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Performance enhancement of INS/CNS integration navigation system based on particle swarm optimization back propagation neural network

  • Qiuying Wang
  • , Yibing Li
  • , Ming Diao*
  • , Wei Gao
  • , Zhao Qi
  • *Corresponding author for this work
  • Harbin Engineering University
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

For the surface ship integrated navigation system of INS/CNS, the Star Sensor may invalidity due to the cloud weather, which leads to the integrated system cannot work anymore. To resolve the problem, an INS/CNS integrated navigation method based on particle swarm optimization back propagation neural network (PSO BPNN) is proposed in this paper. During the effective Star Sensor navigation process, the INS positioning error can be obtained and used for training PSO BPNN; when the Star Sensor is in invalid state, the already trained BPNN is used for forecasting the INS positioning error. The effectiveness of this approach was demonstrates by simulation and experimental study. The results showed that the INS/CNS integrated navigation method based on PSO BPNN can effectively estimate and compensate the INS navigation error under the star senor invalid state.

Original languageEnglish
Pages (from-to)33-45
Number of pages13
JournalOcean Engineering
Volume108
DOIs
StatePublished - 24 Aug 2015

Keywords

  • BP neural network
  • Inertial navigation
  • Integrated navigation
  • Particle swarm optimization
  • Star Sensor

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