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关于考虑具有不同随机特性调制信号的调相/调频噪声雷达波形分析

On the Analysis of PM/FM Noise Radar Waveforms Considering Modulating Signals with Varied Stochastic Properties.

作者信息

Pralon Leandro, Beltrao Gabriel, Barreto Alisson, Cosenza Bruno

机构信息

Brazilian Army Technological Center, 23020-470 Rio de Janeiro, Brazil.

SnT, University of Luxembourg, L-1855 Luxembourg, Luxembourg.

出版信息

Sensors (Basel). 2021 Mar 3;21(5):1727. doi: 10.3390/s21051727.

DOI:10.3390/s21051727
PMID:33802245
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7958961/
Abstract

Noise Radar technology is the general term used to describe radar systems that employ realizations of a given stochastic process as transmit waveforms. Originally, carriers modulated in amplitude by a Gaussian random signal, derived from a hardware noise source, were taken into consideration, justifying the adopted nomenclature. With the advances made in hardware as well as the rise of the software defined noise radar concept, waveform design emerges as an important research area related to such systems. The possibility of generating signals with varied stochastic properties increased the potential in achieving systems with enhanced performances. The characterization of random phase and frequency modulated waveforms (more suitable for several applications) has then gained considerable notoriety within the radar community as well. Several optimization algorithms have been proposed in order to conveniently shape both the autocorrelation function of the random samples that comprise the transmit signal, as well as their power spectrum density. Nevertheless, little attention has been driven to properly characterize the stochastic properties of those signals through closed form expressions, jeopardizing the effectiveness of the aforementioned algorithms as well as their reproducibility. Within this context, this paper investigates the performance of several random phase and frequency modulated waveforms, varying the stochastic properties of their modulating signals.

摘要

噪声雷达技术是一个通用术语,用于描述将给定随机过程的实现用作发射波形的雷达系统。最初,考虑的是由硬件噪声源产生的高斯随机信号进行幅度调制的载波,这也解释了所采用的命名法。随着硬件技术的进步以及软件定义噪声雷达概念的兴起,波形设计成为与此类系统相关的一个重要研究领域。生成具有不同随机特性信号的可能性增加了实现高性能系统的潜力。随机相位和频率调制波形(更适用于多种应用)的特性在雷达领域也获得了相当高的知名度。为了方便地塑造构成发射信号的随机样本的自相关函数及其功率谱密度,已经提出了几种优化算法。然而,很少有人关注通过闭式表达式来恰当地表征这些信号的随机特性,这损害了上述算法的有效性及其可重复性。在此背景下,本文研究了几种随机相位和频率调制波形的性能,改变了其调制信号的随机特性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/64412141d725/sensors-21-01727-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/3fdeb34ec998/sensors-21-01727-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/82e5882f1635/sensors-21-01727-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/a565c714da47/sensors-21-01727-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/a566d8006f99/sensors-21-01727-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/503c646af346/sensors-21-01727-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/0e089c0402dc/sensors-21-01727-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/3e597ec4779d/sensors-21-01727-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/5deecd9be06b/sensors-21-01727-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/64412141d725/sensors-21-01727-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/c0be1a4646b4/sensors-21-01727-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/773fdf85e561/sensors-21-01727-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/3fdeb34ec998/sensors-21-01727-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/82e5882f1635/sensors-21-01727-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/a565c714da47/sensors-21-01727-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/a566d8006f99/sensors-21-01727-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/503c646af346/sensors-21-01727-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/0e089c0402dc/sensors-21-01727-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/3e597ec4779d/sensors-21-01727-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/5deecd9be06b/sensors-21-01727-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcdd/7958961/64412141d725/sensors-21-01727-g011.jpg

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本文引用的文献

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Circular data in biology: advice for effectively implementing statistical procedures.生物学中的循环数据:有效实施统计程序的建议。
Behav Ecol Sociobiol. 2018;72(8):128. doi: 10.1007/s00265-018-2538-y. Epub 2018 Jul 11.
3
On entropy rate for the complex domain.关于复域的熵率。
IEEE Trans Signal Process. 2010 Apr 1;58(4):2409-2414. doi: 10.1109/TSP.2010.2040411.