Abstract
Compared with other vehicle sensors, the vehicle radar has strong adaptability and it can detect targets in the harsh environment, which make the vehicle radar technology become popular in the field of vehicle sensors. However, there will be a big error in target tracking while detecting targets on the road through vehicle radar. In order to solve this problem, this paper has present a method which uses Elman neural network to study historical trajectory of the target and then predicts the next coordinates of this target. At last the improved nearest neighbor method is used to remove false alarms by combining information of the predicted coordinates and the measurement coordinates, so the target tracking can be finished. The Matlab simulation results prove that the method can improve the target tracking accuracy of vehicle radar.
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Acknowledgment
This research was financially supported by the Project of the National Natural Science Foundation of China (No. 61327802) and Program for New Century Excellent Talents (NCET-13-0923).
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Guan, Y., Feng, S., Huang, H., Chen, L. (2017). A Method for Improving Target Tracking Accuracy of Vehicle Radar. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_10
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DOI: https://doi.org/10.1007/978-3-319-68345-4_10
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