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Laser Echo Signal Optimization Based on Dynamic Cognitive Enhancement Network
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Yan Ding, Ying Yuan, Lei Wang
Automobile Technology | 2026, (4) : 34 - 41
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Automobile Technology | 2026, (4): 34-41
Laser Echo Signal Optimization Based on Dynamic Cognitive Enhancement Network
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Yan Ding, Ying Yuan, Lei Wang
Affiliations
  • Yellow River Conservancy Technical University, Kaifeng 475004
Published: 2026-04-24 doi: 10.19620/j.cnki.1000-3703.20250551
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To address the issue of attenuation and waveform distortion in laser echo signals, laser echo signal model is constructed. Lightweight CNN-Transformer hybrid network is built to extract both local details and global temporal features of the signal, and a dynamic adjustment mechanism is designed to adaptively fuse local and global features. Furthermore, cognitive enhancement module is introduced, which utilizes an external memory bank to store and retrieve prior information from historical echoes, and optimizes feature inference through knowledge distillation loss. The results indicate that the attenuation of the laser echo is positively correlated with the severity of adverse weather conditions. Through distillation learning, the student network fully retains the core feature extraction logic of the teacher network. The proposed Dynamic Cognitive Enhancement Network algorithm reduces Mean Squared Error (MSE) by 40.2% and improves Peak Signal to Noise Ratio (PSNR) by 2.21 dB compared to the suboptimal model.

Laser echo  /  Dynamic cognitive  /  Knowledge distillation  /  Adaptive allocation  /  Hybrid network
丁燕, 袁英, 王磊. 基于动态认知增强网络算法的激光回波信号优化研究. 汽车技术, 2026 , (4) : 34 -41 . DOI: 10.19620/j.cnki.1000-3703.20250551
Yan Ding, Ying Yuan, Lei Wang. Laser Echo Signal Optimization Based on Dynamic Cognitive Enhancement Network[J]. Automobile Technology, 2026 , (4) : 34 -41 . DOI: 10.19620/j.cnki.1000-3703.20250551
Year 2026 volume Issue 4
130
32
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doi: 10.19620/j.cnki.1000-3703.20250551
  • Online Date:2026-09-23
  • Published:2026-04-24
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  • Revised:2025-10-01
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    Yellow River Conservancy Technical University, Kaifeng 475004
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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