TY - JOUR
T1 - Doppler-Division MIMO Radar-Based Target Detection for Edge Sensing Systems
AU - Long, Jiamin
AU - Zheng, Le
AU - Li, Yang
AU - Liang, Can
AU - Hu, Xueyao
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2026
Y1 - 2026
N2 - Low-altitude platforms, such as uncrewed aerial vehicles (UAVs), are increasingly employed for real-time sensing in edge-enabled Internet of Things (IoT) networks, where radar-based perception is critical for situational awareness. Multiple-input multiple-output (MIMO) radar systems offer high angular resolution and spatial diversity, making them well-suited for such applications. To fully exploit the benefits of MIMO, efficient waveform designs that support simultaneous multichannel transmission are essential. Doppler division multiple access (DDMA) is a promising waveform strategy that achieves transmit orthogonality through Doppler-domain encoding, offering strong inter-channel orthogonality and supporting low-complexity implementation. However, in multitarget environments, DDMA-MIMO radar suffers from mutual shadowing effects that degrade detection performance. To address this challenge, this article proposes a double-threshold detection framework tailored for DDMA-MIMO radar in edge sensing systems. The method employs a double-threshold strategy: an adaptive first threshold based on the Akaike information criterion (AIC) selects candidate targets, and a second threshold derived via maximum likelihood estimation produces the final detections. Theoretical analysis and simulation results demonstrate that the proposed double-threshold framework consistently outperforms conventional approaches, providing robust detection and effective false alarm regulation.
AB - Low-altitude platforms, such as uncrewed aerial vehicles (UAVs), are increasingly employed for real-time sensing in edge-enabled Internet of Things (IoT) networks, where radar-based perception is critical for situational awareness. Multiple-input multiple-output (MIMO) radar systems offer high angular resolution and spatial diversity, making them well-suited for such applications. To fully exploit the benefits of MIMO, efficient waveform designs that support simultaneous multichannel transmission are essential. Doppler division multiple access (DDMA) is a promising waveform strategy that achieves transmit orthogonality through Doppler-domain encoding, offering strong inter-channel orthogonality and supporting low-complexity implementation. However, in multitarget environments, DDMA-MIMO radar suffers from mutual shadowing effects that degrade detection performance. To address this challenge, this article proposes a double-threshold detection framework tailored for DDMA-MIMO radar in edge sensing systems. The method employs a double-threshold strategy: an adaptive first threshold based on the Akaike information criterion (AIC) selects candidate targets, and a second threshold derived via maximum likelihood estimation produces the final detections. Theoretical analysis and simulation results demonstrate that the proposed double-threshold framework consistently outperforms conventional approaches, providing robust detection and effective false alarm regulation.
KW - Doppler division multiple access (DDMA)-multiple-input multiple-output (MIMO)
KW - edge sensing systems
KW - multitarget detection
UR - https://www.scopus.com/pages/publications/105019582735
U2 - 10.1109/JIOT.2025.3622411
DO - 10.1109/JIOT.2025.3622411
M3 - Article
AN - SCOPUS:105019582735
SN - 2327-4662
VL - 13
SP - 5491
EP - 5502
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 4
ER -