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Improved Multi-object Tracking Algorithm for Forward Looking Sonar Based on Rotation Estimation

  • Xiufen YeEmail author
  • Xinglong Ma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11741)

Abstract

Multi-object tracking algorithm for forward-looking sonar (FLS) often requires carrier motion information, in order to correct the tracking error caused by the carrier motion. However, it is sometimes difficult to obtain carrier information or synchronize the sonar image with carrier attitude sensor data. Therefore, it is still meaningful to study tracking multiple objects without using carrier motion information. In this paper we focus on improving the performance of multi object tracking without navigation data when the sonar carrier is rotating. The traditional detection-by-tracking framework was improved by rotation estimation. A linear motion model in polar coordinate system was used, and both detection and data association were performed in polar coordinates system. Phase correction was used to estimate the rotation velocity. The velocity was added to the motion model as a control. The improved method was tested on real sonar sequence obtained in conditions which carrier rotated several times. For evaluating the algorithm, we presented a simple approach for object detection. Finally, the results of several tracking metrics show better performance compared with conventional tracking method.

Keywords

Forward looking sonar Multi-object tracking Motion estimation 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 41876100), the State Key Program of National Natural Science Foundation of China (Grant No. 61633004), the National key research and development program of China (Grant No. 2018YFC0310102 and 2017YFC0306002), the Development Project of Applied Technology in Harbin (Grant No. 2016RAXXJ071) and the Fundamental Research Funds for the Central Universities (Grant No. HEUCFP201707).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Harbin Engineering UniversityHarbinChina

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