High-speed Target Research Articles

АНАЛІЗ АКУСТИЧНИХ СИГНАЛІВ ЗАСОБІВ ПОВІТРЯНОГО НАПАДУ

This paper analyzes the acoustic signals of aerodynamic aerial attack weapons used by the Russian Federation during a full-scale invasion. These include strike unmanned aerial vehicles, cruise missiles, jet and turboprop aircraft, and helicopters. It has been established that the time for observing an acoustic signal is limited by the speed of the vehicle. For high-speed targets (cruise missiles, airplanes), it averages 10 s, and for slower targets, 40-50 s. The Welch periodogram method was used to extract the spectral characteristics of acoustic signals. It is shown that the acoustic signal of propeller-driven vehicles is the sum of harmonic and noise-like broadband components, and that of turbojet-powered vehicles has a predominantly noise-like structure with several narrowband components. It was found that at the moment of maximum convergence, the signal spectrum has the greatest width. The characteristic change in the frequency of harmonic components associated with the Doppler effect is investigated. It can be used to estimate the parameters of motion and identify the vehicle. By correlation analysis of acoustic signals, it was found that broadband components have a noise-like structure. An acoustic signal for the case of simultaneous over flight of different types of vehicles was formed by adding records of different acoustic signals. It is shown that the characteristic spectral characteristics of all objects are preserved on the frequency-time plane. The results of the analysis can be used to build mathematical models of acoustic signals and to develop methods for processing signals of aerial attack weapons in an acoustic airspace monitoring system. Keywords: aerial attack weapons; acoustic signal; spectrogram; acoustic monitoring system; harmonic component.

Radar detection and speed estimation of high‐speed targets using phase‐modulated waveforms

AbstractSpecifying parameters of high‐speed targets as range and velocity in radar systems operating with phase‐modulated signals is a problematic process because of the serious effect of high Doppler frequency on these types of waveforms. In the existence of a high‐speed target, its Doppler frequency will be very high such that it totally changes the phase sequence of the received signal. As a result, the matched filter output will be distorted. Therefore, estimating target parameters will be impossible. In this letter, a new method is proposed for detecting and estimating velocity of high speed targets using phase‐modulated signals. The suggested technique methodology depends on compensating the target high‐Doppler frequency for signal recovery using a customized waveform shape. Moreover, the Doppler frequency value is estimated without ambiguity from one pulse, and without the need for a range‐Doppler module. As such, the implementation of the proposed method is simple and inexpensive. The performance evaluation of the new method shows its superiority in compensation and estimation compared to other techniques when examined under higher Doppler frequency and noise compared to the conventional radar.

Snapshot-Type Polarization Spectral Imaging Resolution Enhancement Based on Dual-Channel Complementary Microarray Coding Imaging Fusion

Snapshot-type polarization spectral imaging is a crucial dynamic high-speed target detection method in remote sensing in space because it has a high temporal resolution. However, the sparse representation of snapshot-type imaging in spectral or spatial dimension leads to low spectral or spatial resolution. To resolve the problem we propose double-channel complementary microarray coding snapshot-type polarization spectral imaging by utilizing the transmission and reflection complementary principle of a single microarray coding plate, the dual-channel multispectral and hyper-spectral image fused to enhancing the resolution of polarization spectral imaging. This study combined with the principle of intensity modulation used in full polarization measurements, and established the spectral modulation and reconstruction model of dual-channel complementary microarray coding. According to the principle of dual-channel complementary snapshot polarization spectral imaging proposed in this paper, the dual-channel multispectral and hyper-spectral image fusion model was setted up. This study improved the snapshot polarization spectral imaging spectral and spatial resolutions, increased the spatial resolution PSNR by 3 dB, and made the spectral resolution significantly higher. The findings of this study can assist in achieving high temporal resolution, high spectral resolution, high spatial resolution, and fully polarized snapshot-type polarization spectral imaging.

Imaging Characteristics of Disturbance Flow Field Surrounding a Hypersonic Target

The disturbance flow field arises naturally with hypersonic target flying in near space. In situations where traditional infrared and radar systems lose effectiveness, space-based optical detection of this surrounding flow can serve as an alternative method for detecting high-speed targets. This paper presents a remote sensing imaging analysis of the disturbance flow field surrounding a hypersnoic target at different flight altitudes and Mach numbers. Utilizing Fourier Optics and Background-Oriented Schlieren, in conjunction with the fourth-order Runge-Kutta ray tracing algorithm, the imaging blurring and imaging deviation of three typical backgrounds under the influence of the disturbance flow field are obtained. Additionally, the study analyzes the influence of flight conditions and parameters of the imaging system on the imaging characteristics, and provides optical design recommendations. The results indicate that the presence of disturbance flow fields leads to varying degrees of visually apparent blurring effects and indiscernible deviation effects on the background images. Furthermore, the profiles of the disturbance flow field are extracted, in agreement with current experimental research. This study verifies the feasibility of space-based optical detection of hypersonic targets through disturbance flow field remote sensing imaging and contributes to the advancement of imaging research in this field.

Segmented Radon Fourier Transform for Long-Time Coherent Radars

Coherent pulse integration is a well-known technique for effective target detection with increased output signal-to-noise ratio (SNR). Radon fourier transform (RFT) uses long-time coherent integration technique for improved target detection in a 3-dimensional search but increases the parameters search time. This paper presents a new approach of Segmented Radon Fourier Transform (SRFT) for fast detection of high speed targets without significantly degrading the detection performance. SRFT divides the received echo data matrix into an arbitrary number of segments along the slow time dimension of the data matrix. Each segment is a complete independent data matrix which can proceed independently and in parallel fashion. This paper implements a complete pipeline of radar receiver with SRFT to validate its integration in a radar signal processor. Experiments show that the parameters search time of SRFT is reduced by N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sub> times when compared with RFT, where N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sub> is the number of segments. There is a negligible degradation of 0.035dB in SNR when compared with standard RFT for 120 pulses. The difference is further reduced as the number of pulses are increased.

On designing good doppler tolerance waveform with low PSL of ambiguity function

Although the thumbtack-type ambiguity functions (AF) of the existing phase-coded signals are of good range-Doppler resolutions, they are not suitable for detection of high-speed targets due to their poor Doppler tolerance. In this paper, we address the design of waveform with good Doppler tolerance, which is expected to be of both diagonal-ridge-type AF and also local low peak sidelobe level (PSL). First we formulate the design model of Doppler tolerant waveform via minimizing the ratio of PSL to the minimum mainlobe level. Then, we solve the resulting fractional programming problem via quartic polynomial transfer and high-order polynomial optimization. Numerical results demonstrate the excellent Doppler tolerance and low PSL performance of our design.

Research on Head Pursuit Interception Strategy for Hypersonic Target

In the wake of countries competing to develop high-efficiency offensive weapons, high-precision systems have also developed. Due to the high speed and high maneuverability of hypersonic targets, it is always difficult to meet the accuracy and rapidity requirements by using the traditional interception mode. In order to improve the accuracy of the hypersonic target interception, a head pursuit guidance strategy is developed for hypersonic target interception in this study. Firstly, a dynamic model is established by analyzing the relative motion between the interceptor and the target, which needs to place the low-speed interceptor before the high-speed target. Subsequently, a head pursuit interception guidance strategy is presented, which controls the interceptor flight trajectory by controlling its normal acceleration to achieve a successful interception target. Finally, for the maneuvering and non-maneuvering targets, the dynamic characteristics of interceptor are analyzed, respectively, and full trajectory dynamic simulations under different conditions for the hypersonic target interception are worked out to illustrate the feasibility and robustness of the proposed guidance strategy.

중·대형함정 소형·고속 표적 대응능력 향상을 위한 5인치 지향성파편탄 적용 연구

중·대형함정 소형·고속 표적 대응능력 향상을 위한 5인치 지향성파편탄 적용 연구

Ship Defense Strategy Using a Planar Grid Formation of Multiple Drones

This article introduces a ship defense strategy using a planar grid formation of multiple drones. We handle a scenario where a high-speed target with variable velocity heads towards the ship. The ship measures the position of the target in real time. Based on the measured target, the drones guidance laws are calculated by the ships on-board computer and are sent to every drone in real time. The drones form a planar grid formation, whose center blocks the Line-Of-Sight (LOS) line connecting the target and the ship. Since the target is guided to hit its goal (ship), the drones can effectively block the target by blocking the LOS line. We enable slow drones to capture a fast target by making the drones stay close to the ship while blocking the LOS at all times. By using a grid formation of drones, we can increase the capture rate, even when there exists error in the prediction of the target’s position. To the best of our knowledge, this article is unique in using a formation of multiple drones to intercept a fast target with variable velocity. Through MATLAB simulations, the effectiveness of our multi-agent guidance law is verified by comparing it with other state-of-the-art guidance controls.

Innovative Isostatic Processing Technologies for Defence and other Strategic Applications

Powder Metallurgy (P/M) involving Cold Isostatic Pressing (CIP) and Hot Isostatic Pressing (HIP) techniques is the best suited processing route for manufacture of critical components from ceramics and highly complex metallic materials. The CIP followed by sintering route was adopted for the development of fused silica radomes for application in high-speed target seeking missiles. On the other hand, the HIP, a single-step processing technique has been used for the development of First-Wall (FW) of Test Blanket Modules (TBMs) from India Specific Reduced Activation Ferritic Martensitic (INRAFM) steel. The FW is an important component required for International Thermo-nuclear Experimental Reactor (ITER) application.The details of innovative processes which have been established to overcome the specific technical challenges for the development of CIP and HIP technologies for manufacture of silica radomes and INRAFM steel first-wall respectively for intended applications are highlighted in this paper.

이중대역 레이다를 이용한 해상 저고도 고속 표적 탐지 성능 향상 연구

Low-altitude and high-speed targets that fly close to the sea level are generally detected using a single-band moving target indicator (MTI) technique. The MTI technique detects a moving target by filtering out the sea-clutter Doppler spectrum. However, when detecting a low-altitude, high-speed target flying close to the sea, blind speed problems can occur because of the fast maneuvering characteristics of the target. Moreover, multipath phenomena and false alarm may occur due to the influence of the sea. Such problems make detection difficult. In this paper, we propose a detector suitable for high-speed targets in sea conditions using dual-band radar. Low-altitude and high-speed targets were modeled by considering the maritime situation, and robust detection against blind speed and multipath phenomena was confirmed by applying the proposed technique to the average Doppler power of the received signal in each band. Finally, simulations for various speeds and distances of the target confirmed that the proposed method showed improved target detection performance than the existing single-band method when detecting low-altitude, high-speed targets in sea conditions.

Collaborative Sensing in Perceptive Mobile Networks: Opportunities and Challenges

With the development of innovative applications that demand accurate environment information, for example, autonomous driving, sensing becomes an important requirement for future wireless networks. To this end, integrated sensing and communication (ISAC) provides a promising platform to exploit the synergy between sensing and communication, where perceptive mobile networks (PMNs) were proposed to add accurate sensing capability to existing wireless networks. The well-developed cellular networks offer exciting opportunities for sensing, including large coverage, strong computation, communication power, and, most importantly, networked sensing, where the perspectives from multiple sensing nodes can be collaboratively utilized for sensing the same target. However, PMNs also face big challenges, such as the inherent interference between sensing and communication, the complex sensing environment, and the tracking of high-speed targets by cellular networks. This article provides a comprehensive review on the design of PMNs, covering the popular network architectures, sensing protocols, standing research problems, and available solutions. Several future research directions that are critical for the development of PMNs are also discussed.

3D reconstruction of the dynamic scene with high-speed targets for GM-APD LiDAR

With the advantages of high distance resolution, long detection distance, small size, and low power consumption, Geiger-mode avalanche photodiode (GM-APD) light detection and ranging (LiDAR) has excellent potential for applications such as three-dimensional earth mapping and autonomous driving. The reconstruction for GM-APD LiDAR is based on the statistics of multiple-laser-pulse data, leading to a long imaging time. There are problems such as blurring when the targets are high-speed, which limits its application scope. A reconstruction algorithm of the dynamic scene for GM-APD LiDAR is proposed in this paper to address this problem. Firstly, the motion features (such as velocity and position) of the targets in the scene are extracted by applying the Hough transform and used as a basis to isolate the targets’ echo from the background noise, significantly reducing the noise interference. With these features, the data are corrected for the spatial location to attenuate or eliminate the effects caused by the targets’ motion. Finally, the reconstruction is completed utilizing parameter estimation. Also, we discuss the super-resolution reconstruction capability of this algorithm with sufficient data. Reconstruction results of the scene with targets moving at 100–300 m/s are demonstrated at last. Compared to the conventional algorithms, the peak signal-to-noise ratio (PSNR) is improved by 3–4 dB, and the root-mean-square error (RMSE) of distance is improved by 6–10 times. In addition to a super-resolution reconstruction of the dynamic scene, this method also enables the detection, motion feature extraction, and position prediction of high-speed moving targets in the scene, significantly expanding the application scope of GM-APD LiDAR and having good practical application value.

Signal Accumulation Method for High-Speed Maneuvering Target Detection Using Airborne Coherent MIMO Radar

The airborne coherent multi-input multi-output (MIMO) radar benefiting from coherent integration (including intra-channel integration and inter-channel integration) of multi-channel echoes can obtain superior detection performance for high-speed maneuvering targets. However, due to the coupling motion characteristic between multiple airborne platforms and high-speed targets, the range walk (RW) and Doppler walk (DW) will occur within the intra-channel integration. Besides, the inter-channel signals also exist envelope and phase differences, which will lead to the difficulty in multi-channel integration. We make contributions towards addressing these limitations. On the one hand, we establish a three-dimensional (3-D) geometrical model for high-speed maneuvering target detection with airborne coherent MIMO radar and derive the mathematical expression of radar echoes, while the generalized Radon-Fourier transform (GRFT) is utilized to simultaneously correct the RW and DW for acquiring intra-channel integration. On the other hand, we analyze the properties of GRFT outputs and propose a GRFT-domain integration method to achieve the multi-channel coherent integration. More specifically, the proposed method first constructs a set of coupling equations for the estimation of target motion parameters (i.e., position, velocity and acceleration), then, the target's motion parameters can be estimated by Newton-Raphson method and solving the linear equations. Second, in order to settle the envelope and phase differences between multi-channel echoes, the envelope alignment and phase compensation functions of inter-channel echoes are constituted based on the estimated parameters. Finally, the coherent accumulation of multi-channel echoes can be implemented. Numerical simulations demonstrate the effectiveness of the proposed method.

Pulsed laser scanning design technology under high-speed target detection

Pulsed laser scanning design technology under high-speed target detection

Transient Interference Suppression Method Based on an Improved TK Energy Operator and Fuzzy Reasoning

Since sky wave over-the-horizon radar is seriously affected by transient interference, a transient interference suppression method based on an improved Teager-Kaiser energy operator and fuzzy reasoning is proposed. Initially, due to the extraction of the information entropy of slow time samples, the resolution ability of the energy operator to short-term fluctuation characteristics is improved and used to more accurately locate transient interference. Then, four evaluation indexes are constructed to quantify the confidence of the data reconstruction results obtained via the autoregressive, subspace and smoothing methods. Finally, Dempster and Shafer evidence theory is introduced to conduct fuzzy reasoning on the various reconstruction results, and comprehensive results are obtained. The experimental results show that our proposed method has evident advantages in locating weak interference, preventing clutter broadening and maintaining high-speed target energy.

Pulse Image Sensor-Based High-Precision and High-Speed Target Tracking

Pulse Image Sensor-Based High-Precision and High-Speed Target Tracking

Finger-palm synergistic soft gripper for dynamic capture via energy harvesting and dissipation

Robotic grippers, inspired by human hands, show an extraordinary ability to manipulate objects of various shapes, sizes, or materials. However, capturing objects with varying kinetic energy remains challenging, regardless of the classical rigid-bodied or frontier soft-bodied grippers. Here, we demonstrate a rapid energy harvesting and dissipation mechanism for the soft grippers leveraging the finger-palm synergy. Theoretically and experimentally, this mechanism enables a soft gripper to reliably capture high-speed targets by dissipating and harvesting almost all the target’s kinetic energy within 30 milliseconds. The energy harvesting and dissipating capability are adjustable and can be enhanced by inflating pressure. Additionally, the harvested energy is autonomously transferred into fingers to enhance their grasping force and reduce the response time. To highlight, the grippers we developed are integrated into a six-rotor drone and successfully capture flying objects in an outdoor experiment. These results significantly advance robotics development in achieving dynamic capture of dynamic targets.

Quasi-continuous time-stretched photon Doppler velocimetry

In transient high-speed scenes such as chemical explosions, magnetic compression, electric explosion, and laser-driven flyer, the target object can accelerate from 0 to tens of km/s in a few nanoseconds. The time-stretched photon Doppler velocimetry uses the time-stretched interferometry to downscale the frequency of the Doppler shift signal in the optical domain, which breaks through the bandwidth limitations of photoelectric detectors and electrical digital to analog converters. A quasi-continuous time-stretched photon Doppler velocimetry (QT-PDV) is proposed in this paper, for the measurement of microsecond high-speed movement events. On the principle of hardware optical path, the velocity signal of the target object is encoded on multiple stretched chirp pulses, avoiding sampling interruptions and trigger condition limitations; in the signal demodulation methods, the error compensation algorithm is used to compensate for the frequency shift signal, which reduces the system error caused by the displacement and increases the effective recording time. This paper adopts the high-power nanosecond laser to drive the metal film to produce a high-speed target, where beat frequency was downscaled to 2.2 GHz from 4.4 GHz.

Bio-mimetic high-speed target localization with fused frame and event vision for edge application.

Evolution has honed predatory skills in the natural world where localizing and intercepting fast-moving prey is required. The current generation of robotic systems mimics these biological systems using deep learning. High-speed processing of the camera frames using convolutional neural networks (CNN) (frame pipeline) on such constrained aerial edge-robots gets resource-limited. Adding more compute resources also eventually limits the throughput at the frame rate of the camera as frame-only traditional systems fail to capture the detailed temporal dynamics of the environment. Bio-inspired event cameras and spiking neural networks (SNN) provide an asynchronous sensor-processor pair (event pipeline) capturing the continuous temporal details of the scene for high-speed but lag in terms of accuracy. In this work, we propose a target localization system combining event-camera and SNN-based high-speed target estimation and frame-based camera and CNN-driven reliable object detection by fusing complementary spatio-temporal prowess of event and frame pipelines. One of our main contributions involves the design of an SNN filter that borrows from the neural mechanism for ego-motion cancelation in houseflies. It fuses the vestibular sensors with the vision to cancel the activity corresponding to the predator's self-motion. We also integrate the neuro-inspired multi-pipeline processing with task-optimized multi-neuronal pathway structure in primates and insects. The system is validated to outperform CNN-only processing using prey-predator drone simulations in realistic 3D virtual environments. The system is then demonstrated in a real-world multi-drone set-up with emulated event data. Subsequently, we use recorded actual sensory data from multi-camera and inertial measurement unit (IMU) assembly to show desired working while tolerating the realistic noise in vision and IMU sensors. We analyze the design space to identify optimal parameters for spiking neurons, CNN models, and for checking their effect on the performance metrics of the fused system. Finally, we map the throughput controlling SNN and fusion network on edge-compatible Zynq-7000 FPGA to show a potential 264 outputs per second even at constrained resource availability. This work may open new research directions by coupling multiple sensing and processing modalities inspired by discoveries in neuroscience to break fundamental trade-offs in frame-based computer vision.