基于ofdm的四维改进矩阵笔法遥感

Samuel P. Lavery;Tharmalingam Ratnarajah
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引用次数: 0

摘要

通信和遥感系统对有限射频(RF)频谱的需求增加,激发了双功能雷达通信(DFRC)系统的设计。从一个系统同时执行双重功能可以避免跨系统干扰。正交频分复用(OFDM)波形在电信中很常见,并且可以将来自目标的回波与传输信号进行比较,以隔离与目标的距离、速度、方位角和仰角相关的相移。通过将改进矩阵增强矩阵铅笔(MMEMP)技术扩展到四维,并补偿载波间干扰(ICI),提出了一种估计相移从而估计目标参数的方法。推导了cram - rao下限(CRLB),并对不同参数化的第五代新无线电(5G NR)系统进行了仿真,结果表明,在更小的时频资源块下,基于傅立叶和多信号分类(MUSIC)的参数估计具有更高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OFDM-Based Remote Sensing Using the 4-D Modified Matrix Pencil Method
Increased demands from communications and remote sensing systems on a limited radio frequency (RF) spectrum motivate design of dual-function radar communications (DFRC) systems. Simultaneously performing dual functions from one system circumvents cross-system interference. Orthogonal frequency-division multiplexing (OFDM) waveforms are common in telecommunications, and echoes from targets can be compared with a transmitted signal to isolate phase shifts related to targets’ ranges, velocities, azimuth angles, and elevation angles. By extending the modified matrix enhancement matrix pencil (MMEMP) technique to four dimensions, and compensating for intercarrier interference (ICI), this article presents a method of estimating the phase shifts and thereby the target parameters. The Cramér-Rao lower bound (CRLB) is derived, and differently parameterized fifth-generation new radio (5G NR)-inspired systems are simulated, demonstrating superior precision to Fourier- and multiple signal classification (MUSIC)-based parameter estimation with a much smaller time-frequency resource block.
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