Micro-Doppler Based Target Recognition With Radars: A Review

Hanif, Ali; Muaz, Muhammad; Hasan, Aamir; Adeel, Muhammad

doi:10.1109/jsen.2022.3141213

Cited by 56 publications

(30 citation statements)

References 122 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Human presence sensing overcomes the shortcomings of passive monitoring of infrared thermal sensors and inability to recognize small movements and stationary human bodies. It can actively determine the presence of human bodies in real time [16,17]. It has obvious low false triggering and a large sensing area, and can assist in interlocking clearance.…”

Section: Jinst 19 P05059mentioning

confidence: 99%

Development of beamline control system for Hefei Advanced Light Facility

Liu,

Chen,

Liu

et al. 2024

J. Inst.

View full text Add to dashboard Cite

The design and the control scheme of beamline control system for Hefei Advanced Light Facility (HALF;Hefei, People's Republic of China) which is under construction is described in this paper.It mainly includes, equipment protection safety, personal protection safety,fast signal interlock and status monitoring and fault diagnosis system. In this control system ,the human presence perception function has been added to the personal protection safety system. Multi-parameter status monitoring of key equipment on beamline station can automatically alarm equipment failures and send relevant personnel timely notifications. At the same time, it can also provide early warning on the health status of key equipment on the beamline. The system not only improves the safety and reliability of beamline control, but also increases the degree of automation and intelligence, reduces the workload of operation and maintenance personnel, and improves operation and maintenance efficiency.

show abstract

Section: Jinst 19 P05059mentioning

confidence: 99%

Development of beamline control system for Hefei Advanced Light Facility

Liu,

Chen,

Liu

et al. 2024

J. Inst.

View full text Add to dashboard Cite

show abstract

“…Detecting the relative motion between a radiation noise source e (Buckingham et al, 2002;Qiao et al, 2021;Gusland et al, 2021;Hanif et al, 2022), the water surface, and an underwater vehicle containing the receiving hydrophone will produce the Doppler effect, and the signal frequency collected by the hydrophone will be different from that of the original radiation sound source. This time-varying frequency difference is the Doppler frequency shift, and contains state information of the speed, distance, depth, direction of motion, and trajectory of the moving noise source (Lo, 2017).…”

Section: Introductionmentioning

confidence: 99%

Motion parameter estimation of AUV based on underwater acoustic Doppler frequency measured by single hydrophone

Rong

Xu²

2022

Front. Mar. Sci.

View full text Add to dashboard Cite

This paper describes the use of a single hydrophone to estimate the motion parameters of an autonomous underwater vehicle (AUV) from the underwater acoustic signal excited by its propulsion motor. First, the frequency range of the hydroacoustic signal radiated by the AUV motor is determined, and a detection and recognition model is designed. In the case of uniform linear motion of the AUV, the geometric relationship between the Doppler frequency shift curve of the sound source is derived and the motion model of the sound source and sound line propagation is established. An estimation algorithm for the motion parameters of multiple AUVs based on data from a single hydrophone is derived. Then, for Doppler underwater acoustic signals disturbed by independent identically distributed noise with an arbitrary probability distribution, a cumulative phase difference power amplification instantaneous frequency estimation method is proposed. This method is based on the sum of multiple logarithmic functions. Finally, the effectiveness and accuracy of the algorithm in estimating the motion parameters of multiple AUVs are verified through simulations and experiments.

show abstract

“…The micro-Doppler theory was first proposed by V. C. Chen from the US Naval Laboratory [3]; it is used to represent the Doppler effect caused by the micromotion of the various components within a target. Nowadays, micro-Doppler signatures are widely used in radar target recognition and micro-motion parameter estimation [4][5][6]. The micro-motion of the drone is generated by the propeller blade rotation, and the bird is due to the flapping of the wings.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Rotor Drone Micro-Motion Parameter Estimation Method Based on CVMD and SVD

Yang

Liang

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

It is of great significance to detect drones in airspace due to the substantial increase and regrettable misuse in the consumer market. In this paper, we establish a micro-motion theoretical model of a drone and analyze the micro-Doppler signature of rotor targets and the flicker mechanisms of the multi-rotor targets. Hence, for the target recognition problem of multi-rotor drones, a multi-rotor target micro-Doppler parameter estimation method is proposed. Firstly, a signal frequency domain segmentation method is proposed based on the complex variational mode decomposition (CVMD) to separate the high-frequency part of the high-frequency flicker in the frequency domain. Secondly, for the signal after frequency domain segmentation, a flicker time domain position method based on singular value decomposition (SVD) is proposed. Finally, by integrating CVMD frequency domain segmentation and SVD time domain positioning, the reconstruction of multi-rotor target scintillation at different speeds is realized, and the micro-motion parameters of rotor blades are successfully estimated. The simulation results show that the method has high accuracy in estimating the micro-motion parameters of a multi-rotor, which makes up for the shortage of the traditional method in estimating the micro-motion parameters of the multi-rotor target.

show abstract

Micro-Doppler Based Target Recognition With Radars: A Review

Cited by 56 publications

References 122 publications

Development of beamline control system for Hefei Advanced Light Facility

Development of beamline control system for Hefei Advanced Light Facility

Motion parameter estimation of AUV based on underwater acoustic Doppler frequency measured by single hydrophone

A Multi-Rotor Drone Micro-Motion Parameter Estimation Method Based on CVMD and SVD

Contact Info

Product

Resources

About