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Volume 46 Issue 9
Sep.  2024
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BO Juntian, ZHANG Jiahao, WANG Guohong, YU Hongbo, ZHANG Xiangyu, WANG Wantian, WANG Hengfeng. A 3D Multi Targets Track before Detect Algorithm with Self-feedback Optimization of Dual Accumulation[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3629-3636. doi: 10.11999/JEIT240057
Citation: BO Juntian, ZHANG Jiahao, WANG Guohong, YU Hongbo, ZHANG Xiangyu, WANG Wantian, WANG Hengfeng. A 3D Multi Targets Track before Detect Algorithm with Self-feedback Optimization of Dual Accumulation[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3629-3636. doi: 10.11999/JEIT240057

A 3D Multi Targets Track before Detect Algorithm with Self-feedback Optimization of Dual Accumulation

doi: 10.11999/JEIT240057
Funds:  The National Fund for Distinguished Young Scholars (52025072), The Young Elite Scientists Sponsorship Program by CAST (2021-JCJQ-QT-009), The National Natural Science Foundation of China (62271498), Shandong Provincial Natural Science Foundation, China (ZR2020MF015, ZR2020QF010)
  • Received Date: 2024-01-26
  • Rev Recd Date: 2024-04-17
  • Available Online: 2024-05-18
  • Publish Date: 2024-09-26
  • Considering the problem of 3D weak multi target detection, a 3-level Parallel-line-coordinate Transformation (PT) Track Before Detect (TBD) algorithm based on the dual accumulation self-feedback optimized is proposed in this paper. By introducing PT into TBD technology, the measurement points are transformed and accumulated sequentially on the normalized radial distance-time, azimuth angle-time and elevation angle-time planes, then the power accumulation are used to feedback the optimized binary accumulation, effectively mitigating the mutual interference between strong targets overwhelming weak targets and formation targets. Simulation results show that when the overall signal-to-clutter ratio reaches 10 dB, the overall detection probability of the proposed algorithm is close to 80%, demonstrating the effectiveness of the algorithm.
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