Extraction and Analysis of Micro-Doppler Signature in FMCW Radar

Peter, Soorya; Reddy, Vinod V.

doi:10.1109/radarconf2147009.2021.9455202

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…In this work, we propose a new type of artificial landmark for indoor localization using FMCW radar, see Fig. 1, The key idea is to employ rotating parts in the landmarks that cause a micro-Doppler pattern [22], [23] in the radar image. By this means, the detection of landmarks is significantly improved, and relative position measurements can be robustly extracted.…”

Section: A Contributionmentioning

confidence: 99%

Indoor Localization based on Short-Range Radar and Rotating Landmarks

Thormann,

Steuernagel,

Baum

2024

Preprint

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A novel concept for indoor self-localization based on relative position measurements to rotating artificial landmarks (with known positions) using short-range radar is proposed. This includes a complete processing pipeline for extracting distance and angle measurements from the raw radar data, which consists of a neural network for distance estimation, a basic angle-of-arrival estimator, and a particle filter for position tracking. Due to the ability of radar to measure range rate, i.e., the velocity in the direction of a detection, it is possible to robustly detect the landmarks by detecting and localizing their micro-Doppler pattern. This mean localization is possible even under difficult conditions (e.g., light changes). Experiments with a wheeled mobile robot and common office fans as landmarks demonstrate the effectiveness of the approach for indoor localization.

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Section: A Contributionmentioning

confidence: 99%

Indoor Localization based on Short-Range Radar and Rotating Landmarks

Thormann,

Steuernagel,

Baum

2024

Preprint

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“…Lee et al [ 26 ] proposed a method for extracting high-frequency micro-Doppler features of the FMCW lidar based on the micro-motion object signal model. Peter et al [ 27 ] proposed a new method that combined Cross Wigner Ville and Cross Wigner Hough transforms for the detection and parameter extraction of FMCW signals. However, the modulation of micro-Doppler echo frequency can also lead to offset and broadening effects of the range profile in the fast time domain.…”

Section: Introductionmentioning

confidence: 99%

Decoupling and Parameter Extraction Methods for Conical Micro-Motion Object Based on FMCW Lidar

Yang,

Liu

et al. 2024

Sensors

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Micro-Doppler time–frequency analysis has been regarded as an important parameter extraction method for conical micro-motion objects. However, the micro-Doppler effect caused by micro-motion can modulate the frequency of lidar echo, leading to coupling between structure and micro-motion parameters. Therefore, it is difficult to extract parameters for micro-motion cones. We propose a new method for parameter extraction by combining the range profile of a micro-motion cone and the micro-Doppler time–frequency spectrum. This method can effectively decouple and accurately extract the structure and the micro-motion parameters of cones. Compared with traditional time–frequency analysis methods, the accuracy of parameter extraction is higher, and the information is richer. Firstly, the range profile of the micro-motion cone was obtained by using an FMCW (Frequency Modulated Continuous Wave) lidar based on simulation. Secondly, quantitative analysis was conducted on the edge features of the range profile and the micro-Doppler time–frequency spectrum. Finally, the parameters of the micro-motion cone were extracted based on the proposed decoupling parameter extraction method. The results show that our method can effectively extract the cone height, the base radius, the precession angle, the spin frequency, and the gravity center height within the range of a lidar LOS (line of sight) angle from 20° to 65°. The average absolute percentage error can reach below 10%. The method proposed in this paper not only enriches the detection information regarding micro-motion cones, but also improves the accuracy of parameter extraction and establishes a foundation for classification and recognition. It provides a new technical approach for laser micro-Doppler detection in accurate recognition.

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“…However, the CW radar cannot determine the target range, and hence it is rarely used for surveillance purposes. Although the extraction method of the micro-Doppler signature in an FMCW radar was presented in refs [29,30], the periodicity in the spectrogram is not clearly visible. Other methods for detecting micro-Doppler signals from drones by using radar systems with different dwell times and multistatic radar can be found in refs [31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

A design of a high‐resolution frequency modulated continuous wave radar for drone detection based on spurious phase noise and discrete clutter reduction

Vu Hop,

Cao Quyen,

Van Loi

2023

IET Radar Sonar & Navi

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The authors deal with the problem of the design and manufacture of a high‐resolution FMCW radar for drone detection and classification. The difficulties of the problem are discrete clutter reduction and spurious phase noise mitigation. The discrete clutter is due to the reflected signals from land vehicles, birds etc., while the spurious phase noise is inherent in the radar signal due to the phase‐locked loop component and leakage between the transmitting and receiving paths. Both spurious phase noise and clutter will increase the system noise level and hence reduce the probability of detection of small targets such as drones and induce false alarms on the radar screen. In order to reduce discrete clutter, the authors propose a method to separate a drone from discrete clutter based on the design of the radar system parameters for a drone and its propeller detection, target's Doppler dispersion and moving characteristics. For spur mitigation, a method that focuses on the design of the isolation coefficient between transmitting and receiving paths to decrease the power of spurs below the minimum power requirement at the input of the analogue‐to‐digital converter is introduced. The results were applied by the authors to the development and manufacture of a radar with the given specifications for drone detection and classification. Different laboratory and field tests show that the spurs are mitigated and the drones are separated from discrete clutter with a range and accuracy better than the one recently published.

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Extraction and Analysis of Micro-Doppler Signature in FMCW Radar

Cited by 8 publications

References 29 publications

Indoor Localization based on Short-Range Radar and Rotating Landmarks

Indoor Localization based on Short-Range Radar and Rotating Landmarks

Decoupling and Parameter Extraction Methods for Conical Micro-Motion Object Based on FMCW Lidar

A design of a high‐resolution frequency modulated continuous wave radar for drone detection based on spurious phase noise and discrete clutter reduction

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