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15 September 2023 Volume 36 Issue 9
  
    Short-Term Power Load Forecasting Based on FA-SVR-LSTM Combined Model
    WEN Yanfei,WANG Wanxiong
    Electronic Science and Technology. 2023, 36(9):  1-7.  doi:10.16180/j.cnki.issn1007-7820.2023.09.001
    Abstract ( 298 )   HTML ( 55 )   PDF (957KB) ( 71 )  
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    As the basis for maintaining the operation and analysis of the power grid system, short-term power load forecasting provides judgment basis and information for the economic dispatch and safety analysis of the power grid system, and plays an important role in maintaining the normal operation of the power grid system. In this study, the FA(Firefly Algorithm) is used to optimize the penalty factor c, nuclear parameter g of SVR(Support Vector Regression) model and the number of neurons m and learning rate lr of LSTM(Long Short-Term Memory) model. The FA-SVR-LSTM combined prediction model is established using the optimal parameters, and the sample data are predicted. Taking the historical data of power load of Florida as an example, four reference models of LSTM, SVR, FA-SVR and FA-LSTM are established to predict the power load of 360 h in 15 days, and the results are compared with those of FA-SVR-LSTM. The experimental results show that compared with LSTM and SVR model, the prediction accuracy of FA-SVR-LSTM model is improved by 33.184 9% and 30.326 5%, respectively. The evaluation values of MAPE and RMSE are significantly lower than those of the other four models. These results indicate that the prediction effect of FA-SVR-LSTM combined model is significantly improved when compared with other models.

    Design of Low Sidelobe W-Band Sparse Array Consists of Horn-Like Antenna
    ZHOU Biao,ZHANG Shuai,ZHANG Dexun,LIN Zhicheng,WANG Jian
    Electronic Science and Technology. 2023, 36(9):  8-14.  doi:10.16180/j.cnki.issn1007-7820.2023.09.002
    Abstract ( 295 )   HTML ( 12 )   PDF (1500KB) ( 57 )  
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    In order to solve the design problem of wideband wide-angle low sidelobed phased array antenna caused by factors such as large loss, manufacturing process, T/R component size, number of channels and location, a wideband type horn antenna unit in the frequency range of 80~110 GHz is designed in this study, and the antenna standing wave ratio is less than 1.8. Considering the space limitation of T/R components, a 64-element high-gain, low-sidelobe, wide-band and wide-angle scanning array antenna is designed by optimizing the array position, and a small low-profile air waveguide feeding network is designed for the array. The simulation results show that the designed 64 element sparse array has the advantages of wide bandwidth, wide angle, low sidelobes, high gain, easy fabrication and realization, and the gain is higher than 22.6 dB, the sidelobes level is lower than -6.2 dB, and the active VSWR of each element is less than 2 under the scanning range of ±40°.

    Design of SoC Secure Memory Based on Lightweight Block Cipher
    LIU Wei,ZENG Xiangyi,XIAO Hao
    Electronic Science and Technology. 2023, 36(9):  15-20.  doi:10.16180/j.cnki.issn1007-7820.2023.09.003
    Abstract ( 204 )   HTML ( 17 )   PDF (976KB) ( 61 )  
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    In view of the security risks faced by RAM(Random Access Memory) and Flash memory of embedded on-chip systems, this study outlines physical attacks against memory of traditional SoC(System on Chip) chips, and presents a memory controller that supports encryption algorithms. Using the lightweight block cipher algorithm LBlock-s, the cryptographic security analysis shows that the algorithm has a good resistance to differential cryptanalysis. Compared with traditional block cipher algorithms such as AES(Advanced Encryption Standard), the proposed method reduces hardware resource consumption while guaranteeing security and is suitable for all kinds of resource-constrained secure SoC chips. To improve the data throughput, the hardware structure of the algorithm is expanded so that the standard 32 rounds of encryption or decryption take 1 clock cycle. This scheme guarantees that sensitive data cannot be parsed even if acquired by the attacker without consuming more hardware resources and encrypting delay, and effectively avoids physical attack on the security chip.

    TDOA Sound Source Localization Method Based on Particle Swarm Optimization Algorithm
    ZHANG Dagui,ZHOU Zhifeng,ZHANG Yi,WANG Liduan
    Electronic Science and Technology. 2023, 36(9):  21-28.  doi:10.16180/j.cnki.issn1007-7820.2023.09.004
    Abstract ( 320 )   HTML ( 18 )   PDF (1009KB) ( 92 )  
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    In order to solve the problem of 3D coordinate estimation of sound source based on planar microphone array, this study introduces particle swarm optimization algorithm in TDOA(Time Difference of Arrival) sound source localization algorithm. The true value of the delay difference is calculated using the generalized cross-correlation method of the PHAT(Phase Transform) weighting function. Combined with the coordinate position of the microphone, the estimated value of the delay difference between the hypothetical sound source arriving at the microphone is calculated through the geometric relationship. The sum of the squares of the error between the actual value and the estimated value of the design delay is the particle fitness function. The particle swarm optimization algorithm is used to search for the sound source points in the space that conform to the fitness function, so as to realize the sound source position estimation. The simulation results show that the proposed algorithm has better robustness and noise resistance than the spherical interpolation method when the calculation speed is similar to that of the spherical interpolation method.

    Wide Scanning and Low Sidelobe K-Band Circularly Polarized Thinning Array
    ZHOU Biao,ZHANG Shuai,YAN Denghui,LIN Zhicheng,WANG Jian
    Electronic Science and Technology. 2023, 36(9):  29-34.  doi:10.16180/j.cnki.issn1007-7820.2023.09.005
    Abstract ( 130 )   HTML ( 4 )   PDF (1984KB) ( 56 )  
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    This study presents a low profile wide band wide angle low sidelobe circular-polarized sparse phased array antenna for K band. The radiation part of the antenna unit consists of a circular patch with parasitic ring radiator and an L-shaped patch. Due to the feed port limitations of the T/R assembly, the antenna is miniaturized through the underlying microstrip cable connection metal through-hole, making the antenna easy to integrate with the internal T/R assembly. At the same time, the sequential rotation technique is applied in the antenna array to expand the axial ratio bandwidth. In addition, considering the constraints of the element layout introduced by T/R assembly, a multi-constrained subarray level optimization algorithm is designed. Only through the optimization of the subarray position, a 400-cell wide band, wide angle and low sidelobe sparse array is designed. Simulation results show that the sparse array achieves normal gain of 30.46 dB, beam width of less than 4.5° and sidelobes level of less than -13.13 dB within ±55° under the sparse ratio of 44.6%, which is suitable for K-band satellite communication phased array antenna.

    Visual Detection of Structural Cracks Using Depth Deformable Contour ModelLAI
    Bin ,WANG Sen
    Electronic Science and Technology. 2023, 36(9):  35-40.  doi:10.16180/j.cnki.issn1007-7820.2023.09.006
    Abstract ( 143 )   HTML ( 5 )   PDF (3171KB) ( 59 )  
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    At present, the deep learning instance segmentation method for crack detection mainly generates a boundary box through target detection to segment pixel by pixel mask, which will affect the detection effect of structural crack contour, and is accompanied by complex post-processing cost. To solve this problem, this study proposes to use deep snake algorithm model of deep deformable contour to identify and detect structural cracks. The robustness of the model is improved by data enhancement of the structural crack data set. At the same time, the pre training network parameters on the large image data set coco are transferred to the structural crack segmentation model as initialization by transfer learning. The experimental results on the self-made crack image data set show that the trained model can correctly identify the crack object and complete the segmentation of multiple crack targets at the same time. On the premise of the average detection time of 0.12 s, the AP50 reaches 75.4%. The comparison between the proposed methool and other deep learning models and edge detection algorithms also reflect the advantages of Deep Snake algorithm.

    Rotation Angle Estimation of JPEG Images Using Block Artifact Spectrum Analysis
    DANG Lianghui,ZHANG Yujin
    Electronic Science and Technology. 2023, 36(9):  41-49.  doi:10.16180/j.cnki.issn1007-7820.2023.09.007
    Abstract ( 57 )   HTML ( 2 )   PDF (3902KB) ( 32 )  
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    Image rotation makes fake images more realistic in geometric perspective, and the performance of existing JPEG image rotation angle estimation algorithms is easily disturbed by block artifacts and the image block size. It remains an imminent and challenging work for the rotation angle interval [1°,15°]. This study presents an effective algorithm to estimate the rotation angle of JPEG images based on block artifact spectral analysis. Firstly, the edges of the image are extracted and removed using a variant colony algorithm to highlight block effects. Secondly, the effect of image texture is further mitigated by cross-differentiation. Thirdly, extraneous peaks are removed in the Fourier transform domain by setting reasonable thresholds and using a Gaussian high-pass filter to reduce interference. Finally, the amplitude component of the Fourier spectrum is projected into the polar coordinates, and the polar angle corresponding to the peak in the polar coordinates is the estimation of rotation angle we need. The experimental results show that the average absolute error of the method is lower than that of the existing methods for the detection of small-size JPEG images whose rotation angle lies within the [1°,15°] interval. Besides, when the compression quality factor is gradually reduced, the performance of the proposed method is still better than the existing methods, and the robustness of the proposed method to JPEG compression is better.

    Image Dehazing Algorithm Based on Residual Attention and Semi-Supervised Learning
    SUN Xi,YU Lianzhi
    Electronic Science and Technology. 2023, 36(9):  50-57.  doi:10.16180/j.cnki.issn1007-7820.2023.09.008
    Abstract ( 118 )   HTML ( 5 )   PDF (3402KB) ( 55 )  
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    Dehazing algorithms based on training synthetic images cannot achieve satisfactory results on real image data sets. In view of these problems of unsatisfactory generalization ability, this study proposes a semi-supervised learning network based on residual attention mechanism for single image dehaze. The backbone network of the proposed model consists of an encoder and a decoder. Using stacked residual attention modules, the feature weights of different scales are adjusted to give more weight to important features. Local residuals choose to bypass hazy regions so that the model can focus on valid information. The training in this study is divided into two branches: supervised learning and unsupervised learning, which input synthetic data and real data respectively. Dark channel loss and total variational loss are used to constrain the unsupervised branches. The results show that the proposed algorithm obtains ideal results on both synthetic data sets and real data sets, and the average processing time of images is only 0.01 s, achieving a balance between dehazing effect and processing time.

    Design of Broadband Sound Transmission Structure Based on Gradient Fluid-Solid Superlattice
    ZHANG Lijuan,ZHANG Sai,SHEN Jiamin,GU Xin
    Electronic Science and Technology. 2023, 36(9):  58-65.  doi:10.16180/j.cnki.issn1007-7820.2023.09.009
    Abstract ( 74 )   HTML ( 2 )   PDF (2791KB) ( 36 )  
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    In order to weaken the Gibbs oscillation in the passband of periodic fluid-solid superlattice structure, a gradient fluid-solid superlattice structure (GFSL) with symmetrical linear distribution of solid layer filling fraction is designed by introducing structural gradient. Based on the transfer matrix method, the acoustic transmission characteristics of GFSL structure are calculated. On this basis, the effects of different gradient parameters on the sound transmission characteristics of GFSL structure are discussed to adjust the passband performance. The sound transmission characteristics of GFSL structure are verified from the perspectives of frequency domain and time domain by finite element method. The results show that the GFSL structure effectively eliminates the Gibbs oscillation and forms a flat broadband passband. The proposed GFSL structure has potential application value in underwater high-intensity ultrasonic energy concentration, acoustic impedance matching and filtering.

    Optimization and Implementation of 2-Base Exponential Function Algorithm Based on FPGA
    CHENG Tiantian,SONG Yukun
    Electronic Science and Technology. 2023, 36(9):  66-72.  doi:10.16180/j.cnki.issn1007-7820.2023.09.010
    Abstract ( 178 )   HTML ( 11 )   PDF (1789KB) ( 78 )  
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    In view of the problems of small calculation value range and large error in common hardware implementation methods of exponential function, an improved hardware implementation method of base 2 exponential function y=2x combining polynomial and lookup table is proposed. The optimization algorithm adopts the interval division to compress the input x to (-1/512,1/512) and then performs the Taylor series expansion of the exponential function to ensure that the accuracy reaches 10-16 in the double-precision floating-point when the Taylor series is expands to x4. And storage resource consumption is reduced by optimizing intermediate data storage policies. Hardware design implementation and performance test of the improved algorithm on Xilinx XC7K325T FPGA(Field Programmable Gate Array) are performed by using Verilog HDL. The results show that within the value range that double-precision floating-point numbers can represent, the full-domain exponential function calculation can be supported by the designed circuit with less storage consumption, and the calculation accuracy is not less than 10-16.

    Optimal Design of Double Parameter ECDSA Algorithm over GF (2m)
    FANG Yingli,FANG Yuming
    Electronic Science and Technology. 2023, 36(9):  73-78.  doi:10.16180/j.cnki.issn1007-7820.2023.09.011
    Abstract ( 53 )   HTML ( 2 )   PDF (1534KB) ( 31 )  
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    In view of the problems of the classical elliptic digital signature algorithm, such as low signature efficiency and forgery signature attack, a provably secure double parameter elliptic curve digital signature scheme is proposed and implemented by hardware in this study. Based on the existing research, the Lopez-Dahab projection coordinate system is used to reduce the number of modular inverse operations in the signature process, and the group operation layer is partially parallel operations to improve the efficiency of the high point multiplication algorithm.For finite field operations, fast modular multiplication algorithm of serial parallel hybrid structure, fast modular square operation and improved Itoh-Tsujii modular inverse algorithm are adopted.The security analysis result of the scheme shows that the scheme can effectively resist forgery attack and random number replacement attack, and ensure the security in the process of message transmission. The timing simulation results show that the implementation of a point multiplication operation occupies 23 087 logic units, the operation process only needs 476 clocks,and the number of clocks is reduced by 75% when compared with similar point multiplication operations.

    A Dynamic-Static Load Balancing Algorithm Based on Improved Genetic Algorithm
    HU Yifei,BAO Ziqun,BAO Xiaoan
    Electronic Science and Technology. 2023, 36(9):  79-85.  doi:10.16180/j.cnki.issn1007-7820.2023.09.012
    Abstract ( 228 )   HTML ( 8 )   PDF (927KB) ( 59 )  
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    In view of the problems that current load balancing algorithm affects system efficiency under low load and poor distribution efficiency under high load, based on Nginx server, a dynamic and static load balancing algorithm based on improved genetic algorithm is proposed in this study. The algorithm chooses to use server performance parameters based on CPU performance, memory performance, disk I/O and network bandwidth as server node performance evaluation indexes and static weighted polling algorithm weights under low load, and designs a dynamic load balancing algorithm under high load based on the change of node performance utilization rate as a percentage of the cluster average load utilization rate by introducing operation conversion thresholds and dynamic. By introducing the improved genetic algorithm of operation transition threshold and dynamic triangular function operation probability as the threshold calculation method, the transformation of static algorithm dominant area into dynamic algorithm dominant area is calculated. This study designs comparison experiments to verify that the proposed algorithm has better load balancing effect when compared with weighted polling algorithm, probabilistic meritocracy algorithm and dnfs_conn algorithm in the experimental environment, and has about 15% improvement in the values of average response time and actual concurrent connections when compared with dnfs_conn algorithm.

    Transformer-Based Maneuvering Target Tracking
    DANG Xiaofang,CAI Xingyu
    Electronic Science and Technology. 2023, 36(9):  86-92.  doi:10.16180/j.cnki.issn1007-7820.2023.09.013
    Abstract ( 150 )   HTML ( 9 )   PDF (1753KB) ( 87 )  
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    In view of the problems of maneuvering targets tracking when the Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM), such as the gradient disappears and explodes due to the long sequence, which leads to the poor tracking effect after the target maneuvers, a Transformer-Based Network (TBN) is proposed.TBN uses an encoder designed based on attention mechanism to extract the historical track features of the target sequence and improves the ability of capturing the maneuvering situation of the target.Using the Center Max(CM) normalization method, all sequences are subtracted from their initial values, which reduces the complexity of network learning and enhances the generalization of network.The results show that the position accuracy and velocity accuracy of the CM normalization and TBN method are improved by 11.2% and 41.9%, compared with the LSTM network in the large track data set with maneuvering conditions.The method proposed in this study can track the target correctly even when the observed value is missing.

    Research and Design of One Extended Target Simulation System for High Resolution Force Radar
    LUO Jie,KONG Lingfeng,ZHANG Kunfeng
    Electronic Science and Technology. 2023, 36(9):  93-102.  doi:10.16180/j.cnki.issn1007-7820.2023.09.014
    Abstract ( 128 )   HTML ( 7 )   PDF (4455KB) ( 61 )  
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    This study presents the design and implementation of a high-resolution radar extended target simulation system for simulating extended target echoes in high-resolution radar. The study establishes target echo models for one-dimensional distance targets, two-dimensional surface targets, and three-dimensional volume targets. The key technologies used to achieve the design and implementation of the high-resolution radar extended target simulation system include wideband RF receiver technology, large instantaneous bandwidth baseband echo signal generation technology, target RCS(Radar Cross Section) data acquisition and modulation technology, and wideband agile frequency synthesizer. The system is used to conduct RF simulation and two-dimensional imaging processing of a typical fighter jet target, and the results are compared with the simulation results obtained using RadBase simulation software to verify the effectiveness of the system. The validation results indicate that the RF simulation and two-dimensional imaging processing results of the system are consistent with the simulation results obtained using the RadBase software.

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