Abstract
High resolution one-dimensional range image can be acquired with stepped frequency continuous wave, from which the information of targets derived. But sampling redundancies caused by oversampling result in failure to identify the targets in the one-dimensional range image. Nowadays, the existing solutions of sampling redundancy removal include of abandonment method, selection maximum method and maximum confidence method, which are complex in computing for stepped frequency continuous wave. In this paper, two methods are proposed to simplify the computation, namely, end-point method and full-point method. The end-point method obtains the one-dimensional range image by performing the inverse fast Fourier transform of the sampling points of the last group. The full-point method obtains the one-dimensional range image by performing an inverse fast Fourier transform of all the sampling points. The simulation shows that two methods can both reduce the amount of computation in the condition of guaranteeing the accuracy.
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Acknowledgments
The authors acknowledge the support from the National Natural Science Foundation of China (Grant No. 61401196) and the Natural Science Foundation of Jiangsu Province (Grant No. BK20140954), and also acknowledge Central University Basic Operating Expenses Project of Harbin Engineering University (Grant No. 201749), (Grant No. GK2080260144).
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Pan, Y., Diao, M., Chen, Z. (2019). Sampling Redundancy Removal Algorithms for Stepped Frequency Continuous Wave. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent, Interactive Systems and Applications. IISA 2018. Advances in Intelligent Systems and Computing, vol 885. Springer, Cham. https://doi.org/10.1007/978-3-030-02804-6_113
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DOI: https://doi.org/10.1007/978-3-030-02804-6_113
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