TY - GEN
T1 - Distributed Radar Multi-frame Detection with Least Squares Quantization
AU - Lu, Jing
AU - Zhou, Shenghua
AU - Varshney, Pramod K.
AU - Zheng, Jibin
AU - Peng, Xiaojun
AU - Liu, Hongwei
AU - Shao, Zhiqiang
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/21
Y1 - 2020/9/21
N2 - In a distributed multiple-input multiple-output (MIMO) radar system, multiple-frame local observations can be transmitted to a fusion center (FC) for a better detection performance, but the communication cost may be huge. In this paper, we study how to impose the least squares quantization (LSQ) method on distributed multi-frame detection (MFD). Local test statistics instead of raw signals are quantized by the LSQ algorithm and then a decision rule is formulated based on the dynamic-programming based MFD algorithm. Numerical results indicate that the LSQ algorithm causes an insignificant detection performance loss at three-bit LSQ quantization. Meanwhile, this method greatly reduces the computational complexity and the communications bandwidth costs.
AB - In a distributed multiple-input multiple-output (MIMO) radar system, multiple-frame local observations can be transmitted to a fusion center (FC) for a better detection performance, but the communication cost may be huge. In this paper, we study how to impose the least squares quantization (LSQ) method on distributed multi-frame detection (MFD). Local test statistics instead of raw signals are quantized by the LSQ algorithm and then a decision rule is formulated based on the dynamic-programming based MFD algorithm. Numerical results indicate that the LSQ algorithm causes an insignificant detection performance loss at three-bit LSQ quantization. Meanwhile, this method greatly reduces the computational complexity and the communications bandwidth costs.
KW - distributed MIMO radar
KW - dynamic programming
KW - least squares quantization
KW - multi-frame detection
UR - http://www.scopus.com/inward/record.url?scp=85098585996&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098585996&partnerID=8YFLogxK
U2 - 10.1109/RadarConf2043947.2020.9266325
DO - 10.1109/RadarConf2043947.2020.9266325
M3 - Conference contribution
AN - SCOPUS:85098585996
T3 - IEEE National Radar Conference - Proceedings
BT - 2020 IEEE Radar Conference, RadarConf 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Radar Conference, RadarConf 2020
Y2 - 21 September 2020 through 25 September 2020
ER -