Aspect angle sequences of ballistic conical targets.

<b>NOTE: </b>This dataset is part of the project IMD. We highly recommend that you first review the project details to gain a better understanding of the dataset's background.INTROIn this dataset, you can find the aspect angle sequences for four types of ballistic conical targets. The aspect angle is the angle between the radar line of sight (LOS) and the target's body axis. By combining static electric field data with interpolation methods, an approximate radar echo can be obtained. This method has already been applied in numerous related studies, such as:X. Tian, X. Bai, R. Xue, R. Qin and F. Zhou, "Fusion Recognition of Space Targets With Micromotion," in <i>IEEE Transactions on Aerospace and Electronic Systems</i>, vol. 58, no. 4, pp. 3116-3125, Aug. 2022, doi: 10.1109/TAES.2022.3145303.X. Tian, X. Bai and F. Zhou, "Recognition of Micro-Motion Space Targets Based on Attention-Augmented Cross-Modal Feature Fusion Recognition Network," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-9, 2023, Art no. 5104909, doi: 10.1109/TGRS.2023.3275991.Lee J I, Kim N, Min S, et al. Space target classification improvement by generating micro-Doppler signatures considering incident angle[J]. Sensors, 2022, 22(4): 1653.J. Dong, Q. She and F. Hou, "HRPnet: High-Dimensional Feature Mapping for Radar Space Target Recognition," in <i>IEEE Sensors Journal</i>, vol. 24, no. 7, pp. 11743-11758, 1 April1, 2024, doi: 10.1109/JSEN.2024.3361926.In our simulation, we follow basic physical principles to construct a simplified ballistic model, which is therefore not entirely accurate. The core objective of this project is to build a unified dataset to provide a benchmark for related research, rather than achieving precise modeling. HOWTOThe relationship between this data and the final dynamic echo data is well explained in the paper found at this link. The specific simulation methods, including kinematic modeling and dynamic sequence generation codes, can be found in the GitHub repository for now. Once the final proofreading is completed, they will be added under this project. Repository link: https://github.com/NilasZ/MRM.For any questions, feel free to contact us:[e-mail]@hdr.mq.edu.au<br><br>