The results obtained from simulation-based evaluation against literature baselines give the proposed target classification accuracy of 85-92% under operational conditions, which is much higher than the CFAR baseline of 72-83% in an actual clutter environment.
Millimeter-wave (mmWave) frequency-modulated continuous-wave (FMCW) radar is currently widely deployed in modern vehicles for advanced driver-assistance systems, and is regarded as one of the most promising sensing modalities for future autonomous vehicle systems. Compared with other major vehicular sensors, such as ca...
Yudai Suzuki, Xiao-Yan Wang, Masahiro Umehira et al.· IEEE Transactions on Aerospa...· 0 citations
This paper presents the deployment and system-level characterization of an adopted multiscale decision fusion convolutional neural network (MDF-CNN) for radar-based object classification on the Xilinx Kria KR260 platform and compares two deployment configurations that differ in hardware, numerical precision, software r...
Turki Aldosari, A. Alghaihab, Saleh A. Alshebeili· Electronics· 0 citations
A preprocessing framework for 4D-radar-based 3D object detection that extracts point clouds from radar tensors while preserving object-shape information and suppressing noise and false alarms is proposed.
Woo-Jin Jung, Dong-Hee Paek, Jeongsu Park et al.· 0 citations
Synthetic Aperture Radar (SAR), utilizing its ability to actively transmit microwave signals, is widely used for military aircraft target reconnaissance and aviation safety monitoring. However, the complex background of ground-based aircraft targets, combined with the coherent imaging characteristics of SAR, results in...
Qing Guo, Hongdong Zhao, Wen-Jing Wang et al.· Radioengineering· 0 citations
This paper proposes a novel Transformer-based neural network architecture specifically designed for radar signal processing that integrates multi-head self-attention mechanisms with temporal convolutional networks to effectively model both local patterns and global dependencies in radar data.
Jun Hu, Cheng Yu, Yahui Hu et al.· International Conference on...· 0 citations
Unmanned aerial vehicle (UAV) rotor micro-Doppler signatures are important for target sensing and recognition in integrated sensing and communication (ISAC) systems. However, in practical environments, these signatures are often severely corrupted by strong dynamic and static interference, resulting in observations wit...
Zong-Qi Mo, Jia-Chen Wei, Ding-You Ma et al.· IEEE International Symposium...· 0 citations
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