Abstract
In substations, a localization system based on a wireless sensor network (WSN) is a challenge, because the propagation of the measured signal could be blocked by various devices. In other words, non-line-of-sight (NLOS) propagation, where the signal propagation path is occluded, will affect measurement accuracy. A novel localization method based on a two-step weighted least squares and a probability distribution function is proposed to reduce the influence of NLOS error on the localization result. In this method, the initial multi-group localization result is obtained by the two-step weight weighted least-squares method, and the probability distribution function of the target is constructed by using the initial localization results, which can effectively reduce the influence of the NLOS error on the localization result. The simulation and test results show that the proposed method can keep the coordinate error within 30 cm in the substation. Compared with the localization result of two-step weighted least-squares (TSWLS) method, the average localization error is reduced by more than 1 m. Compared with the other two similar algorithms, the localization accuracy is improved by more than 50%. The tested results show that the localization performance of the method is robustness in the NLOS environment of the substation. While ensuring stability, the proposed algorithm is less efficient than some existing ones. However, under the calculation conditions of ordinary computers, the average single-point calculation time is less than 0.1 s, which can meet the needs of applications in substations.
Highlights
In power substations, power equipment is densely populated
The residual weighted (RWGH) algorithm weights different are selected as the localization base station; results by the residual of the initial localization result to reduce the influence of the NLOS error
The RWGH algorithm weights different results by the residual of the initial localization result to reduce the influence of the NLOS error
Summary
Power equipment is densely populated. Due to the high level of voltage, there are many high-risk working areas. To improve the robustness and accuracy of the localization algorithm when using only ranging information, this paper proposes a new method based on probability distribution function. In contrast to the existing localization methods that use the NLOS prior error distribution to correct the results, the localization algorithm proposed in this paper uses the measured data acquired in real time to construct the probability distribution function of the localization target in space, and achieve the position estimation of the target. The probability distribution function of the target is constructed by using multiple sets of initial localization results, and the target coordinates are obtained This method can effectively improve the robustness of the algorithm and reduce the influence of measurement error on the localization result. By solving the optimal estimate of (4), the coordinates of the location of the target can be located
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
