Target Acquisition Research Articles

A multi-view SAR target recognition method using feature fusion and joint classification

ABSTRACT To handle synthetic aperture radar (SAR) image target recognition problem, a multi-view method is proposed. For the multi-view SAR images be recognized, they are first clustered based on the correlation coefficients and divided into several view sets. Afterwards, for the view set containing two or more images, the multiset canonical correlation analysis (MCCA) is employed to fuse them as a single feature vector. For the view set with a single image, its corresponding feature vector is directly used. Finally, the joint sparse representation is used to characterize and classify the feature vectors from different view sets and determine the target label of the multi-view SAR images. Experiments and analysis on the moving and stationary target acquisition and recognition (MSTAR) dataset show that the proposed method can achieve an average recognition rate of 99.42% for 10 types of targets under the standard operating condition (SOC). Its performance is also better than several reference methods under the extended operating conditions (EOC) including noise interference and target occlusion.

Learning Spatio-Temporal Attention Based Siamese Network for Tracking UAVs in the Wild

The popularity of unmanned aerial vehicles (UAVs) has made anti-UAV technology increasingly urgent. Object tracking, especially in thermal infrared videos, offers a promising solution to counter UAV intrusion. However, troublesome issues such as fast motion and tiny size make tracking infrared drone targets difficult and challenging. This work proposes a simple and effective spatio-temporal attention based Siamese method called SiamSTA, which performs reliable local searching and wide-range re-detection alternatively for robustly tracking drones in the wild. Concretely, SiamSTA builds a two-stage re-detection network to predict the target state using the template of first frame and the prediction results of previous frames. To tackle the challenge of small-scale UAV targets for long-range acquisition, SiamSTA imposes spatial and temporal constraints on generating candidate proposals within local neighborhoods to eliminate interference from background distractors. Complementarily, in case of target lost from local regions due to fast movement, a third stage re-detection module is introduced, which exploits valuable motion cues through a correlation filter based on change detection to re-capture targets from a global view. Finally, a state-aware switching mechanism is adopted to adaptively integrate local searching and global re-detection and take their complementary strengths for robust tracking. Extensive experiments on three anti-UAV datasets nicely demonstrate SiamSTA’s advantage over other competitors. Notably, SiamSTA is the foundation of the 1st-place winning entry in the 2nd Anti-UAV Challenge.

Does Target Firm’s Earnings Management Affect Shareholder’s Gains? Evidence from China

This study tests the hypothesis that the target firms are involved in earnings management activities in quarters leading to a takeover announcement. Using a sample of 3,455 Chinese listed firms that are targets of successful acquisitions over the period 2007–2020, and for a matched sample of non-targets, we find that target firms manipulate earnings in quarters leading to the announcement date. Further, we find evidence of a negative relationship between earnings management and short-term gains to shareholders. Our result remains robust after controlling for various deal characteristics. The study also suggests that pre-merger earnings management in target firms is not fully anticipated by the market before the takeover announcement. We find no evidence of earnings management immediately after the announcement quarter.

Sparse Weighting for Pyramid Pooling-Based SAR Image Target Recognition

In this study, a novel feature learning method for synthetic aperture radar (SAR) image automatic target recognition is presented. It is based on spatial pyramid matching (SPM), which represents an image by concatenating the pooling feature vectors that are obtained from different resolution sub-regions. This method exploits the dependability of obtaining the weighted pooling features generated from SPM sub-regions. The dependability is determined by the residuals obtained from sparse representation. This method aims at enhancing the weights of the pooling features generated in the sub-regions located in the target and suppressing the weights of the background. The feature representation for SAR image target recognition is discriminative and robust to speckle noise and background clutter. Experiments performed on the Moving and Stationary Target Acquisition and Recognition public dataset prove the advantageous performance of the presented algorithm over several state-of-the-art methods.

Understanding user performance of acquiring targets with motion-in-depth in virtual reality

Virtual reality (VR) user interfaces contain numerous dynamic interactive tasks, among which acquiring moving targets is a common basic one. Previous studies have investigated user performance in moving target acquisition in desktop and touchscreen settings. However, these findings are not directly transferable to VR where targets and user input have complete freedom in three dimensions. This paper concentrates on motion-in-depth, that is, where a target predominantly exhibits approaching or receding movement as opposed to lateral motion across the user’s field of view. We report on two studies investigating how various factors including texture, shadow, alignment, moving speed and moving direction affect: 1) perception accuracy of 3D targets with motion-in-depth, and 2) user performance, which we define as the combination of movement time (MT) and error rate (ER), in a target acquisition task involving motion-in-depth. Our data reveal a number of empirical results that are distinct from the depth perception of static targets and the user performance of 1D/2D target acquisition. We found that MT and ER when acquiring targets with motion-in-depth have strong regularities as the data showed good fits with Jagacinski’s model for movement time estimation and a Ternary-Gaussian model for error rate prediction. We conclude with implications derived from this study for future designs.

Classification of military equipment targets on radar images generated in noise interference conditions using a convolutional neural network

The paper proposes the solution to the problem of determining the relationship between the accuracy of classification of radar images of targets belonging to ten classes (from the public portion of Moving and Stationary Target Acquisition and Recognition standard data set) and the signal-to-noise ratio (from –20 to 20 dB). Unlike the traditional approach to solving the above problem based on statistic analysis methods, the classification accuracy was estimated using an eight-layer deep convolutional neural network. It is found out that target recognition failure (a decrease in the classification accuracy down to 30 % and lower) regarding sub-meter radar imagery of motor and armoured vehicles requires interference with a background level higher than the average background level of target echoes by at least 10 dB. The study also proves that using pre-trained networks with the MobileNetV1 and Xception architectures fails to improve the classification accuracy.

The Effects of Whole-Body Vibration and Head Supported Mass on Performance and Muscular Demand

For military rotary-wing aircrew, little is known about the interactive effects of vibration exposure and the addition of head supported mass (HSM) on target acquisition performance, head kinematics, and muscular demand. Sixteen healthy male participants wore an aviator helmet with replica night vision goggles and completed rapid aiming head movements to acquire visual targets in axial and off-axis movement trajectories while secured in a Bell-412 helicopter seat mounted to a human-rated shaker platform. HSM configuration (with or without a counterweight (CW)) and vertical whole-body vibration (WBV) conditions (vibration or no vibration exposure) were manipulated as independent variables. WBV exposure degraded target acquisition performance and lengthened time to peak velocity of head movements. For yaw peak velocity in the axial movement trajectory, peak velocity was 9.9%, 11.6%, and 8.4% higher in the noCW + WBV condition compared to the CW + WBV, CW + noWBV, and noCW + noWBV conditions, respectively.

A direct method-based suboptimal attitude guidance for accurate ground-target tracking maneuvers

This work presents an attitude control strategy for Earth-imaging satellites. The proposed methodology is based on the closed-loop implementation of a direct method and a nonlinear programming solver for the quick determination of near-optimal attitude trajectories. The two optimization criteria considered are the target acquisition time and the maneuver energy associated to the actuation torques. For comparison purposes, we take under analysis alternative attitude controllers, such as a quaternion feedback Proportional-Derivative controller, a Linear Quadratic Regulator, a Model Predictive Control, and an adaptive Continuous Twisting Sliding Mode Controller. Optimality and accuracy of these controllers are assessed through simulations in a high-fidelity environment inclusive of orbital perturbations and refined model of the actuation device. Analysis of the results emphasizes the advantages of the proposed methodology over the alternative controllers.

Firm Heterogeneities, Multi-Dimensional Proximities, and Systematic Dynamics of M&A Partnering: Evidences from Transitional China

Corporate investment strategies and decision-making processes are crucial for understanding the operation and evolution of socioeconomic systems. Mergers and acquisitions (M&As) have been the main mode of corporate investment, growth, and upgrading, deeply affecting corporate reorganization, regional industrial restructuring, and economic globalization. By building a database including 5543 M&A partnerings and 1.89 million M&A non-partnerings, this study aims to uncover the systematic dynamics of M&A partnering in regional China during different phases since the mid-1990s, with particular attention given to the effects of firm heterogeneities and multi-dimensional proximities. Although geographical, cognitive, organizational, and institutional proximity dimensions are significantly influential for M&A partnering, we find that the effects of multi-dimensional proximities differ across M&A types and involving firms. Specifically, organizational proximity matters more for large- and medium-sized acquirers, while institutional proximity plays a more vital role in the acquisition target selection of private-owned and small-sized acquirers. Cognitive proximity measured by industrial and technical relatedness is more crucial for horizontal, vertical, and conglomerate M&As that are tightly associated with the corporate product, technical, and functional upgrading. The results indicate that the benefits of cognitive proximity may offset the risks and costs resulting from long-distance M&As, demonstrating the interactive dynamics between proximity dimensions. Our findings suggest that firm heterogeneities, proximity dynamics, and contextual factors should be focused on when explaining the investment decision-making processes of individual corporations in emerging and transitional economies such as China.

Arm Posture Changes and Influences on Hand Controller Interaction Evaluation in Virtual Reality

In virtual reality (VR) applications, hand-controller interaction is largely limited by the biomechanical structure of the arm and its kinematical features. Earlier research revealed that different arm postures generate distinct arm fatigue levels in mid-air operational tasks; however, how they impact interaction performance, e.g., accuracy of target grasp and manipulation, has been less investigated. To fill this gap in knowledge, we conducted an empirical experiment in which thirty participants were recruited to complete a series of target acquisition tasks in a specifically designed VR application. Results show that (1) a bent arm posture resulted in a higher interaction accuracy than a stretched arm posture; (2) a downward arm posture interacted more accurately than an upraised arm posture; since two arms are bilaterally symmetric, (3) either selected arm interacted more accurately on the corresponding side than on the opposite side; and (4) the user-preferred or dominant arm interacted more persistently than the non-dominant one, though two arms generated little difference in interaction accuracy. Implications and suggestions are discussed for designing more efficient and user-satisfying interactive spaces in VR.

How does a partner's acquisition affect the value of the firm's alliance with that partner?

AbstractResearch SummaryHow does an acquisition initiated by a firm's alliance partner affect the value that the firm can create and capture from its alliance with that partner? We conjecture that the similarity between the businesses of the firm and its partner's acquisition target restricts the firm's ability to create and capture value from its alliance, whereas the complementarity between their businesses enhances the firm's gain from its alliance. We further expect relational embeddedness between the firm and its partner to mitigate the competitive tension associated with similarity while reinforcing synergies ascribed to complementarity. Our analysis of 361 firms and their 590 alliances with 91 partners that acquired 164 targets during 2000–2016 supports our predictions about business similarity and complementarity but refutes those concerning relational embeddedness.Managerial SummaryWhen a firm's partner engages in an acquisition, this can impact the value of their alliance. We show that when the acquired target competes with the firm, the value of the alliance declines. In turn, when the target and firm's businesses are complementary, the alliance creates more value. We also find that when the firm and the partner had extensive experience working together, this reinforces the negative effect of business similarity with the target, probably because of perceived betrayal and knowledge leakage. Joint experience also reduces the value of complementarity, likely due to the difficulty of modifying collaborative practices. We encourage managers to scrutinize their partners' corporate initiatives, reduce commitment when the partner acquires a competing target, and leverage new complementarities following the partner's acquisitions.

Banking relationship, information reusability, and acquisition loans

We study whether and how banks reuse information across different but related borrowers in financing mergers and acquisitions. We find that stronger prior lending relationships between acquisition loan lenders and acquisition targets are associated with lower spreads and fewer covenant restrictions on acquisition loans. We show that the results are unlikely to be driven by unobservable acquirer, target, or lender characteristics. Consistent with the information asymmetry hypothesis, the effect is stronger when information asymmetry about the target firm is higher. We also find that the result is not driven by the coinsurance effect.

Knowledge resources and the acquisition of spinouts

In high-technology industries, employee spinouts have increasingly been identified as attractive targets for acquisitions. Yet employee spinouts may originate from different knowledge contexts. This study adopts a resource base perspective to examine the impact of both the knowledge heritage and the product strategy of spinouts originating from different contexts (i.e. from the same industry or from a related downstream industry) on the potential to be acquired by firms in the same industry or in related industries. Our findings, based on data from the semiconductor industry and its related downstream industries, show that spinouts from firms in a focal industry represent appealing targets for a broad range of buyer firms from within the focal industry or from related, downstream industries, independent of their product strategy at entry. By contrast, spinouts from downstream, user industries that enter into an upstream industry, tend to appeal to a more limited set of buyers. Our study suggests that managers and academics should consider the acquisition of spinouts whose founders have origins in related industries as a channel to access critical knowledge from upstream or downstream contexts. Yet because many of the critical knowledge resources that spinouts possess are embodied in their founders, such acquisitions also require careful management of personnel decisions post-acquisition.

Freehand Target Acquisition With a Force-Assisted Device

Freehand Target Acquisition With a Force-Assisted Device

STUDY OF POTENTIAL LOCATIONS OF GREEN OPEN SPACE BASED ON PROCUREMENT CONVENIENCE IN WEST JAKARTA

The Procurement of Public Green Open Space (RTH) in DKI Jakarta Province is carried out by the DKI Jakarta Forestry Service based on the land status of the BPN. The procurement of green open space is passive based on requests from the community. The DKI Jakarta Forestry Service data shows West Jakarta's public green open space has only fulfilled 8.8%. This study aims to assist stakeholders in the procurement of green open space in terms of ease of procurement. The ease aspect is compiled from land-use parameters, BPN land status, spatial pattern zoning, SIPPT, RTH Assets, and raw rice fields. The analysis results show that many areas included in the green zoning in West Jakarta have turned the function of land into built-up land, making it difficult for the local government to acquire land. This research found alternative lands with existing non-built land use conditions and clear land status and potential spatial pattern zoning targeted as green open space land acquisition targets. The analysis results show that from 4071 plots of land, there are 784 plots of land that are very potential with 179 ha. For potential land, there are 3234 plots of land with an area of 301 Ha and 53 plots of land classified as standard with an area of 2.4 Ha. Land with great potential can be used as a procurement priority for the relevant local government in the procurement of green open space in terms of the ease of procurement aspect.Keywords: Green Open Space, GIS, Green Open Space Potential

Domestic and foreign acquisitions, plant survival and employment effects

ABSTRACT We estimate causal treatment effects of domestic and foreign acquisitions on plant survival, employment (growth) and the skill composition within acquired plants. To do so, we look at takeovers of private firms in Danish manufacturing and service sectors during the period 2002–2015. We use plant-, firm-, and industry-level information to control for the non-random selection of the acquisition targets, differentiated for domestic and foreign acquirers, by combining a difference-in-differences approach with a propensity score weighting estimator. Our results reveal positive effects on plant survival, employment (growth) and the skill intensity for domestic targets, while foreign targets reduce their skill intensity following an acquisition.

Customer concentration of targets in mergers and acquisitions

AbstractWe study how the customer concentration of targets impacts the occurrence and structure of mergers and acquisitions (M&A). We hypothesize and find that acquirers respond to customer concentration‐related risk by placing fewer bids for targets with greater customer concentration and by using more stock payment in their offers. These relations vary predictably with major customer‐related uncertainty. Our findings extend the literature by documenting an important risk factor in M&A and by quantifying the economic consequences of customer concentration.

Target Tracking and 3D Trajectory Reconstruction Based on Multicamera Calibration

In traffic scenarios, vehicle trajectories can provide almost all the dynamic information of moving vehicles. Analyzing the vehicle trajectory in the monitoring scene can grasp the dynamic road traffic information. Cross-camera association of vehicle trajectories in multiple cameras can break the isolation of target information between single cameras and obtain the overall road operation conditions in a large-scale video surveillance area, which helps road traffic managers to conduct traffic analysis, prediction, and control. Based on the framework of DBT automatic target detection, this paper proposes a cross-camera vehicle trajectory correlation matching method based on the Euclidean distance metric correlation of trajectory points. For the multitarget vehicle trajectory acquired in a single camera, we first perform 3D trajectory reconstruction based on the combined camera calibration in the overlapping area and then complete the similarity association between the cross-camera trajectories and the cross-camera trajectory update, and complete the trajectory transfer of the vehicle between adjacent cameras. Experiments show that the method in this paper can well solve the problem that the current tracking technology is difficult to match the vehicle trajectory under different cameras in complex traffic scenes and essentially achieves long-term and long-distance continuous tracking and trajectory acquisition of multiple targets across cameras.

Model-driven automatic target recognition of sar images with part-level reasoning

A synthetic aperture radar (SAR) automatic target recognition (ATR) method is proposed based on 3-D scattering center model with part-level reasoning. The scattering centers in the 3-D scattering center model built offline are matched to the test image by a region-to-region matching algorithm at first. Then, a preliminary similarity is defined, in which all the model scattering centers are equally treated. Based on the spatial and physical attributes of the model scattering centers, a spatially constrained similarity and a physically constrained similarity are designed. The three similarities work separately for target recognition and the decision with the highest reliability is adopted. The final decision not only determines the target type but also reflects the possible operating conditions (OCs) of the target such as partial occlusion or articulation, etc. Extensive experiments on the simulated SAR images by electromagnetic (EM) code and measured Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset demonstrate the superior effectiveness and robustness of the proposed method under both standard operating condition (SOC) and several typical extended operating conditions (EOC) compared with several existing template-based and model-based methods.

TECHNOLOGY OF PROPULSION SYSTEM FOR UNMANNED COMBAT AERIAL VEHICLE (UCAV) – A REVIEW

Unmanned Combat Aerial Vehicle (UCAV) is an unmanned aerial vehicle (UAV) that is used for intelligence, surveillance, target acquisition, and reconnaissance and carries aircraft ordnance such as missiles, ATGMs, and/or bombs in hardpoints for drone strikes. These drones are usually under realtime human control, with varying levels of autonomy. Unlike unmanned surveillance and reconnaissance aerial vehicles, UCAVs are used for both drone strikes and battlefield intelligence. Unmanned Combat Aerial Vehicle (UCAV) propulsion technology is significantly related to the flight performance of UCAVs, which has become one of the most important development directions of aviation. It should be noted that UCAVs have three types of propulsion systems, namely the fuel, hybrid fuel-electric, and pure electric, respectively. This paper presents and discusses the classification, working principles, characteristics, and critical technologies of these three types of propulsion systems. It is helpful to establish the development framework of the UCAV propulsion system and provide the essential information on electric propulsion UCAVs. Additionally, future technologies and development, including the high-power density motors, converters, power supplies, are discussed for the electric propulsion UCAVs. In the near future, the electric propulsion system would be widely used in UCAVs. The high-power density system would become the development trend of electric UCAVs. Thus, this review article provides comprehensive views and multiple comparisons of propulsion systems for UCAVs.