Intelligent Methods for Pipeline Operation and Integrity

Yang, Yufeng; Zhang, Qiang; Zhang, Xixiang; Xie, Shuyi; Wu, Gang; Li, Lifeng

doi:10.1061/jpsea2.pseng-1490

Cited by 2 publications

(1 citation statement)

References 71 publications

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“…It is also applied in multi-platform passive localization at the earliest time [6]. The current major TDOA algorithms include Taylor series expansion [7], Chan algorithm [8], AML [9], SX and SI algorithm [10], Fang algorithm [11], Bias Sub and Bias Red algorithm [12], etc. Nevertheless, TDOA algorithm's computing efficiency is restricted by target solution equation.…”

Section: Introductionmentioning

confidence: 99%

A Novel Airspace Planning Algorithm for Cooperative Target Localization

et al. 2022

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With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and significant role in situation awareness. While, in addition to different passive transducer localization modes and solutions of target’s location, the reasonable planning and optimal layout of passive transducers’ location are other major factors affecting the precision of localization. Planning an optimal airspace for passive transducers is the key problem to improve the monitoring efficiency. This paper proposes the optimal layout algorithm for the cooperative platform in the space based on the geometrical relationship of cooperative localization. For example, the principle of direction location in traditional methods is simple: only two passive sensors can work, but the location accuracy of long-distance targets is low. At the same time, TDOA (Time Difference Of Arrival) location has high accuracy and good stability, but it needs at least three passive sensors to work together, which requires the most resources. In this paper, a platform optimization layout algorithm based on direction and TDOA hybrid positioning is proposed. Compared with direction positioning, it improves the long-distance positioning accuracy, reduces the number of sensors required for TDOA positioning, and reduces the resource occupancy rate. However, the TDOA positioning data mixed with direction positioning data inevitably leads to the decline of overall accuracy. In order to solve these difficulties, the weighted least square method is used to optimize the accuracy. The simulation shows that, within the designated target airspace, the optimal action airspace can be generated automatically based on the platforms’ cooperation mode. If there is no resource limitation, the airspace planning based on TDOA positioning has the highest accuracy for the target. However, in practical application, considering the resource limitation, the hybrid positioning of direction and TDOA can also meet the requirements of high accuracy and high stability. The average error is reduced by more than 45% compared with direction positioning, and the airspace occupancy is reduced by more than 30% compared with TDOA positioning. The goal of minimizing the scope of platform airspace planning is realized.

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