| Citation: | Pengcheng GUO, Zheng LIU, Dingli LUO, Jianpu LI. Range Spread Target Detection Based on OnlineEstimation of Strong Scattering Points[J]. Journal of Electronics & Information Technology, 2020, 42(4): 910-916. doi: 10.11999/JEIT190417
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The traditional range-extended target detection is usually completed under the condition of scattering point density or scattering point number priori. The detection performance is greatly reduced when the scattering point information of the target is completely unknown. To solve this problem, a Range Spread Target Detection method based on Online Estimation of Strong Scattering(OESS-RSTD) points is proposed. Firstly, the unsupervised clustering algorithm in machine learning is used to estimate the number of strong scattering points and the first detection threshold adaptively. Then, the second detection threshold is determined according to false alarm rate. Finally, the existence of the target is determined through two detection thresholds. The simulation data and the measured data are used to verify and compare with other algorithms. By comparing the Signal-to-Noise Ratio (SNR) -detection probability curves of various methods with a given false alarm probability, it is verified that the proposed method has higher robustness than the traditional algorithm, and the method does not need any priori information of target scattering points.
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