Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties
Source localization based on time of arrival (TOA) measurements in the presence of clock asynchronization and sensor position uncertainties is investigated in this paper. Different from the traditional numerical algorithms, a neural circuit named Lagrange programming neural network (LPNN) is employe...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-07-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/7/2293 |
| _version_ | 1818033748364492800 |
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| author | Changgui Jia Jiexin Yin Ding Wang Li Zhang |
| author_facet | Changgui Jia Jiexin Yin Ding Wang Li Zhang |
| author_sort | Changgui Jia |
| collection | DOAJ |
| description | Source localization based on time of arrival (TOA) measurements in the presence of clock asynchronization and sensor position uncertainties is investigated in this paper. Different from the traditional numerical algorithms, a neural circuit named Lagrange programming neural network (LPNN) is employed to tackle the nonlinear and nonconvex constrained optimization problem of source localization. With the augmented term, two types of neural networks are developed from the original maximum likelihood functions based on the general framework provided by LPNN. The convergence and local stability of the proposed neural networks are analyzed in this paper. In addition, the Cramér-Rao lower bound is also derived as a benchmark in the presence of clock asynchronization and sensor position uncertainties. Simulation results verify the superior performance of the proposed LPNN over the traditional numerical algorithms and its robustness to resist the impact of a high level of measurement noise, clock asynchronization, as well as sensor position uncertainties. |
| first_indexed | 2024-12-10T06:28:12Z |
| format | Article |
| id | doaj.art-79eeaba874e146608cce8ba6a3911032 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-12-10T06:28:12Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-79eeaba874e146608cce8ba6a39110322022-12-22T01:59:09ZengMDPI AGSensors1424-82202018-07-01187229310.3390/s18072293s18072293Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location UncertaintiesChanggui Jia0Jiexin Yin1Ding Wang2Li Zhang3National Digital Switching System Engineering and Technology Research Center, Zhengzhou 450002, ChinaNational Digital Switching System Engineering and Technology Research Center, Zhengzhou 450002, ChinaNational Digital Switching System Engineering and Technology Research Center, Zhengzhou 450002, ChinaNational Digital Switching System Engineering and Technology Research Center, Zhengzhou 450002, ChinaSource localization based on time of arrival (TOA) measurements in the presence of clock asynchronization and sensor position uncertainties is investigated in this paper. Different from the traditional numerical algorithms, a neural circuit named Lagrange programming neural network (LPNN) is employed to tackle the nonlinear and nonconvex constrained optimization problem of source localization. With the augmented term, two types of neural networks are developed from the original maximum likelihood functions based on the general framework provided by LPNN. The convergence and local stability of the proposed neural networks are analyzed in this paper. In addition, the Cramér-Rao lower bound is also derived as a benchmark in the presence of clock asynchronization and sensor position uncertainties. Simulation results verify the superior performance of the proposed LPNN over the traditional numerical algorithms and its robustness to resist the impact of a high level of measurement noise, clock asynchronization, as well as sensor position uncertainties.http://www.mdpi.com/1424-8220/18/7/2293source localizationtime-of-arrival (TOA)clock asynchronizationsensor position uncertaintiesLagrange programming neural network (LPNN)analog neural network |
| spellingShingle | Changgui Jia Jiexin Yin Ding Wang Li Zhang Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties Sensors source localization time-of-arrival (TOA) clock asynchronization sensor position uncertainties Lagrange programming neural network (LPNN) analog neural network |
| title | Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties |
| title_full | Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties |
| title_fullStr | Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties |
| title_full_unstemmed | Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties |
| title_short | Lagrange Programming Neural Network for TOA-Based Localization with Clock Asynchronization and Sensor Location Uncertainties |
| title_sort | lagrange programming neural network for toa based localization with clock asynchronization and sensor location uncertainties |
| topic | source localization time-of-arrival (TOA) clock asynchronization sensor position uncertainties Lagrange programming neural network (LPNN) analog neural network |
| url | http://www.mdpi.com/1424-8220/18/7/2293 |
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