Title | Radar Target MTD 2D-CFAR Algorithm Based on Compressive Detection |
Publication Type | Conference Paper |
Year of Publication | 2021 |
Authors | Liu, Cong, Liu, Yunqing, Li, Qi, Wei, Zikang |
Conference Name | 2021 IEEE International Conference on Mechatronics and Automation (ICMA) |
Keywords | 2D-CFAR, composability, Compressive detection, compressive sampling, compressive sensing, Doppler effect, Doppler radar, MTD, object detection, pubcrawl, radar detection, Radar measurements, resilience, Resiliency, Sensors, Solid modeling |
Abstract | In order to solve the problem of large data volume brought by the traditional Nyquist sampling theorem in radar signal detection, a compressive detection (CD) model based on compressed sensing (CS) theory is proposed by analyzing the sparsity of the radar target in the range domain. The lower sampling rate completes the compressive sampling of the radar signal on the range field. On this basis, the two-dimensional distribution of the Doppler unit is established by moving target detention moving target detention (MTD), and the detection of the target is achieved with the two-dimensional constant false alarm rate (2D-CFAR) detection algorithm. The simulation experiment results prove that the algorithm can effectively detect the target without the need for reconstruction signals, and has good detection performance. |
DOI | 10.1109/ICMA52036.2021.9512828 |
Citation Key | liu_radar_2021 |