Analysis of radar micro-Doppler with time-frequency transform

Chen, V.C.

doi:10.1109/ssap.2000.870167

Cited by 228 publications

(114 citation statements)

References 4 publications

Supporting

Mentioning

106

Contrasting

Order By: Relevance

“…From the joint time -frequency domain signature, the frequency and the period of vibration or rotation can be found [2,7]. The direction of movement of the target at a specific time may also be found by examining the time data and the sign of the micro-Doppler shift caused by the movement of the target.…”

Section: Mathematics Of Micro-doppler Effectmentioning

confidence: 99%

Analysis of micro-Doppler signatures

Chen

et al. 2003

IEE Proc., Radar Sonar Navig.

Self Cite

321

159

View full text Add to dashboard Cite

Mechanical vibration or rotation of a target or structures on the target may induce additional frequency modulations on the returned radar signal which generate sidebands about the target's Doppler frequency, called the micro-Doppler effect. Micro-Doppler signatures enable some properties of the target to be determined. In the paper, the micro-Doppler effect in radar is introduced and the mathematics of micro-Doppler signatures is developed. Computer simulations are conducted and micro-Doppler features in the joint time -frequency domain are exploited.

show abstract

Section: Mathematics Of Micro-doppler Effectmentioning

confidence: 99%

Analysis of micro-Doppler signatures

Chen

et al. 2003

IEE Proc., Radar Sonar Navig.

Self Cite

321

159

View full text Add to dashboard Cite

show abstract

“…Remote sensing for the recognition and classification of various human activities using radar has attracted great attention from researchers [1][2][3][4][5][6][7][8] since Victor Chen introduced micro-motion in radar observation [9][10][11], especially for finer-grained human activities (e.g., waving, jumping, picking up an object, standing with random micro-shaking, etc.). It has a critical and promising applicability in many fields, such as anti-terrorism, post-disaster search and rescue, border control, and patient monitoring in hospitals.…”

Section: Introductionmentioning

confidence: 99%

MHHT-Based Method for Analysis of Micro-Doppler Signatures for Human Finer-Grained Activity Using Through-Wall SFCW Radar

Liang

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

Ultra-wideband radar-based penetrating detection and recognition of human activities has become a focus on remote sensing in various military applications in recent years, such as urban warfare, hostage rescue, and earthquake post-disaster rescue. However, an excellent micro-Doppler signature (MDS) extracting method of human motion with high time-frequency resolution, outstanding anti-interference ability, and extensive adaptability, which aims to provide favorable and more detailed features for human activity recognition and classification, especially in the non-free space detection environment, is in great urgency. To cope with the issue, a multiple Hilbert-Huang transform (MHHT) method is proposed for high-resolution time-frequency analysis of finer-grained human activity MDS hidden in ultra-wideband (UWB) radar echoes during the through-wall detection environment. Based on the improved HHT with effective intrinsic mode function (IMF) selection according to the cosine similarity (CS) principle, the improved HHT is applied to each channel signal in the effective channel scope of the UWB radar signal and then integrated along the range direction. The activities of swinging one or two arms while standing at a spot 3 m from a wall were used to validate the abilities of the proposed method for extracting and separating the MDS of different moving body structures with a high time-frequency resolution. Simultaneously, the corresponding relationship between the frequency components in MHHT-based spectra and structures of the moving human body was demonstrated according to the radar Doppler principle combined with the principle of human body kinematics. Moreover, six common finer-grained human activities and a piaffe at different ranges under the through-wall detection environment were exploited to confirm the adaptability of the novel method for different activities and pre-eminent anti-interference ability under a low signal-noise-clutter ratio (SNCR) environment, which is critical for remote sensing in various military application, such as urban warfare, hostage rescue, earthquake post-disaster rescue.

show abstract

“…Real-time non-contact detection is an effective approach of monitoring the human physiological features, as well as the significant development direction of future life-monitoring equipment [1][2][3]. The principle is to conduct the micro-Doppler modulation for the electromagnetic wave with the partial weak periodic motion caused by the heartbeat and breathing and to extract the corresponding micro-Doppler parameters in the echo signal for realizing the extraction of physiological feature parameters [4][5][6]. At present, it has wide applications in throughwall target detection, search-and-rescue missions at disaster sites, biomedical monitoring, and other related fields [7,8].…”

Section: Introductionmentioning

confidence: 99%

Separation algorithm of vital sign signal in complex environments based on time-frequency filtering

Tian

Yang

2016

J Wireless Com Network

View full text Add to dashboard Cite

Life detection radar that combines radar technology with biomedical engineering detects human physiological signals (respiration, heartbeat, body movement, etc.) from a long distance with non-contact method. In this field, vital sign detection and parameter extraction are hot issues in current researches, and the acquisition of vital sign signal of human target with radar may very helpful. In this paper, a separation method for vital sign signals based on time-frequency filtering (TFF) is proposed, which mainly predicts the instantaneous frequency (IF) by combining the Viterbi algorithm (VA) with strong noise immunity and taking advantage of the high-resolution time-frequency transformation method with good cross-term inhibitory effect in B distribution (BD), so as to extract the weak vital sign signals in the radar echo effectively. According to the simulation result, this algorithm has good resolution precision and anti-noise performance, and it is applicable for the extraction of vital sign signals in low signal-to-noise ratio, which may provide basis for the further launch of parameter extraction of the vital sign signals.

show abstract

Analysis of radar micro-Doppler with time-frequency transform

Cited by 228 publications

References 4 publications

Analysis of micro-Doppler signatures

Analysis of micro-Doppler signatures

MHHT-Based Method for Analysis of Micro-Doppler Signatures for Human Finer-Grained Activity Using Through-Wall SFCW Radar

Separation algorithm of vital sign signal in complex environments based on time-frequency filtering

Contact Info

Product

Resources

About