Abstract
For the sake of solve the low-quality particles and degeneration in the process of particle filter, Multisensor information fusion based on intelligent particle filter scheme is proposed. The process is divided into two steps, On the one hand, Multi-sensor data is sent to the appropriate particle filter calculation module in order to optimize the particle distribution for the purpose updating the proposed distribution density. On the other hand, By incorporating the algorithm into the likelihood model structured by multi-sensor data, meanwhile, the low-weight particles will be modified into high-weight ones according to genetic operators and the posterior distribution will be more effectively estimated, thus high-quality particles can be obtained. Ultimately, a more precise estimate value will be achieved. A simulation experiment shows the effectiveness of the algorithm.
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Acknowledgements
This work was supported by the National Nature Science Foundation of China (Nos. 51579024, 61374114) and the Fundamental Research Funds for the Central Universities (DMU no. 3132016311, 3132016005).
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Zhang, C., Guo, C. (2016). Multisensor Information Fusion Scheme Based on Intelligent Particle Filter. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 645. Springer, Singapore. https://doi.org/10.1007/978-981-10-2669-0_19
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DOI: https://doi.org/10.1007/978-981-10-2669-0_19
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