微动目标的微多普勒特征提取与ISAR成像

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"Micro-Doppler Signature Extraction and ISAR Imaging for Target With Micromotion Dynamics" 这篇研究论文探讨了针对具有微动特性的目标的微多普勒（Micro-Doppler，m-D）信号提取和逆合成孔径雷达（Inverse Synthetic Aperture Radar, ISAR）成像技术。微多普勒效应在频域中产生，是由于目标的微小运动导致的，这一现象在目标检测、识别和分类中具有特殊的重要性。传统的距离-多普勒算法在处理由微动动力学引起的m-D效应时无法得到清晰的ISAR图像。这是因为微动产生的m-D效应在频谱图上表现为正弦调制，而主要物体运动引起的多普勒效应则表现为直线形式。因此，m-D特征的提取关键在于如何在正弦波和直线之间进行分离。论文中提到了消除技术，这是一种常用于去除地面杂波的经典方法。作者将这种方法应用于频谱图，以此来处理m-D效应和主物体多普勒效应的分离问题。通过这种技术，可以更好地提取出微动目标的m-D特征，从而改进ISAR成像的质量和精度。微多普勒签名的提取对于理解和分析复杂动态目标如旋转机械、生物体或者有微小振动的物体至关重要。ISAR成像则能够提供目标的三维形状信息，结合m-D效应，可以更深入地理解目标的运动状态和结构特性。该研究对于雷达系统的设计和目标识别算法的优化具有重要意义。这篇论文深入研究了微多普勒效应对ISAR成像的影响，并提出了一种利用消除技术改善成像质量的方法。这对于提升雷达系统的性能，特别是在复杂环境下的目标识别能力，具有重要的理论和实践价值。

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 8, NO. 3, MAY 2011 411

Micro-Doppler Signature Extraction and ISAR

Imaging for Target With Micromotion Dynamics

Kai-ming Li, Xian-jiao Liang, Qun Zhang, Senior Member, IEEE, Ying Luo, and Hong-jing Li

Abstract—The micromotion of a target will generate a micro-

Doppler (m-D) effect in the frequency domain. The m-D effect is

regarded as a unique property of the target, which has special

signiﬁcance in target detection, identiﬁcation, and classiﬁcation.

The classical range-Doppler algorithm cannot obtain a clear in-

verse synthetic aperture radar (ISAR) image due to the m-D effect

induced by micromotion dynamics. The m-D effect induced by

periodical micromotion is represented as a sinusoidal modulation

in a spectrogram, whereas the Doppler induced by a main body is

depicted as the form of a straight line. Therefore, the extraction of

an m-D signature is transformed into the separation of a sinusoid

and a straight line. The cancellation technique is a classical method

for removing ground clutter. Based on the same principle, the

cancellation technique is applied to the spectrogram in this letter,

which successfully achieves the separation of the m-D signature

and gets the clearer ISAR image of the main body. The effective-

ness and robustness of the algorithm are proved by simulation

results.

Index Terms—Automatic target recognition (ATR), micro-

Doppler (m-D) effect, micromotion, radar imaging, spectrogram

cancellation, time–frequency analysis.

I. INTRODUCTION

SIDE from the translation of a target centroid, there are

slight movements of the target body or components, such

as vibration, rotation, or acceleration, which are named as

“micromotions” [1]. Rotation and vibration are two of the most

common forms of micromotions. In inverse synthetic aperture

radar (ISAR) imaging, the target with rotating or vibrating

parts, such as a helicopter, will generate additional frequency

modulation aside from the Doppler frequency shift caused by

the target body, which is called the “micro-Doppler (m-D) ef-

fect” [1]–[3]. The m-D effect is referred to as a unique property

of the target, which has special signiﬁcance in the detection,

classiﬁcation, and recognition of the target with micromotions.

Manuscript received May 27, 2010; revised August 4, 2010; accepted

August 19, 2010. This work was supported in part by the National Nature

Science Foundation of China under Grant 60971100 and in part by the Nature

Science Foundation of Shaanxi Province under Grant 2010JQ8007.

K. Li, X. Liang, and Y. Luo are with the Institute of Telecommunica-

tion Engineering, Air Force Engineering University, Xi’an 710077, China

(e-mail: likaiming1982@163.com; drdd111586@163.com; luoying2002521@

163.com).

Q. Zhang is with the Institute of Telecommunication Engineering, Air Force

Engineering University, Xi’an 710077, China, and also with the Key Labo-

ratory of Wave Scattering and Remote Sensing Information (Ministry of Ed-

ucation), Fudan University, Shanghai 200433, China (e-mail: zhangqunnus@

gmail.com).

H. Li is with the College of Geographical Science, Southwest University,

Chongqing 400715, China (e-mail: lihongjing3@163.com).

Color versions of one or more of the ﬁgures in this paper are available online

at http://ieeexplore.ieee.org.

Digital Object Identiﬁer 10.1109/LGRS.2010.2081660

Since the concept of the m-D effect was proposed by Chen

in 2000 [2], the extraction and separation techniques of the

m-D signature have developed rapidly. The m-D effect induced

by periodic rotation or vibration will be shown as a form

of sinusoidal modulation in the spectrogram [1]–[3]. Chen

systematically researches the m-D effect and extracts the m-D

feature by mainly using the time–frequency analysis techniques

[2], [3]; Thayaparan et al. detect and separate the m-D signature

by utilizing the adaptive joint time–frequency analysis and

wavelet transform theory [4]; Setlur et al. parameterize the m-D

signal and implement its separation [5]; Chen [6] decomposes

the m-D signal as the linear combination of independent basic

functions; Li and Ling [7] put forward an adaptive chirplet de-

composition algorithm, which has a heavy calculation burden;

Cai et al. [8] and Bai et al. [9] propound the experimental-mode

decomposition (EMD) method and the complex-valued EMD

method for the m-D signature extraction, respectively. Then,

the methods for image processing have also been introduced for

the separation of the m-D feature; Stankovic et al. [10] apply the

Radon transform to extract the m-D signature while Zhang et al.

[11] apply the Hough transform in a spectrogram to extract the

m-D signature of the targets with large rotors, but its calculation

cost is also high. Moreover, some literatures have researched

the application of the m-D effect in the signature extraction of

a target, such as the geometrical signature extraction of wheels

[12], the micromotion signature extraction of a helicopter [4],

the urban sensing and indoor sensing [13], the gait and activity

analysis of a pedestrian [1]–[4], [7], [12], [14], etc., which are

effective for automatic target recognition.

Due to the inﬂuence of the m-D effect, the image quality

of the target is deteriorated when using a traditional range-

Doppler algorithm, which brings difﬁculties for target recog-

nition. Therefore, it is necessary to separate and extract the

m-D information and then implement the ISAR imaging. A

cancellation technique is used for removing ground clutter

[15], which based on the amplitude of the echoes generated

by stationary objects on the ground is relatively stable. In this

letter, the cancellation technique is applied to a spectrogram

in terms of the similar situation under a chirp signal system,

which is effective for the extraction of the m-D signature and for

getting a clearer ISAR image. The performance of the method

is simulated and discussed, and the method is also perfected for

signature extraction and recognition for the micromotion target

with a small rotating or vibrating radius by combining with the

time–frequency analysis technique.

II. m-D E

FFECT

By taking the rotating target for example, the point scatterer

model of ISAR imaging is shown in Fig. 1. The radar is

located at the origin O of the radar coordinate system XOY .

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