Target Motion Research Articles

Time Reversal Detection for Moving Targets in Clutter Environments

Moving target detection plays a pivotal role in many applications, especially in radar systems. In addition, time-reversal (TR) technology can improve radar detection probability by effectively solving the problem of multipath signals. However, detection performance can be affected when clutter exists and target Doppler shifts are unknown. For this reason, we propose a novel moving target detection algorithm that leverages TR technology and a novel waveform optimization method in clutter and multipath signal environments. In this paper, we establish a TR signal model for a moving target in such environments and derive the TR average likelihood ratio test (TR-ALRT) detector. Additionally, we introduce a waveform optimization method that adapts to clutter and unknown Doppler information further to enhance the performance of the TR-ALRT detector. Consequently, a TR-ALRT waveform optimization (TR-ALRT-WO) detector is derived to adapt to the unknown Doppler and environment information, thereby improving the detection probability. Comparative analysis with other detectors under the same conditions validates the effectiveness of our proposed TR-ALRT-WO detector. Furthermore, numerical experiments demonstrate the superior performance of the proposed detection algorithm.

Tracking by segmentation with future motion estimation applied to person-following robots.

Person-following is a crucial capability for service robots, and the employment of vision technology is a leading trend in building environmental understanding. While most existing methodologies rely on a tracking-by-detection strategy, which necessitates extensive datasets for training and yet remains susceptible to environmental noise, we propose a novel approach: real-time tracking-by-segmentation with a future motion estimation framework. This framework facilitates pixel-level tracking of a target individual and predicts their future motion. Our strategy leverages a single-shot segmentation tracking neural network for precise foreground segmentation to track the target, overcoming the limitations of using a rectangular region of interest (ROI). Here we clarify that, while the ROI provides a broad context, the segmentation within this bounding box offers a detailed and more accurate position of the human subject. To further improve our approach, a classification-lock pre-trained layer is utilized to form a constraint that curbs feature outliers originating from the person being tracked. A discriminative correlation filter estimates the potential target region in the scene to prevent foreground misrecognition, while a motion estimation neural network anticipates the target's future motion for use in the control module. We validated our proposed methodology using the VOT, LaSot, YouTube-VOS, and Davis tracking datasets, demonstrating its effectiveness. Notably, our framework supports long-term person-following tasks in indoor environments, showing promise for practical implementation in service robots.

A Coherent Integration and Parameter Estimation Method for Constant Radial Acceleration Weak Target via SOKT-IAR-LVD

In order to enhance the detection and parameter estimation capacity to the maneuvering target with complex motions, a low complexity coherent integration and parameter estimation method named SOKT-IAR-LVD is proposed in this paper. In SOKT-IAR-LVD, first, the second-order keystone transform (SOKT) is utilized to eliminate the range curvature induced by target acceleration. Second, improved axis rotation (IAR) is applied to regulate the linear range migration by rotating the fast time axis and the target envelope is aligned along the slow time axis with a quadratic phase characteristic. At last, the target signal is coherently integrated via the Lv’s Distribution (LVD) transform. The target motion parameters, including range, velocity, and acceleration, are estimated by the IAR and LVD results. The integration gain and computational load of SOKT-IAR-LVD are analyzed. Without needing to estimate the Doppler ambiguity number and target acceleration, the computational burden of SOKT-IAR-LVD is three orders of magnitude lower than that of the Radon-Lv’s Distribution (RLVD) method. Simulation results demonstrate that the detection performance of SOKT-IAR-LVD is almost the same as that of RLVD and that the required input SNR of SOKT-IAR-LVD is 17.4 dB lower than that of SOKT–Radon Fourier transform (SOKT-RFT) when the detection threshold is set to 12 dB.

A motor plan is accessible for voluntary initiation and involuntary triggering at similar short latencies.

Movement goals are an essential component of motor planning, altering voluntary and involuntary motor actions. While there have been many studies of motor planning, it is unclear if motor goals influence voluntary and involuntary movements at similar latencies. The objectives of this study were to determine how long it takes to prepare a motor action and to compare this time for voluntary and involuntary movements. We hypothesized a prepared motor action would influence voluntarily and involuntarily initiated movements at the same latency. We trained subjects to reach with a forced reaction time paradigm and used a startling acoustic stimulus (SAS) to trigger involuntary initiation of the same reaches. The time available to prepare was controlled by varying when one of four reach targets was presented. Reach direction was used to evaluate accuracy. We quantified the time between target presentation and the cue or trigger for movement initiation. We found that reaches were accurately initiated when the target was presented 48ms before the SAS and 162ms before the cue to voluntarily initiate movement. While the SAS precisely controlled the latency of movement onset, voluntary reach onset was more variable. We, therefore, quantified the time between target presentation and movement onset and found no significant difference in the time required to plan reaches initiated voluntarily or involuntarily (∆ = 8ms, p = 0.2). These results demonstrate that the time required to plan accurate reaches is similar regardless of if they are initiated voluntarily or triggered involuntarily. This finding may inform the understanding of neural pathways governing storage and access of motor plans.

Building the method for multi-target tracking based on the combination of PHD filter and JPDA filter using particle filter in 3D mixed coordinate system

Changing the target number, non-linear measurement models and non-Gaussian noise faces a challenge to multi-target tracking problems which are factors affecting the accuracy, execution time and deciding the success of the method as well. In this paper, the authors present a method to solve these problems. Wherein, the motion of targets is represented in the mixed coordinate system 3D base on combining PHD (Probability Hypothesis Density) and JPDA (Joint Probability Data Association). This method can track multiple targets in the most general case, that is to change the target number, system model and measurement model which is non-linear as the noise is non-Gaussian. The result of this work can be applied to the real-time response system when the targets are moving in close distances with rapid maneuvering.

Infrared moving small target detection based on spatial-temporal local contrast under slow-moving cloud background

It is intractable to detect infrared moving small targets under slow-moving clouds, because small targets are weak so that they may be submerged in clouds, in addition to cloud edges are difficult to distinguish from them. To overcome these obstacles, a robust spatial–temporal local contrast method for infrared moving small targets is proposed. Firstly, the spatial–temporal local energy change saliency (STLECS) map is designed to discriminate whether interframe local energy changes are caused by cloud slow-motion or target motion. In addition, a multi-directional interval minimum gradient (MDIMG) map is also constructed to measure the difference between the target and the background edge on the gradient distribution. To further enhance the saliency of moving targets in space–time domain, a fused spatial -temporal saliency (FSTS) map is obtained by combining the STLECS map and the MDIMG map, and an adaptive threshold is applied to this fused map to segment real targets. The performance experiment results based on real images show that the proposed method has the better performance compared to other state-of-the-art contrast-based methods.

Planning strategies for robust carbon-ion scanning radiotherapy for stage I esophageal cancer: a retrospective study.

This study aimed to establish a treatment planning strategy with carbon-ion scanning radiotherapy (CIRTs) for stage I esophageal cancer. The clinical data of seven patients treated with CIRTs were used. The setup error and interfractional and intrafractional motion error were analyzed using in-room computed tomography (CT) images for each treatment day. Finally, the planning target volume (PTV) margin was identified according to the accuracy of the treatment system. To ensure robustness against the positional displacements of the target and organs at risk (OAR), the replacement areas were placed as a contour adjacent to the tumor or OAR on the CT-image. The CT values of these areas were replaced by those of the target or OAR. Further, the dose distributions were optimized. Moreover, the variations in the target coverage from the initial plan for each treatment day (ΔV95%) were evaluated. By contrast, the risk of OAR was not evaluated in this study. The setup error was within 1.0mm. The interfractional and intrafractional target motion errors were 2.8 and 5.0mm, respectively. The PTV margins were 6.5 and 6.8mm in the axial and depth directions, respectively. The robustness to target and OAR displacement was evaluated. The results showed that the target coverage with replacement could suppress decreased target coverage more than that without replacement. The PTV determination and replacement methods used in this study improved the target coverage in CIRTs for stage I esophageal cancer. Despite the need for a clinical follow-up, this method may help to improve clinical outcomes.

Reduced attentional inhibition for peripheral distractors of angry faces under central perceptual load in deaf individuals: evidence from an event-related potentials study.

Studies have shown that deaf individuals distribute more attention to the peripheral visual field and exhibit enhanced visual processing for peripheral stimuli relative to hearing individuals. This leads to better detection of peripheral target motion and simple static stimuli in hearing individuals. However, when threatening faces that represent dangerous signals appear as non-targets in the periphery, it remains unclear whether deaf individuals would retain an advantage over hearing individuals in detecting them. In this study, 23 deaf and 28 hearing college students were included. A modified perceptual load paradigm and event-related potentials (ERPs) were adopted. In the task, participants were instructed to search for a target letter in a central letter array, while task-irrelevant face distractors (happy, neutral, and angry faces) were simultaneously presented in the periphery while the central perceptual load was manipulated. Behavioral data showed that angry faces slowed deaf participants' responses to the target while facilitating the responses of hearing participants. At the electrophysiological level, we found modulation of P1 amplitude by central load only in hearing individuals. Interestingly, larger interference from angry face distractors was associated with higher P1 differential amplitude only in deaf individuals. Additionally, the amplitude of N170 for happy face distractors was smaller than that for angry and neutral face distractors in deaf participants. The present data demonstrates that, despite being under central perceptual load, deaf individuals exhibit less attentional inhibition to peripheral, goal-irrelevant angry faces than hearing individuals. The result may reflect a compensatory mechanism in which, in the absence of auditory alertness to danger, the detection of visually threatening information outside of the current attentional focus has a high priority.

Evaluation of Higher Order Target Models in Radar And IRST Data Fusion

In general, the motion of maneuvering targets is described by acceleration model, which is a kinematic model, including position derivatives up to the second order. It is found that for tracking highly maneuvering targets, it is necessary to include higher order position derivatives in the model. A model including derivatives of position up to the third order called the jerk model is presented. In this paper, the tracking performance of an extended Kalman filter with the jerk model is evaluated and compared with that of an extended Kalman filter with acceleration model for fusion and tracking of a maneuvering target sensed by IRST and radar.

Estimation of Target Motion Parameters from the Tonal Signals with a Single Hydrophone.

In the shallow-water waveguide environment, the tonal signals radiated by moving targets carry modal interference and Doppler shift information. The modal interference can be used to obtain the time of the closest point of approach (tCPA) and the ratio of the range at the closest point of approach to the velocity of the source (rCPA/v). However, parameters rCPA and v cannot be solved separately. When tCPA is known, the rCPA and the v of the target can be obtained theoretically by using the Doppler information. However, when the Doppler frequency shift is small or at a low signal-to-noise ratio, there will be a strong parametric coupling between rCPA and v. In order to solve the above parameter coupling problem, a target motion parameter estimation method from tonal signals with a single hydrophone is proposed in this paper. The method uses the Doppler and modal interference information carried by the tonal signals to obtain two different parametric coupling curves. Then, the parametric coupling curves can be used to estimate the two motion parameters. Simulation experiments verified the rationality of this method. The proposed method was applied to the SWellEx-96 and speedboat experiments, and the estimation errors of the motion parameters were within 10%, which shows the method is effective in its practical applications.

The role of color in transsaccadic object correspondence.

With each saccade, visual information is disrupted, and the visual system is tasked with establishing object correspondence between the presaccadic and postsaccadic representations of the saccade target. There is substantial evidence that the visual system consults spatiotemporal continuity when determining object correspondence across saccades. The evidence for surface feature continuity, however, is mixed. Surface features that are integral to the saccade target object's identity (e.g., shape and contrast polarity) are informative of object continuity, but features that may only imply the state of the object (e.g., orientation) are ignored. The present study tested whether color information is consulted to determine transsaccadic object continuity. We used two variations of the intrasaccadic target displacement task. In Experiments 1 and 2, participants reported the direction of the target displacement. In Experiments 3 and 4, they instead reported whether they detected any target movement. In all experiments, we manipulated the saccade target's continuity by removing it briefly (i.e., blanking) and by changing its color. We found that large color changes can disrupt stability and increase sensitivity to displacements for both direction and movement reports, although not as strongly as long blank durations (250 ms). Interestingly, even smaller color changes, but not blanking, reduced response biases. These results indicate that disrupting surface feature continuity may impact the process of transsaccadic object correspondence more strongly than spatiotemporal disruptions by both increasing the sensitivity and decreasing the response bias.

A Camera Calibration Method for Limited Motion of Target in Space

In modern industrial production, vision measurement systems are widely used for product quality inspection. Camera calibration is a crucial step in vision measurement systems that directly affects the accuracy of measurement results. However, in practical applications, the limited space for measurement and restricted movement of calibration targets present new challenges for camera calibration. In this paper, we propose a camera calibration method that is suitable for calibration targets with limited movement space. This method only requires one image of the calibration target to complete system calibration, greatly simplifying the on-site calibration work. Experimental results show that our method has a re-projection error of 0.0187 pixels, indicating high reliability and applicability. The application of this method in the inspection of seamless steel pipes demonstrates its potential for practical industrial production.

Detecting Correlated Target Motion in Moving and Static Dot Arrays

Detecting Correlated Target Motion in Moving and Static Dot Arrays

Comparison of different pseudo-linear estimators for vision-based target motion estimation

Comparison of different pseudo-linear estimators for vision-based target motion estimation

Characterization of deorbiting satellites and space debris with radar

During deorbiting, be it natural orbital decay or otherwise (e.g. self-disposal or active debris removal), precise knowledge of the condition of the target is of critical importance. The Tracking and Imaging Radar (TIRA) is an instrument that possesses the ability to accurately determine satellite and space debris orbits while also generating detailed radar images of them.We present recent results from the characterization of deorbiting satellites and space debris employing TIRA. Drawing examples from orbital decay events (Tiangong-1, Soyuz 2.1v R/B), deorbiting (Tiangong-2) and self-disposal operations (Carbonite-1, MicroSCOPE), we demonstrate the potential of TIRA. Furthermore, we focus on the emerging field of active debris removal (ADR), where reliable information of the on-orbit status and attitude motion of potential targets can “make or break” an ADR mission. In this context, the on-orbit status of a JAXA R/B (43682) and a VESPA adapter (39162) are investigated.We employ inverse synthetic aperture radar (ISAR) imaging and 3D modelling of ISAR images, obtained with TIRA, to characterize the status and attitude motion of satellites and space debris. When certain conditions render direct imaging unsuitable, the more powerful L-band tracking radar of TIRA is used to obtain and analyze the temporal evolution of their radar cross-section (RCS). In this work, we employ for the first time, a wavelet time–frequency analysis of such RCS signatures, specifically of NABEO-1 (43692) in LEO and an Ariane 5 rocket body (28904) in geostationary transfer orbit (GTO), to characterize their on-orbit status. The wavelet analysis delivers results in good agreement with more traditional tools, with added information on time localization of periodicities. We are thus able to confirm the tumbling motion of NABEO-1 and constrain the rotational velocity of Ariane 5 upper stage (28904).

Long‐time coherent integration for radar detection of manoeuvring targets based on accurate range evolution model

AbstractLong‐time coherent integration (LTCI) is one of the most effective approaches to enhance radar detection ability of weak targets. The existing LTCI methods generally assume that the target motion satisfies polynomial models in range coordinates. However, it may be hard to provide precise description of common target motions, especially manoeuvring motions, using a polynomial with finite terms. In this study, LTCI for radar detection of weak manoeuvring targets is investigated. The range evolution rules over time are derived and employed to formulate the target signal for two common manoeuvring motions, constant acceleration (CA) and constant turn (CT) motions in Cartesian coordinates. Aiming at realising accurate energy accumulation and improving detection performance of CA and CT targets, two LTCI algorithms based on the derived range evolution model are proposed. By extracting target signal and compensating for phase fluctuation between samples in accordance with the accurate range evolution model, the coherent accumulation of target signal can be effectively accomplished, eliminating the complex range and Doppler frequency migration effects simultaneously. The use of accurate range evolution model guarantees effective energy integration regardless of target manoeuvrability and integration time as long as the target performs CA or CT motion. Moreover, more information of target kinematic characteristics such as target acceleration and turn rate, additional to range and Doppler, can be observed. Simulations are conducted to validate the effectiveness of the proposed algorithms.The cover image is based on the Research Article Long‐time coherent integration for radar detection of manoeuvring targets based on accurate range evolution model by Zeyu Xu et al., https://doi.org/10.1049/rsn2.12445.

A Computationally Efficient Estimator for the Target Angle, Delay, and Doppler Parameters in Passive Radar

The azimuth, elevation, time delay (TD), and Doppler shift (DS) of the target echo signal are important parameters for target localization in passive radar. In this paper, for the problem of joint estimation of target azimuth, elevation, TD, and DS parameters in passive radar, a computationally efficient estimator is proposed based on segmented coherent integration and uniform circular array (UCA) interferometer direction finding. First, according to the parameters of the target motion and illuminators of opportunity, the reference and surveillance signals are divided into segments, with fast time within a segment and slow time across the segments; then, matching filtering along the fast time and fast Fourier transform (FFT) along the slow time are performed to accumulate the target echo energy to the same delay-Doppler cell; finally, the UCA interferometer two-dimensional direction finding is performed at the delay-Doppler cell where the target echo is located, to achieve the target azimuth and elevation estimate. Simulation results demonstrate that the proposed algorithm has low computational complexity, high real-time processing capability, and can achieve efficient and real-time estimation of the azimuth, elevation, TD, and DS parameters of weak target echoes in passive radar.

Accuracy of on-site teleoperated milling with haptic assistance

PurposeIn bone surgery specialties, like orthopedics, neurosurgery, and oral and maxillofacial surgery patient safety and treatment success depends on the accurate implementation of computer-based surgical plans. Unintentional plan deviations can result in long-term functional damage to the patient. With on-site teleoperation, the surgeon operates a slave robot with a physically-decoupled master device, while being directly present at the operation site. This allows the surgeon to perform surgical tasks with robotic accuracy, while always remaining in the control loop.MethodsIn this study the master- and slave-side accuracy of an on-site teleoperated miniature cooperative robot (minaroHD) is evaluated. Master-side accuracy is investigated in a user study regarding scale factor, target feed rate, movement direction and haptic guidance stiffness. Scale factors are chosen to correspond to primarily finger, hand, and arm movements. Slave-side accuracy is investigated in autonomous milling trials regarding stepover, feed rate, movement direction, and material density.ResultsMaster-side user input errors increase with increasing target feed rate and scale factor, and decrease with increasing haptic guidance stiffness. Resulting slave-side errors decrease with increasing scale factor and are < 0.07 mm for optimal guidance parameters. Slave-side robot position errors correlate with the feed rate but show little correlation with stepover distance. For optimal milling parameters, the 95th percentile of tracked slave-side position error is 0.086 mm with a maximal error of 0.16 mm.ConclusionFor optimal guidance and milling parameters, the combined error of 0.23 mm is in the range of the dura mater thickness (< 0.27 mm) or mandibular canal wall (~ 0.85 mm). This corresponds to safety margins in high-demand surgical procedures like craniotomies, laminectomies, or decortication of the jaw. However, for further clinical translation, the performance and usability of on-site teleoperated milling must be further evaluated for real-life clinical application examples with consideration of all error sources in a computer-assisted surgery workflow.

MMTD: Multistage Moving Target Defense for Security-Enhanced D-FACTS Operation

In recent studies, moving target defense (MTD) has been applied to detect false data injection (FDI) attacks using distributed flexible AC transmission system (D-FACTS) devices. However, the inherent conflict between the security goals of MTD (i.e., detecting FDI attacks) and the economic goals of D-FACTS devices (i.e., reducing power losses) would impede the application of MTD in real systems. Moreover, the detection capabilities of existing MTDs are often insufficient. This paper proposes a multi-stage MTD (MMTD) approach to resolve these two issues by adding a group of designed security-oriented schemes before D-FACTS’ economy-oriented scheme to detect FDI attacks. We keep these security-oriented schemes for a very short time interval and then revert to the economy-oriented scheme for the remaining time to ensure the economic requirements. We prove that a designed MMTD can significantly improve the detection capability compared to existing one-stage MTDs. We find the supremum of MMTD’s detection capability and study its relationship with system topology and D-FACTS deployment. Meanwhile, a greedy algorithm is proposed to search the MMTD strategy to reach this supremum. Simulation results show that the proposed MMTD can achieve the supremum against FDI attacks while outperforming current MTD strategies on economic indicators.

Hybrid UWB-Inertial TDoA-Based Target Tracking With Concentrated Anchors

In this paper, hybrid radio/inertial mobile target tracking for accurate and smooth path estimation is considered. The proposed tracking approach builds upon an Ultra WideBand (UWB)-based positioning algorithm, based on the Linear Hyperbolic Positioning System (LinHPS), with Time Difference of Arrival (TDoA) processing and anchors concentrated on a single hotspot at the center of the environment where the target moves. First, we design an Adaptive Radio-based Extended Kalman Filter (AREKF), which does not require a priori statistical knowledge of the noise in the target movement model and estimates the measurement noise covariance, at each sampling time, according to a proper LookUp Table (LUT). In order to improve the performance of AREKF, we incorporate inertial data collected from the target and propose three “hybrid” radio/inertial algorithms, denoted as Hybrid Inertial Measurement Unit (IMU)-aided Radio-based EKF (HIREKF), Hybrid Noisy Control EKF (HNCEKF), and Hybrid Control EKF (HCEKF). Our results on experimentally acquired paths show that the proposed algorithms achieve an average instantaneous position estimation error on the order of a few centimeters. Moreover, the minimum target path length estimation error, obtained with HCEKF, is on the order of 6% and 1% for two paths with lengths equal to approximately 17 m and 46 m, respectively.