Explore the vast range of titles available.

Micro‐Doppler effect is a vital feature of a target that reflects its oscillatory motions apart from bulk motion and provides an important evidence for target recognition with radars. However, establishing the micro‐Doppler database poses a great challenge, since plenty of experiments are required to get the micro‐Doppler signatures of different targets for the purpose of analyses and interpretations with radars, which are dramatically limited by high cost and time‐consuming. Aiming to overcome these limits, a low‐cost and powerful simulation platform of the micro‐Doppler effects is proposed based on time‐domain digital coding metasurface (TDCM). Owing to the outstanding capabilities of TDCM in generating and manipulating nonlinear harmonics during wave‐matter interactions, it enables to supply rich and high‐precision electromagnetic signals with multiple micro‐Doppler frequencies to describe the micro‐motions of different objects, which are especially favored for the training of artificial intelligence algorithms in automatic target recognition and benefit a host of applications like imaging and biosensing. A low‐cost and high‐flexible radar micro‐Doppler signature generation platform is proposed based on metasurface. The presented metasurface contains time‐varying modulation periods, thus capable of supplying the electromagnetic signals with designable micro‐Doppler frequencies to describe micro‐motions of different objects. The proposed method is especially favored for the training of AI algorithms and benefits a host of applications like imaging and biosensing.

Future space exploration missions require increased autonomy. This is especially true for navigation, where continued reliance on Earth-based resources is often a limiting factor in mission design and selection. In response to the need for autonomous navigation, this work introduces the StarNAV framework that may allow a spacecraft to autonomously navigate anywhere in the Solar System (or beyond) using only passive observations of naturally occurring starlight. Relativistic perturbations in the wavelength and direction of observed stars may be used to infer spacecraft velocity which, in turn, may be used for navigation. This work develops the mathematics governing such an approach and explores its efficacy for autonomous navigation. Measurement of stellar spectral shift due to the relativistic Doppler effect is found to be ineffective in practice. Instead, measurement of the change in inter-star angle due to stellar aberration appears to be the most promising technique for navigation by the relativistic perturbation of starlight.

The micro‐Doppler (m‐D) effect caused by the rotational parts of the targets influences the quality of inverse synthetic aperture radar (ISAR) imaging. In this letter, a novel deep network‐assisted method is proposed to reduce the m‐D effect in ISAR imaging. The training data, including ISAR images with m‐D effect and ISAR images without m‐D effect, help the network establish non‐linear mapping relationships. The simulated and measured data results show the effectiveness of the proposed method. The micro‐Doppler (m‐D) effect caused by the rotational parts of the targets influences the quality of inverse synthetic aperture radar (ISAR) imaging. In this letter, a novel deep network‐assisted method is proposed to reduce the m‐D effect in ISAR imaging. The training data, including ISAR images with m‐D effect and ISAR images without m‐D effect, help the network establish non‐linear mapping relationships.

Accurately classifying and identifying non-cooperative targets is paramount for modern space missions. This paper proposes an efficient method for classifying and recognizing non-cooperative targets using deep learning, based on the principles of the micro-Doppler effect and laser coherence detection. The theoretical simulations and experimental verification demonstrate that the accuracy of target classification for different targets can reach 100% after just one round of training. Furthermore, after 10 rounds of training, the accuracy of target recognition for different attitude angles can stabilize at 100%.

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, establishes echo models of harmonic vibration points and plane and rotating propellers, and reveals the complex modulation laws of the micro-Doppler effect. In addition, since an echo is a multi-component signal superposed by multiple modulated signals, this paper provides a sparse reconstruction method combined with time–frequency distributions and realizes signal separation and time–frequency analysis. A MicroDopplerlet time–frequency atomic dictionary, matching the complex modulated form of echoes, is designed, which effectively realizes the concise representation of echoes and a micro-Doppler effect analysis. Meanwhile, the needed micro-motion parameter information for underwater signal detection and recognition is extracted.

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 echoes are divided into three groups according to the frequency probability density: torso, feet, and other segments. Two channels of echoes are selected as inputs to the SSM, which is employed to identify the corresponding micro-Doppler trajectory. On this basis, five gait features of torso amplitude, stride length, walking cycle, torso maximum speed, and feet maximum speed are extracted. Simulation based on the Boulic model, compared with the traditional SSM, demonstrated that there is no need to estimate the model order and that a more accurate torso micro-Doppler trajectory and effective micro-motion features of the feet can be obtained by the proposed method. Finally, 77 GHz FMCW radar was used to collect the echoes of four pedestrians. The classifier was designed based on a support vector machine (SVM), and the classification experiment verified the effectiveness of the extracted gait features.

The expeditious acquisition of information pertaining to objects through the utilization of quantum technology has been a perennial issue of concern. So far, the efficient utilization of information from dynamic objects with limited resources remains a significant challenge. Here, we realize a nonlocal integrated sensing of the object’s amplitude and phase information by combining digital spiral imaging with the correlated orbital angular momentum states. The amplitude information is utilized for object identification, while the phase information enables us to determine the rotational speed. We demonstrate the nonlocal identification of a rotating object’s shape, irrespective of its rotational symmetry, and introduce the concept of the correlated rotational Doppler effect, establishing a fundamental connection between this effect and the classical rotational Doppler effect, i.e., that both rely on extracting crucial information from the spiral spectrum of objects. The present study highlights a promising pathway towards the realization of quantum remote sensing and imaging.

A longstanding pursuit in information communication is to increase transmission capacity and accuracy, with multiplexing technology playing as a promising solution. To overcome the challenges of limited spatial information density and systematic complexity in acoustic communication, here real‐time spatiotemporal communication is proposed and experimentally demonstrated by a single sensor based on the rotational Doppler effect. The information carried in multiplexed orbital‐angular‐momentum (OAM) channels is transformed into the physical quantities of the temporal harmonic waveform and simultaneously detected by a single sensor. This single‐sensor configuration is independent of the channel number and encoding scheme. The parallel transmission of complicated images is demonstrated by multiplexing eight OAM channels and achieving an extremely‐low bit error rate (BER) exceeding 0.02%, owing to the intrinsic discrete frequency shift of the rotational Doppler effect. The immunity to inner‐mode crosstalk and robustness to noise of the simple and low‐cost communication paradigm offers promising potential to promote relevant fields. A single‐sensor‐based simple and low‐cost communication paradigm to realize the real‐time and high‐capacity acoustic OAM multiplexing communication based on rotation Doppler effect. The exemption from spatial separation and intrinsic discrete frequency shift of the mechanism gives rise to the mitigation of crosstalk and robustness to noise, evidenced by the extremely‐low bit error rate exceeding 0.02%.

The linear Doppler effect has been widely used to detect the translational motion of objects. However, it suffers difficulties in measuring the angular motion of a rotating target. In recent years, the rotational Doppler effect based on a vortex beam has been helpful to solve the problem of rotational measurement and has attracted extensive attention in remote sensing. This paper expounds the theoretical and experimental basis of the rotational Doppler effect and briefly summarizes its development for the detection of macro and micro targets. Specifically, the properties and analysis methods of a rotational Doppler shift when the vortex beam is misaligned with the rotation axis are described in detail. In addition, the existing problems and further developments in rotation detection based on the rotational Doppler effect are discussed.

Observing and controlling molecular motion and in particular rotation are fundamental topics in physics and chemistry. To initiate ultrafast rotation, one needs a way to transfer a large angular momentum to the molecule. As a showcase, this was performed by hard X-ray C1s ionization of carbon monoxide accompanied by spinning up the molecule via the recoil “kick” of the emitted fast photoelectron. To visualize this molecular motion, we use the dynamical rotational Doppler effect and an X-ray “pumpprobe” device offered by nature itself: the recoil-induced ultrafast rotation is probed by subsequent Auger electron emission. The time information in our experiment originates from the natural delay between the C1s photoionization initiating the rotation and the ejection of the Auger electron. From a more general point of view, time-resolved measurements can be performed in two ways: either to vary the “delay” time as in conventional time-resolved pump-probe spectroscopy and use the dynamics given by the system, or to keep constant delay time and manipulate the dynamics. Since in our experiment we cannot change the delay time given by the core-hole lifetime τ, we use the second option and control the rotational speed by changing the kinetic energy of the photoelectron. The recoil-induced rotational dynamics controlled in such a way is observed as a photon energydependent asymmetry of the Auger line shape, in full agreement with theory. This asymmetry is explained by a significant change of the molecular orientation during the core-hole lifetime, which is comparable with the rotational period.