A modified sequential kalman asynchronous track fusion based on sound propagation time

Autor: xueli Sheng, Yan Wang, Mengfei Mu, Lai Song, Zeyi Wu
Rok vydání: 2022
DOI: 10.21203/rs.3.rs-2207162/v1
Popis: Abstract: This paper presents a modified sequential kalman asynchronous track fusion method based on the sound propagation time. The proposed method deals with the asynchronous issue, which is caused by different acoustic signal propagation times, for the distributed underwater acoustic detection systems. When the bearing of the target is estimated by various sensors distributed system, we adopt the the effective sound velocity approach to calculate the sound propagation time from the target signals to the receving sensors respectively. We also update the tracked target information asynchronously for distributed detection system, using the multi-sensor asynchronous sampling information. The sequential kalman filtering algorithm is employed here to achieve the asynchronous track fusion. Simulation results demonstrate that the proposed algorithm can significantly improve the location accuracy compared with the original algorithm. The adaptability of the proposed method to the addition and deletion of the fusion sensor is proved robust and has a certain application value.
Databáze: OpenAIRE