Structural total least squares algorithm for locating multiple disjoint sources based on AOA/TOA/FOA in the presence of system error

Chen, Xin; Wang, Ding; Liu, Ruirui; Yin, Jianxin; Wu, Ying

doi:10.1631/fitee.1700735

Cited by 8 publications

(5 citation statements)

References 44 publications

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“…B. SHORTCOMINGS OF [48] Total least squares approach still spans its application to the TDoA localization, e.g., in [48], [52], [57]. The NM in [48] follows the framework in [47].…”

Section: Introductionmentioning

confidence: 99%

TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

Tausiesakul,

Asavaskulkiet

2024

IEEE Access

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An important service in the wireless systems for the human daily life is the information of a mobile user location. Wireless sensor network is a structure that can be used to determine the mobile user position. The time-difference-of-arrival (TDoA) technique is often considered for wireless localization due to the low cost of sensor network. In this work, the error covariance matrices are derived for predicting the error performance of the conventional closed-form constrained total least squares (CTLS) estimator. More importantly, three new Newton's methods are proposed for computing the CTLS solution in the TDoA localization. In addition, theoretical performance of both new Newton-based approaches is provided in closed forms. Numerical simulation is conducted to compare the derived theoretical prediction with the corresponding actual estimation error. It is illustrated that the two new Newton-based techniques provide better performance, in terms of lower bias and root mean square error, less computational time, and more reliability, than the former Newton-based algorithms. Furthermore, the derived expressions for the theoretical error covariance well coincide with the actual random estimation results.INDEX TERMS First-order Taylor's series expansion, error covariance, localization, time difference of arrival, Newton's method.

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“…B. SHORTCOMINGS OF [48] Total least squares approach still spans its application to the TDoA localization, e.g., in [48], [52], [57]. The NM in [48] follows the framework in [47].…”

Section: Introductionmentioning

confidence: 99%

TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

Tausiesakul,

Asavaskulkiet

2024

IEEE Access

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“…Accurate localization and navigation of autonomous underwater vehicle (AUV) is a critical focus area to a number of applications, such as underwater search and rescue, seafloor mapping, shallow water mine countermeasures, and oceanographic surveys [1][2][3][4][5][6][7][8][9][10]. Accurate localization is vital to ensure the accuracy of navigation and other applications.…”

Section: Introductionmentioning

confidence: 99%

Accurate Closed-Form Solution for Moving Underwater Vehicle Localization Using Two-Way Travel Time

et al. 2020

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Position information is essential for an underwater vehicle that can affect the performance of many other applications. Vehicle motion during the two-way travel time (TWTT) using an acoustic positioning system can affect the localization accuracy of the estimators based on the traditional static model. A new time measurement model for moving vehicle localization is presented, which compensates for the vehicle motion. The Cramér–Rao lower bounds (CRLBs) of the proposed model are derived for two different cases, where the depth of the underwater vehicle is unknown or known. Then, closed-form solutions for the two cases using the proposed model are derived and the solutions are shown analytically to reach the CRLBs. Simulations collaborate the theoretical performance of the proposed estimators and the moving model significantly improves the localization accuracy in comparison with the static model.

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“…At present, time of arrival (TOA), received signal strength indicator (RSSI), time difference of arrival (TDOA) and arrival of angle (AOA) are common ranging methods. Two methods can also be combined to complement each other, such as TOA and AOA combined position technology [4]. Location accuracy is sensitive to the spreading of NLOS and multipath effect in complicated environments with abundant barriers between the tag and anchor; thus, the influences of NOLS should be decreased or eliminated urgently [5].…”

Section: Introductionmentioning

confidence: 99%

Study on the Improved Unscented Kalman Filter Ultra-Wideband Indoor Location Algorithm based on Two-Way Time-of-Flight

Tian¹,

Li²

2018

JESTR

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Traditional indoor location technologies based on wireless sensor network have difficulty in satisfying the requirements of positioning accuracy and real-time tracking in the non-line-of-sight (NLOS) environment due to considerable errors. In this study, an indoor location and tracking algorithm for the ultra-wideband (UWB) system was proposed to solve accurate location and tracking problems of the moving target in the complicated indoor environments. First, this algorithm measured the distance between tag and anchor accurately by the two-way time-of-flight (TW-TOF) method, and then calculated the position coordinates of the tag by the CHAN algorithm after the range measurement. Second, the coordinates of tag position were used as the observation value of unscented Kalman filter (UKF) with the state updating equation of UKF modified. Finally, the real-time position states and speed of the tag could be acquired. The proposed algorithm was compared with the extended Kalman filter (EKF) through a simulation experiment. Results demonstrate that the improve UKF algorithm can realize accurate location and dynamic tracking of the moving target in the indoor NLOS environment. The location accuracy of the proposed algorithm is 33.5% higher than that of the EKF algorithm. The study can provide certain references for accurate location and tracking of the moving target in the complicated indoor environments.

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Structural total least squares algorithm for locating multiple disjoint sources based on AOA/TOA/FOA in the presence of system error

Cited by 8 publications

References 44 publications

TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton’s Methods

Accurate Closed-Form Solution for Moving Underwater Vehicle Localization Using Two-Way Travel Time

Study on the Improved Unscented Kalman Filter Ultra-Wideband Indoor Location Algorithm based on Two-Way Time-of-Flight

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