Search Results (6)

As a typical and widely used passive jamming method, chaff clouds have a strong interference effect on radar that remains a significant challenge effectively to counteract. It is exceedingly necessary to improve the anti-chaff jamming ability of radars. In this paper, we address this challenge by proposing an effective residual attention network named RA-Net. Specifically, we introduce an attention mechanism that enables the network to focus on the most informative and stable hierarchical features of the high-resolution range profile (HRRP) data, significantly improving the model’s feature extraction capability and overall performance. In addition, we address the limitation of insufficient measured chaff cloud echo data by establishing a remarkably rich and diverse data set of chaff cloud HRRP data through extensive field experiments. This dataset serves as a valuable resource and a critical foundation for advancing HRRP recognition research in this domain. Experimental results on measured HRRP data demonstrate that RA-Net achieves superior recognition accuracy of 97.10%, outperforming traditional methods, and also exhibits outstanding generalization capability. These results establish RA-Net as a new benchmark for chaff cloud HRRP recognition. Full article

In response to potential denial environments such as canyons, gullies, islands, and cities where users are located, traditional Telemetry, Tracking, and Command (TT&C) systems can still maintain core requirements such as availability, reliability, and sustainability in the face of complex electromagnetic environments and non-line-of-sight environments that may cause service degradation or even failure. This paper presents a single-station emergency solution that integrates communication and TT&C (IC&T) functions based on radar chaff cloud technology. Firstly, a suitable selection of frequency bands and modulation methods is provided for the emergency IC&T system to ensure compatibility with existing communication and TT&C systems while catering to the future needs of IC&T. Subsequently, theoretical analyses are conducted on the communication link transmission loss, data transmission, code tracking accuracy, and anti-multipath model of the emergency IC&T system based on the chosen frequency band and modulation mode. This paper proposes a dual-way asynchronous precision ranging and time synchronization (DWAPR&TS) system employing dual one-way ranging (DOWR) measurement, a dual-way asynchronous incoherent Doppler velocity measurement (DWAIDVM) system, and a single baseline angle measurement system. Next, we analyze the physical characteristics of the radar chaff and establish a dynamic model of spherical chaff cloud clusters based on free diffusion. Additionally, we provide the optimal strategy for deploying chaff cloud. Finally, the emergency IC&T application based on the radar chaff cloud relay is simulated, and the results show that for severe interference, taking drones as an example, under a measurement baseline of 100 km, the emergency IC&T solution proposed in this paper can achieve an accuracy range of approximately 100 m, a velocity accuracy of 0.1 m/s, and an angle accuracy of 0.1°. In comparison with existing TT&C system solutions, the proposed system possesses unique and potential advantages that the others do not have. It can serve as an emergency IC&T reference solution in denial environments, offering significant value for both civilian and military applications. Full article

Chaff is a passive jammer widely used to disrupt radar or radio-frequency sensors. A mass of chaff fibers dispersed in the air is commonly referred to as a chaff cloud. It is nearly impossible to numerically simulate in real-time the enormous amount of chaff fibers composing the chaff cloud. In this paper, we model the behavior of numerically estimated chaff clouds as probability density functions (PDFs) and apply approximation techniques to estimate the radar cross-section (RCS) of the chaff cloud in real time. To model the aerodynamics of the chaff cloud, we represented the combination of PDFs as functions of time and wind speed. The applied approximation techniques—vector radiative transfer and generalized equivalent conductor method—showed a computation time that cannot be achieved by low-frequency methods such as the method of moments or finite-difference time-domain. Moreover, the dynamic RCS results of the approximation techniques showed a similar trend to those of other studies simulating similar situations. The proposed scheme is effective for real-time chaff cloud simulation, and the modeled dynamics and estimated dynamic RCSs can be a standard baseline for developing new analysis methods for chaff clouds. In the future, the proposed scheme will extend to more chaff fibers and more diverse environmental parameters. Full article

Attackers can exploit compromised hosts to launch attacks over the Internet. This protects an intruder, placing them behind a long connection chain consisting of multiple compromised hosts. Such attacks are called stepping-stone intrusions. Many algorithms have been proposed to detect stepping-stone intrusions, but most detection algorithms are weak in resisting intruders’ session manipulation, such as chaff-perturbation. This paper proposes a novel detection algorithm: Packet Cross-Matching and RTT-based two-dimensional random walk. Theoretical proof shows network traffic cross matching can be effective in resisting attackers’ chaff attack. Our experimental results over the AWS cloud show that the proposed algorithm can resist attackers’ chaff attacks up to a chaff rate of 100%. Full article

Chaff jamming is a widely used passive interference method. A chaff cloud diffusion model for the widespread chaff cloud was presented. The high-density chaff cloud aerodynamic model can rapidly predict the chaff elements’ time-varying spatial orientation, location, and overall spatial distribution. Basing on these pieces of information, the radar cross section (RCS) for the single chaff fibre can be obtained based on the method of moments (MoM). For high-density chaff clouds, the attenuation and shielding effects on the signal must be considered. This paper proposed a voxel splitting method in rotated coordinates, dividing the chaff cloud into rectangular cells with one side perpendicular to the direction of radar entry. The varied polarized RCS features of the chaff cloud were simulated and analysed on this foundation. By dividing the chaff cloud into dynamic voxels and considering the uneven density distribution of the chaff cloud and the signal attenuation in each segment caused by the continuous fluctuating shape, fine-grained simulations of the chaff cloud radar echoes can be performed. Full article

Ship recognition from chaff cloud jamming is challenging since they have similar dimensions and radar cross sections. In this paper, a polarimetric recognition technique with sophisticated polarimetric decomposition is proposed. To this end, a seven-component model-based decomposition is first put forward by integrating three sophisticated scattering models, thus the dominant and local scattering of ships can be characterized accurately. According to the derived scattering contributions, a robust discrimination feature is then designed based on the concept of contrast and suppression. Coupled with the average scattering angle estimated from eigen-based decomposition, the constructed feature vector is inputted into the support vector machine and the recognition is finally fulfilled. The proposed method is tested on simulated and real polarimetric radar data and the results demonstrate that the proposed method achieves the highest recognition rate of over 98%, which outperforms the state-of-the-art methods. Full article