate subsets of reference nodes, both of which are locally synchronized. In yet another solutions proposed in [14] and [15], all anchor nodes are described as operating asynchronously, but after receiving a packet initiating the position estimation process from the master node, they all have to send their positioning packets at a defined point in time. Therefore, the signals from all the reference nodes are sent in a synchronized manner and the position equations correspond to the classical synchronous TDoA system.…”

Section: Introductionmentioning

confidence: 99%

Position and Orientation Estimation in Radio Network With Groups of Locally Synchronized Nodes

Sadowski,

Stefanski

2023

IEEE Access

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This article presents a positioning system with groups of locally synchronized nodes. A mobile object is equipped with a group of several synchronized receivers that are able to measure the difference in the time of arrival of signals from reference transmitters. The reference transmitters are synchronized only in local groups, with no global synchronization between groups. It is assumed that the synchronous operation of transmitters and receivers in groups does not allow for the phase-coherent emission and reception of signals, making beamforming and angle of arrival estimation impossible. The structure of the positioning system and the equations for estimating the position and orientation angle are presented, along with the Gauss-Newton algorithm for iteratively estimating the coordinates and orientation of the mobile object. The possible accuracy of the proposed solution is evaluated using dilution of precision and the Cramer-Rao lower bound. The analysis showed that although the quality of the position estimation in the proposed solution is highly dependent on the mutual location of the reference transmitters and the mobile object, the orientation angle can be estimated highly accurately, almost regardless of the mobile object location.

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Section: Introductionmentioning

confidence: 99%

Position and Orientation Estimation in Radio Network With Groups of Locally Synchronized Nodes

Sadowski,

Stefanski

2023

IEEE Access

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“…In general, the localization methods contain two main categories of two-step localization method and one-step localization method. Algorithms of two-step localization method [11][12][13][14][15][16][17][18][19][20] are commonly composed of two steps: first, each receiver station measures and computes the parameters related to the position of the target. The parameters involved in position include time difference of arrival (TDOA) [11][12][13], angle of arrival (AOA) [14][15][16][17], frequency difference of arrival (FDOA) [18][19][20], etc.…”

Section: Introductionmentioning

confidence: 99%

“…Algorithms of two-step localization method [11][12][13][14][15][16][17][18][19][20] are commonly composed of two steps: first, each receiver station measures and computes the parameters related to the position of the target. The parameters involved in position include time difference of arrival (TDOA) [11][12][13], angle of arrival (AOA) [14][15][16][17], frequency difference of arrival (FDOA) [18][19][20], etc. The second step is to construct equations using the parameters to estimate the position of the target.…”

Section: Introductionmentioning

confidence: 99%

A Fast Direct Position Determination Algorithm for LFM Signal Based on Spectrum Detection

2022

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For the purpose of simultaneously estimating and locating the linear frequency modulation (LFM) emitter with unknown parameters, an innovative approach, i.e., Fast Direct Position Determination (FDPD), is introduced. The proposed algorithm is based on maximum likelihood estimation (MLE) and spectrum detection. To improve the accuracy and overcome the dramatic complexity of plain maximum likelihood formulation, we further derive the objective function equation of Direct Position Determination (DPD) algorithm and present an enhanced strategy to solve the highly nonlinear optimization problem. By combining the two-step localization method, one-step localization method, and short-time Fourier transform (STFT), our approach realizes jointly estimation of the transmitted signal parameters and emitter localization. Simulation results show that the proposed method is superior compared to the existing DPD, and two-step localization algorithms in terms of localization error and computational complexity, especially for low signal-to-noise ratio (SNR).

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