The Doppler effect in radio systems has been widely explored by the radio communication community. However, these studies have been limited to simple motion such as linear translation. This paper presents a model for the Doppler modulation effect, i....
At present, the micro-Doppler effects of underwater targets is a challenging new research problem. This paper studies the micro-Doppler effect of underwater targets, analyzes the moving characteristics of underwater micro-motion components, establish...
In this study, we examine the use of micro-Doppler signals produced by different blades (i.e., puller and lifting blades) to aid in radar-based target recognition of small drones. We categorize small drones into three types based on their blade types...
In this paper, an improved state-space method (SSM) is proposed for gait feature extraction. By introducing zero-phase component analysis Whitening (ZCA Whitening) and an algorithm to search estimated echo as the preprocessing method, pedestrian echo...
Micro-Doppler signals analysis has been emerging as an important topic in target identification, and relative research has been focusing on features extraction and separation of the radar signals. As a time-frequency representation, the Hilbert-Huang...
Not any radar dwell time of a drone radar is suitable for detecting micro-Doppler (or jet engine modulation, JEM) produced by the rotating blades in radar signals of drones. Theoretically, any X-band drone radar system should detect micro-Doppler of...
Micro-Doppler signatures play a crucial role in capturing target features for the radar classification task, and the time–frequency distribution method is widely used to represent micro-Doppler signatures in many applications including human ac...
Micro-Doppler, induced by micro-motion of targets, is an important characteristic of target recognition once extracted via parameter estimation methods. However, micro-Doppler is usually too significant to result in ambiguity in the terahertz band be...
This paper proposes a micro-Doppler flash detection framework for hovering unmanned aerial vehicle (UAV) detection with linear frequency modulated continuous wave (LFMCW) radar under the dual constraints of strong ground clutter and severe thermal no...
Micro-Doppler signature can convey information of detected targets and has been used for target recognition in many Radar systems. Nevertheless, micro-Doppler for the specific Forward Scattering Radar (FSR) system has yet to be analyzed and investiga...
Micro-Doppler is regarded as a unique signature of a target with micro-motions. The sophisticated recognition of the cone-shaped targets can be realized through the micro-Doppler effect. However, it is difficult to extract the micro-motion features p...
With the popularity of small-screen smart mobile devices, gestures as a new type of human–computer interaction are highly demanded. Furthermore, finger gestures are more familiar to people in controlling devices. In this paper, a new method for recog...
Micro-Doppler signature represents the micromotion state of a target, and it is used in target recognition and classification technology. The micro-Doppler frequency appears as a transition of the Doppler frequency due to the rotation and vibration o...
With the proliferation of unmanned aerial vehicles (UAVs) in both commercial and military use, the public is paying increasing attention to UAV identification and regulation. The micro-Doppler characteristics of a UAV can reflect its structure and mo...
In this paper, we propose to extract the motions of different human limbs by using interferometric radar based on the micro-Doppler-Range signature (mDRS). As we know, accurate extraction of human limbs in motion has great potential for improving the...
Human body detection is very important in the research of automotive safety technology. The extraction and analysis of human micro-motion based on frequency-modulated continuous wave (FMCW) radar is gradually receiving attention. Aimed at the modulat...
The large quantity of resident space objects orbiting Earth poses a threat to safety and efficient operations in space. Radar sensors are well suited to detecting objects in space including decommissioned satellites and debris, whereas the more commo...
The classification of targets by the use of radars has received great interest in recent years, in particular in defence and military applications, in which the development of sensor systems that are able to identify and classify threatening targets...
Human motion classification based on micro-Doppler effect has been widely used in various fields. However, the motion classification performance would be greatly degraded if the wireless environment has non-target micro-motion interference. In this c...
This paper proposes a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT) for identification of a complicated movement targets. This algorithm, consisting of a STFRFT order-changing and quick selection method...
The micro-Doppler features formed by the micro-motion of rotating blades of rotors and turbines are of great significance for aircraft target detection and recognition. Mastering the micro-motion features is the premise of radar target identification...
Micro-Doppler is a unique characteristic of targets with micro-motions, which can provide significant information for target classification and recognition. However, the monostatic radar has the shortcoming of only obtaining the radial micro-motion c...
Remote sensing techniques in the microwave frequency range have been successfully used in the context of bird, bat and insect measurements. This article breaks new ground in the analysis of freely flying insects by using a continuous-wave (CW) radar...
We propose a stacking method for ensemble learning to distinguish micro-Doppler signals generated by human walking from background noises using radar sensors. We collected micro-Doppler signals caused by four types of background noise (line of sight...
The problem of separating multicomponent micro-Doppler (m-D) signals is common in the field of radar signal processing. In some implementations, it is necessary to separate the multicomponent m-D signal that contains missing samples. To address this...
In the field of autonomous driving, it is important to protect vulnerable road users (VRUs) and ensure the safety of autonomous driving effectively by improving the detection accuracy of VRUs in the driver’s field of vision. However, due to the...
With the increase in small unmanned aerial vehicle (UAV) applications in several technology areas, detection and small UAVs classification have become of interest. To cope with small radar cross-sections (RCSs), slow-flying speeds, and low flying alt...
Classifying space targets from debris is critical for radar resource management as well as rapid response during the mid-course phase of space target flight. Due to advances in deep learning techniques, various approaches have been studied to classif...
This paper investigates the use of micro-Doppler spectrogram signatures of flying targets, such as drones and birds, to aid in their remote classification. Using a custom-designed 10-GHz continuous wave (CW) radar system, measurements from different...
The micro-movement feature is recognized as one of the practical features of space target recognition in academic circles. The separation of the micro-Doppler curve of the scattering center is the key to feature extraction and parameter estimation, w...
Radio frequency interference, which makes it difficult to produce high-quality radar spectrograms, is a major issue for micro-Doppler-based human activity recognition (HAR). In this paper, we propose a deep-learning-based method to detect and cut out...
A micro-Doppler signature (m-DS) based on the rotation of drone blades is an effective way to detect and identify small drones. Deep-learning-based recognition algorithms can achieve higher recognition performance, but they needs a large amount of sa...
Recently, rapid advances in radio detection and ranging (radar) technology applications have been implemented in various fields. In particular, micro-Doppler radar has been widely developed to perform certain tasks, such as detection of buried victim...
Different from microwave radar, laser radar could be more sensitive to the micro-Doppler (m-D) effect due to its wave length. This limits the application of conventional methods, such as time–frequency based approach, since the processing needs...
We propose in this work a dynamic group sparsity (DGS) based time-frequency feature extraction method for dynamic hand gesture recognition (HGR) using millimeter-wave radar sensors. Micro-Doppler signatures of hand gestures show both sparse and struc...
To address the challenge of accurately distinguishing UAVs and birds in a low-altitude detection field, this paper proposes a classification algorithm of UAVs and birds based on L/K dual-band micro-Doppler spectrograms and Mamba. We establish a dual-...
The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a...
In this paper, we present a tailored shooting and bouncing ray (SBR) method for the fast solution of electromagnetic (EM) scattering from a moving target. And, the micro-Doppler features of the moving target are investigated using a time-frequency an...
This study investigates the use of a custom-built 10 GHz continuous wave micro-Doppler radar system to analyze external vibrations of idling vehicles under various conditions. Scenarios included different gear engagements with one occupant and parked...
The rapid increase in production of small unmanned rotorcrafts (SURs) has made real-time drone surveillance critical for airspace security. Effective SUR detection is essential for maintaining aviation safety, protecting privacy, and ensuring public...
We present a technique for the identification of human and animal movement and height using a low power millimeter-wave radar. The detection was based on the transmission of a continuous wave and heterodyning the received signal reflected from the ta...
The capability of sensors to identify individuals in a specific scenario is a topic of high relevance for sensitive sectors such as public security. A traditional approach involves cameras; however, camera-based surveillance systems lack discretion a...
This study presents a novel approach to remote speech recognition using a millimeter-wave micro-Doppler radar system operating at 94 GHz. By detecting micro-Doppler speech-related vibrations, the system enables non-contact and privacy-preserving spee...
The fine state of targets can be represented by the extracted micro-Doppler (m-D) components from the radar echo. However, current methods do not consider the specialty of the m-D components, and their performance with non-sinusoidal components is po...
Short-range radar has become one of the latest sensor technologies for the Internet of Things (IoT), and it plays an increasingly vital role in IoT applications. As the essential task for various smart-sensing applications, radar-based human activity...
This study addresses the growing concern over the impact of small unmanned aerial vehicles (UAVs), particularly rotor UAVs, on air traffic order and public safety. We propose a novel method for micro-Doppler feature extraction in multi-rotor UAVs wit...
Radar remote sensing provides an effective means of analyzing target characteristics for low-altitude surveillance, and the rapid growth and misuse of drones highlight the need for efficient classification of small aerial targets such as drones and b...
Deep learning architectures are being increasingly adopted for human activity recognition using radar technology. A majority of these architectures are based on convolutional neural networks (CNNs) and accept radar micro-Doppler signatures as input....
The purpose of this paper is to show the feasibility of grasping force control by feeding back signals of the developed micro-laser Doppler velocimeter (μ-LDV) and by discriminating whether a grasped object is slipping or not. LDV is well known as a...
The increase in drone misuse by civilian apart from military applications is alarming and need to be addressed. This drone is characterized as a low altitude, slow speed, and small radar cross-section (RCS) (LSS) target and is considered difficult to...
of 7