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Active jammers in the form of digital radio frequency memory (DRFM) could produce false targets with a coherence of range and velocity, making it increasingly efficient in interrupting radar systems based on data correlation analysis. By integrating the temporal variability characteristic and mitigating the impact of measurement errors inherent in the radar system, we propose a novel false target recognition methodology for a two‐station netted radar utilizing extended Kalman filter (EKF) and the Neyman–Pearson criterion. From the aspects of filtering characteristics and active jammer parameters, the simulation shows that the technique could obtain observable different convergence curves for false targets and is sensitive to velocity or range deception under specific parameters. Moreover, the method exhibits a favorable tolerance for measurement error and an exceptional capability to identify false targets from various directions, considering both radar performance parameters and spatial scale. This outcome highlights the significance of setting specific parameters following countermeasure scenarios and requirements, showcasing its practical value in engineering practice. [ABSTRACT FROM AUTHOR]

Images taken by fisheye cameras are characterized by wide field of view, geometric distortion and large scale variance, which bring great challenges to object detectors based on general convolutional networks. Existing object detection algorithms can be further improved with respect to network structure design, feature learning to be applicable to the distorted object detection task on fisheye images. To mitigate the effect of radial distortion on fisheye images, a multi-head attention module with multi-branch stacking structure is used in the YOLOv7 backbone to capture global contextual information. Meanwhile, a simple and efficient layer aggregation structure combining deformable convolutions is used on the Neck side of YOLOv7 to achieve effective multi-scale feature fusion. Experiments are conducted on the public comprehensive fisheye image dataset VOC_360, and the results show that the improved YOLOv7 fisheye image object detector effectively achieves detection accuracy of 84.3% and 70.4% for mAP50 and mAP50:95, respectively, which is 3.1 percentage points and 6.4 percentage points higher than the baseline model YOLOv7, respectively. [ABSTRACT FROM AUTHOR]

To address the problem and reduce the risk wherein a ship‐based cross‐eye jammer could set a protected ship as a target, an unmanned platform equipped with a jammer is proposed to be used. However, the jamming situation violates the original cross‐eye jamming conditions and introduces some new elements. In this regard, the impact of outboard cross‐eye jamming in the presence of ship echoes is derived in detail. The analysis shows that the outboard cross‐eye jamming combines the characteristics of outboard active and traditional cross‐eye jamming gains. It can reduce the standard cross‐eye jamming requirement of the jamming‐to‐signal ratio (JSR) and improve the jamming effect. The phase difference of a cross‐eye jammer can be controlled at 0° or 180° to obtain a larger angular positioning deviation based on the JSR requirement, thus providing a theoretical basis for applications of unmanned outboard cross‐eye jamming. [ABSTRACT FROM AUTHOR]

Jamming resources allocation (JRA) is an essential task in clustered combat environments. Especially in cases with multiple threats, efficient JRA is imperative for protecting key assets. In this study, multiple distributed outboard jammers protecting multiple targets against a multi‐missile threat are considered, where the function of JRA includes jamming object selection and jammer power allocation. To address this problem, first, a scheme to evaluate the jamming effectiveness of the radar seeker under cooperative jamming from multiple jammers is proposed. Considering power allocation, a mixed‐integer programing model for the optimisation of JRA is further established. A two‐track simultaneous update binary particle swarm algorithm (TS‐BPSO) is then devised to obtain the solutions of the JRA. Finally, the effectiveness of the proposed method for multiple jammers in the multiple missiles scenario is evaluated through simulations. The simulation results suggest that the distributed cooperative jamming resource allocation is affected by the incoming orientation of the missile and the relative position of the jammers and the targets. The findings of the study enable evaluating the use of jammer formations and provide insights into developing effective jamming strategies. [ABSTRACT FROM AUTHOR]