Identification of low and slow small targets in multi-band radar requires high-precision micromotion features, while traditional data analysis provides methods with features that are not obvious and difficult to quantify. Aiming at this problem, two methods based on distance dimension transform are proposed to extract features from radar echo data, and the extracted parameters are compared and analyzed. The results show that the feature extraction accuracy of the Hilbert algorithm is better than that of the wavelet transform, and its information entropy is reduced by 6.31 bits, reduced by 91.31% compared to the wavelet transform; the signal-to-noise ratio is improved by 42.55 dB, which is about 10 times higher than that of the wavelet transform. In addition, these two feature extraction methods have the highest feature extraction accuracy for DJI Inspire 2 DJI Matrice 600 UAVs, which have been implemented in recent years, and their signal-to-noise ratios can reach up to 50.39dB. 

Xinqian Mao, Ye Yu, Weimin Jia, Guodong Jin, Yihong Li, Wei Jin, Jianwei Zhao. Research on Target Micromotion Features Extraction Based on Wavelet Transform and Hilbert Transform. Academic Journal of Engineering and Technology Science(2025), Vol. 8, Issue 2:27-35. https://doi.org/10.25236/AJETS.2025.080204.

[1] Jinpeng G, Shaoqiang C, Fawei Y, et al. Low-slow-small target detection using stepped-frequency signals in a strongly folded clutter environment[J]. IET Radar, Sonar & Navigation, 2021, 15(9): 1030-1044.

[2] Yu J, Liu Y, Bai Y, et al. A double-threshold target detection method in detecting low slow small target[J]. Procedia Computer Science, 2020, 174, 616-624.

[3] Li L Y, He S, Zhao Z, et al. Construction and development of "low, slow and small" target prevention and control system[J]. Infrared and Laser Engineering, 2023, 52(12): 282-292.

[4] Saadaoui Z F, Cheggaga N, Djabri H E N. Multi-sensory system for UAVs detection using Bayesian inference[J]. Applied Intelligence, 2023, 53(24). 29818-29844.

[5] Yang Z. Research on target recognition of UAV remote sensing image based on improved mask R-CNN model[J]. International Journal of Computational Intelligence Studies, 2023, 12(1-2): 72-91.

[6] Gu X X, Zhu M L, Wang L, et al. Wavelet transform-based feature extraction of ECG signals[J]. Software Guide, 2021, 20(05): 77-81.

[7] Huang D. Research on target recognition of UAV mapping images based on multimodal feature fusion[J]. Resource Guide, 2024, (12): 27-30+34.

[8] Wen D Y, Zhang X H, Liu J Y, et al. Research on fault feature extraction method of valve signal based on SSA-VMD[J]. Compressor Technology,2024, (03): 17-22.

[9] Huang R Q, Su M, Liu J, et al. Dynamic electromagnetic scattering feature extraction of flying birds based on wavelet transform and singular value decomposition[J]. Journal of Guangxi Normal University (Natural Science Edition), 2024, 42(04): 74-89.

[10] Zhou C J, Jia Y H, Zhang Y K, et al. Fault feature extraction method based on FCEEMD composite screening[J]. Computer Engineering and Science, 2023, 45(11): 2070-2077.

[11] Yang L, Shen R H. Comparative study of Hilbert-Yellow transform and wavelet transform in fault feature extraction[J]. Journal of Military Engineering, 2009, 30(05): 628-632.

[12] Guo Y R, Feng J H, Yang L W, et al. Seismic strong vibration feature extraction based on improved Hilbert-Yellow transform[J]. World Earthquake Engineering, 2023, 39(02): 138-147.

[13] Huang J J, Liu X X, Liu P Y. Design and implementation of unmanned aerial vehicle based on target recognition[J]. Integrated Circuit Applications, 2023, 40(12): 104-105.

[14] Jiawei J, Li W, Zhongrong L. Enhancing second-order blind identification for underdetermined operational modal analysis through bandlimited source separation[J]. Journal of Sound and Vibration, 2024, 572.

[15] Li B, Hu G X, Shi J J, et al. Rolling bearing fault feature extraction method based on multi-penalty factor optimisation VMD[J]. System Engineering and Electronic Technology, 2023, 45(11):3690-3698.

[16] Kun Z, Chaoyong M, Yonggang X, et al. Feature extraction method based on adaptive and concise empirical wavelet transform and its applications in bearing fault diagnosis[J]. Measurement, 2021, 172.

[17] Ren J, Li W, Guo C Y. Multi-target tracking algorithm based on UAV platform[J]. Radio Engineering, 2023, 53(01): 34-39.

[18] Zhang P F, Li G, Huo C Y, et al. UAV classification and identification based on dual radar micromotion feature fusion[J]. Radar Journal, 2018, 7(05): 557-564.

[19] Qu H Q, Chen Y J, Xing Z Q. Feature extraction and identification of optical fibre vibration signals based on wavelet transform[J]. Journal of Northern Polytechnic University, 2015, 27(03): 20-24.

[20] Wei J, Gu X Q, Ning F L. Hilbert time-frequency spectral feature extraction method[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2021, 49(01): 50-54.

[21] Li G. Research and application of signal analysis based on Hilbert's yellow transform and its improvement method [D]. Chengdu: Chengdu University of Technology, 2012.