https://www.joeds.ir/ New Researches in Electronic Defense Systems en daily 1 Fri, 20 Feb 2026 00:00:00 +0330 Fri, 20 Feb 2026 00:00:00 +0330 https://www.joeds.ir/article_240572.html In this paper, a suitable neural network is designed to increase the detection and classification of signals emitted from military targets. The proposed algorithm presents a novel method for target signal detection based on artificial intelligence. After generating two datasets of radar signals, the necessary preprocessing is performed on these data using the time-frequency transformation method and spectrograph images related to these data are generated. Then, by applying the dataset images to the model, the training, validation, and testing processes are performed. The results obtained show that the designed model is able to automatically and optimally extract radar signal features at different levels, and by selecting the best and most effective features, it increases the accuracy and reduces the error in signal detection and classification. The target detection accuracy is more than 97 percent, the detection error in the training data is 2 percent and in the validation data is 1 percent. By optimizing the detection accuracy, the target detection speed has increased acceptably. https://www.joeds.ir/article_219527.html In this paper, a FF, three-order, 3-bit continuous time quadrature delta-sigma modulator by applying error-feedback method is designed for a wideband radar receiver. In this method, the quantization noise of the modulator is extracted then injected to the output of the loop filter by a transfer function consist of delays in the z domain. The proposed method adds a zero to the modulator’s NTF that increases the modulator’s order without adding active blocks. The first, the primary NTF zeros are located at the pass band, and then applying the error-feedback method adds a zero in DC, which increases the bandwidth and SNR of the modulator. Bandwidth, center frequency and SNR of conventional modulator are 0.03Fs, 0.029Fs and 76.48dB, respectively then for proposed structure are 0.044Fs and 0.0215Fs and 86.52dB, respectively. Comparison of the results shows that the bandwidth and SNR of the proposed structure increased by more than 30 and 10 percent, respectively, compared with the conventional structure. https://www.joeds.ir/article_219579.html Abstract: Free Space Optics (FSO) offers easy deployment and high data rates, making it ideal for terrestrial and space communications. However, FSO systems, despite their numerous advantages, are highly vulnerable to environmental factors such as atmospheric attenuation, turbulence, and adverse weather conditions. According to existing literature, the maximum range of an FSO link in terrestrial settings is typically under 5 km with a bit rate of maximum10 Gbps in hazy environments. In this paper, we propose a performance analysis of an FSO system that integrates Coherent Detection with an Intelligent Adaptive Code Modulation (ACM) technique, offering enhanced resilience, increased link length, and improved availability under varying environmental conditions. Performance analysis and simulation results demonstrate the system’s ability to maintain data transmission rates of 40 Gbps over distances up to 1 km and 10 Gbps over distances up to 6 km under adverse conditions such as fog, rain, and snow, while preserving high Q-factors, low BER, and extended link availability. The system dynamically switches between 16QAM, 4QAM, and PAM modulation schemes, depending on real-time assessments of Signal-to-Noise Ratio (SNR) and weather conditions. https://www.joeds.ir/article_234831.html It is of great importance to study the parameters affecting the lifespan and specific capacity of lithium-ion batteries. One of the key factors influencing the efficiency of these batteries is the uniform and dendrite-free deposition of lithium within the electrode structure. This study reveals, for the first time, a strong correlation between the ionic conductivity of the electrolyte and the cycling stability of metal scaffolds in the electroplated state. The high tortuosity of the structure leads to the preferential deposition of lithium on the upper surfaces of the metal scaffolds. This lithium accumulated on the upper surfaces blocks the ion transport inward and effectively reduces the internal capacity of the electrode. Additionally, it causes inhomogeneous current distribution and non-uniform lithium plating and stripping within the structure. Increasing the electrolyte conductivity and reducing the structural tortuosity of the electrode can significantly improve the uniformity of lithium plating and stripping in the metal scaffolds. It will increase the lifespan of the electrodes and the battery. https://www.joeds.ir/article_234832.html This paper presents a comprehensive performance analysis and comparison of nine standard Forward Error Correction (FEC) schemes over a long-haul, single-mode optical fiber channel, where nonlinear effects are considered the primary performance-limiting factor. Utilizing a unified and powerful simulation framework developed in Python, the performance of each code is evaluated under the distinct impact of key nonlinear phenomena—namely Self-Phase Modulation (SPM), Cross-Phase Modulation (XPM), and Four-Wave Mixing (FWM)—in addition to Amplified Spontaneous Emission (ASE) noise. The results are presented as Bit Error Rate (BER) versus Bit Energy-to-Noise Ratio (E_b/N_0) curves, and the "performance penalty" incurred by each nonlinear effect is quantitatively calculated. The comparative analysis reveals that soft-decision codes, such as Low-Density Parity-Check (LDPC) codes, significantly outperform hard-decision schemes by achieving the target BER of 10⁻⁵ at the lowest E_b/N_0. By providing detailed, comparative data and discussing the trade-off between performance and implementation complexity, this research offers a practical guide for selecting the optimal FEC structure in the design of high-speed optical transmission systems and establishes the necessary groundwork for future research. https://www.joeds.ir/article_237770.html The application of graphene-based nanomaterials for microwave absorption has been hindered by high conductivity and excessively high dielectric loss . A promising approach to address this challenge is achieving impedance match by utilizing ferromagnetic graphene while simultaneously suppressing conductivity. In this study, we explored B-doped and Co-decorated graphene ( GBCoαα ) for this purpose . Density Functional Theory ( DFT ) and theoretical calculations were employed to compute impedance parameters and reflection loss . The nanocomposite exhibited distinctive dielectric properties attributed to charge transfer at the GBCo interface, leading to outstanding microwave absorption performance over a broad frequency range . Specifically, compared to GCo22, GCo33, and GBCo33 nanocomposites, GBCo22 demonstrated superior microwave absorption efficiency ( reflection loss, RL = -42.02 dB ) due to its favorable impedance matching and a well-balanced interplay of dielectric and magnetic losses . The results indicate that in the frequency range of 2-18 GHz, the proposed structure exhibits a reflection loss below -10 dB. https://www.joeds.ir/article_237771.html This research presents an intelligent framework for the automatic classification of ground targets in Synthetic Aperture Radar images. The principal challenges addressed are the diversity of target characteristics and the presence of inherent speckle noise, which complicate manual analysis and classification. To address these issues, a hybrid architecture based on a Convolutional Neural Network and a Genetic Algorithm is proposed. In this method, the Genetic Algorithm is employed for the automated optimization of the CNN architecture's hyperparameters, while the Lee filter is utilized in the pre-processing stage to effectively reduce noise and preserve edges. Performance evaluation on the standard MSTAR dataset demonstrates that the proposed method achieves a remarkable accuracy of 99.33% in classifying the denoised images. This result clearly indicates the superior performance of the proposed method compared to other conventional approaches. The outcome of this research confirms the high efficacy of the hybrid approach in addressing the complex challenges of SAR image processing and represents a significant step towards the development of robust Automatic Target Recognition systems. https://www.joeds.ir/article_240573.html Multi-object tracking is a fundamental computer-vision task that has drawn ever-increasing attention because of its scientific and commercial potential. Nevertheless, accurate object tracking remains highly challenging; these challenges include the high similarity and density of detected objects. Moreover, occlusion and viewpoint changes can occur as objects move. In this paper, a framework for real-time multi-object tracking is introduced that is based on a modified version of the SORT algorithm. Multi-object tracking is divided into two parts. In the first part, object detection is performed using the YOLO family; if information is lost at this stage, compensating for this lost information later is impossible. The second part concerns object tracking, which itself comprises three stages: first, feature extraction, for which transfer learning with the YOLOv8 family is used; second, position prediction using the Kalman filter; and third, data association and object matching, for which the Hungarian algorithm is employed. In the data-association stage, the use of deep-learning methods has recently expanded. Finally, the MOTA metric was adopted as the result, yielding 65.3, which is 7.2 % better than the reference paper. https://www.joeds.ir/article_240575.html The widespread use of SUAVs in modern battlefields poses a serious threat to military forces and equipment and highlighting the need to develop recognition methods. Traditional techniques face major limitations due to their dependence on parameters such as aspect angle, range and polarization, as well as the inherent characteristics of SUAVs, including low altitude flight, low speed, high maneuverability, and small RCS. this study, by using the Singularity Expansion Method, the system identification approach and employing adaptive and fixed RMSE criteria extracts the statistical features of the targets and introduces some multidimensional feature spaces constructed from the zeros and poles of the target’s transfer function in the resonanc. For evaluation, 3D models of a fixed wing SUAV (Skylark) and a multirotor (Matrice 400) were simulated over the 120–600 MHz frequency range and under various SNR levels. The results indicate that the complex natural resonances depending on the target’s geometry, dimensions, and material provide a reliable basis for recognizing SUAVs. Increasing the SNR from 13 to 19 dB improved the adaptive RMSE by 24%, while the fixed mode, despite its lower accuracy, reduced processing time by 99%. https://www.joeds.ir/article_240576.html In this paper, transmit beamforming and power control of active phased array radars is deployed to reduce probability of interception. With assumption, that the position of the interceptor is known using the information obtained from electronic support measure systems. Effective radiated power of radar in taegt and interceptor directions analysed. To reduction of interception probability, the effective radiated power in the interceptor’s direction is managed while desired radar detection performance is guaranteed and the power budget of each T/R module is satisfied. Beamforming weights are analytically optimized based on a convex optimization framework. Two proposed beamforming designs are compared with the standard Log-Barrier method in terms of interception The results show that the performance of the proposed algorithms is equal to the results obtained from the CVX software package and it performs better than the benchmark Log_Barrier algorithm in terms of the probability of eavesdropping and in terms of computational complexity. probability and convergence time.