Anti-bias Association Algorithm for Automatic Identification System and Radar Based on Bias Detection

Qi Lin; Cui Ya-qi; Xiong Wei; Wang Cong

doi:10.11999/JEIT141472

Volume 37 Issue 8

Aug. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(8): 1855-1861

Qi Lin, Cui Ya-qi, Xiong Wei, Wang Cong. Anti-bias Association Algorithm for Automatic Identification System and Radar Based on Bias Detection[J]. Journal of Electronics & Information Technology, 2015, 37(8): 1855-1861. doi: 10.11999/JEIT141472

Citation:

Qi Lin, Cui Ya-qi, Xiong Wei, Wang Cong. Anti-bias Association Algorithm for Automatic Identification System and Radar Based on Bias Detection[J]. Journal of Electronics & Information Technology, 2015, 37(8): 1855-1861. doi: 10.11999/JEIT141472

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Anti-bias Association Algorithm for Automatic Identification System and Radar Based on Bias Detection

doi: 10.11999/JEIT141472

Received Date: 2014-11-24
Rev Recd Date: 2015-04-10
Publish Date: 2015-08-19

Abstract

Abstract

The classical multi-sensor anti-bias association algorithms require complex calculation procedure, can not be used in real-time condition, for instance the algorithms based on image matching and reference topology feature. On the basis of tracks distribution feature on sea surface and Cell-Average Constant False Alarm Rate (CA-CFAR) detection theory, a real-time anti-bias association algorithm for Automatic Identification System (AIS) and the data track of radar is proposed, named confidential-association algorithm, to make real-time radar systematic error registration and multi-sensor information fusion come true. Monte-Carlo simulation results show that the accuracy of confidential-association algorithm maintains on a high level on the sea-surface environment, it has the superiority of simply calculation procedure and substantially reduces run-time in comparison to current anti-bias association algorithms. Radar automatically registration technique based on confidential-association algorithm reduces average error of the measured data by nearly 90%.
- Radar for sea,
- Anti-bias association,
- Automatic Identification System (AIS),
- Cell-Average Constant False Alarm Rate (CA-CFAR) detection,
- Real-time

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References(27)

References

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