面向车联网的认知雷达通信复合波形设计

doi:10.11959/j.issn.2096-3750.2021.00232

Abstract

Abstract:

The system architecture for cognitive radar-communication (CRC) transceiver was proposed.A cognitive waveforms design approach, which is suitable for simultaneously performing both data communication and target detection was presented.This approach aims at estimating target scattering coefficient (TSC) from the radar scene and facilitating high-data-rate communications.In order to minimize the mean square error (MSE) of the TSC, a convex cost function was established.The peak to average power ratio (PAPR)-constrained optimal solution was achieved by applying the Kalman filtering-based strategy to design the set of ultra-wideband (UWB) transmission pulses and embed into them the information data with the M-ary position phase shift keying modulation technique.In addition to theoretical considerations, the simulation results show an improvement in TSC estimation and target detection probability as the number of iterations increases, while still transmitting data rates in the range of several Mbit/s with low bit error rates between CRC transceivers.

Key words: radar communication network, target detection, UWB, Internet of vehicles, cognitive waveform design

CLC Number:

TN951

Yu YAO, Yanjie LI, Lenan WU, Pu MIAO, Xiaoyu TANG. Cognitive waveform design for radar-communication transceiver networks[J]. Chinese Journal on Internet of Things, 2021, 5(4): 71-80.

Figures/Tables 10

References 38

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	仿真参数
E_s	发射功率	1
ASNR	平均信噪比	8 dB
τ	时间相关系数	0.1 s
M_t	脉冲间隔	1 ms
p _fa	虚警概率	0.05
p_d	检测概率	0.95
PAPR	峰均比	3 dB
f_s	采样频率	10 GHz
f_c	UWB中心频率	3 GHz

Cognitive waveform design for radar-communication transceiver networks

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