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| 1 | Improved de-interleaving algorithm of radar pulses based on dual fuzzy vigilance ART显示文摘As a core part of the electronic warfare(EW) system,de-interleaving is used to separate interleaved radar signals. The de-interleaving algorithm based on the fuzzy adaptive resonance theory(fuzzy ART) is plagued by the problems of premature saturation and performance improving dilemma. This study proposes a dual fuzzy vigilance ART(DFV-ART) algorithm to address these problems and make the following improvements. Firstly, a correction method is introduced to prevent the network from prematurely saturating;then, the fuzzy vigilance models(FVM) are constructed to replace the conventional vigilance parameter, reducing the error probability in the overlapping region;finally, a dual vigilance mechanism is introduced to solve the performance improving dilemma. Simulation results show that the proposed algorithm could improve the clustering accuracy(quantization error dropped60%) and the de-interleaving performance(clustering quality increased by 10%) while suppressing the excessive proliferation of categories. | JIANG Wen FU Xiongjun CHANG Jiayun | 2020 | Journal of Systems Engineering and Electronics2020，31，2： | 4 |
| 2 | Design of high-performance energy integrator detector for wideband radar显示文摘Target detection for wideband radar has recently received extensive attention. The classical energy integrating(EI)detector will always accumulate excess clutter or noise energy,which leads to unacceptable performance deterioration if the detection window is not selected properly. In this paper, an EI detector for the distributed targets in the Gaussian environment is proposed.First, at the stage of preparatory work, the target models are proposed, then, the problem formulation is introduced. Subsequently,in the aspect of optimizing the method of detection window search and the method of threshold setting, the detailed design stages of the proposed detector are provided. Furthermore, theoretical analyses show that the proposed detector is easy to hardware implementation, and it does not need the prior knowledge about the spatial distribution of the target scattering centers in practical radar detection application. Finally, the performance assessment conducted by Monte Carlo simulations verifies that the proposed detector outperforms the conventional detectors. | CHANG Jiayun FU Xiongjun JIANG Wen XIE Min | 2019 | Journal of Systems Engineering and Electronics2019，30，6： | 2 |
| 3 | Wideband radar detector based on characteristic parameters of echoes显示文摘The statistical characterization of radar range cells with the target signals is much more distinct than that of the range cells with noise-only signals.Hence,the quasi-optimal detection principle based on the characteristic parameters of echo signals is adopted to develop a detector of range-spread targets in Gaussian noise.Firstly,the characteristic parameters of the return signals in the entire range profiles of radar are investigated.Secondly,the clustering analysis of the characteristic parameter matrix is discussed to extract the test statistic of echoes.Finally,the probabilities of detection and false alarm of the proposed detector are provided.Theoretical analysis shows that the proposed detector does not need the prior knowledge about the spatial distribution of the target scattering centers in practical scenarios,and it is simple and robust even in low signal-to-noise ratio(low-SNR)scenarios.Monte Carlo(MC)simulations reveal that the detection performance of the proposed detector outperforms the conventional detectors. | CHANG Jiayun FU Xiongjun JIANG Wen XIE Min | 2019 | Journal of Systems Engineering and Electronics2019，30，5： | 1 |
| 4 | An improved de-interleaving algorithm of radar pulses based on SOFM with self-adaptive network topology显示文摘As a core part of the electronic warfare(EW) system,de-interleaving is used to separate interleaved radar signals. As interleaved radar pulses become more complex and denser, intelligent classification of radar signals has become very important. The self-organizing feature map(SOFM) is an excellent artificial neural network, which has huge advantages in intelligent classification of complex data. However, the de-interleaving process based on SOFM is faced with the problems that the initialization of the map size relies on prior information and the network topology cannot be adaptively adjusted. In this paper, an SOFM with self-adaptive network topology(SANT-SOFM) algorithm is proposed to solve the above problems. The SANT-SOFM algorithm first proposes an adaptive proliferation algorithm to adjust the map size, so that the initialization of the map size is no longer dependent on prior information but is gradually adjusted with the input data. Then,structural optimization algorithms are proposed to gradually optimize the topology of the SOFM network in the iterative process,constructing an optimal SANT. Finally, the optimized SOFM network is used for de-interleaving radar signals. Simulation results show that SANT-SOFM could get excellent performance in complex EW environments and the probability of getting the optimal map size is over 95% in the absence of priori information. | JIANG Wen FU Xiongjun CHANG Jiayun QIN Rui | 2020 | Journal of Systems Engineering and Electronics2020，31，4： | 1 |
| 5 | Micro-Doppler Parameter Estimation Method Based on Compressed Sensing显示文摘A micro-Doppler parameter estimation method based on compressed sensing theory is proposed in this paper.The micro-Doppler parameter estimation algorithm was improved for micro-motion targets with translation in this paper.Relatively ideal micro-Doppler parameter estimation results were obtained.The proposed micro-Doppler parameter estimation was compared with the traditional micro-Doppler parameter estimation algorithm.Requirements for return signal length were analyzed with this new algorithm and its performance was also analyzed in various environments with different SNR. | Jiayun Chang Xiongjun Fu Wen Jiang Min Xie | 2019 | Journal of Beijing Institute of Technology2019，28，2： | 0 |
| 6 | Geographical distribution of Aspergillus flavus in peanut harvest period in China显示文摘In order to grasp the distribution of Aspergillus flavus in the soil of peanut production areas in China,A.flavus biomarkers were tested on 555 soil samples from 37 sampling points in 17 provinces,peanut fields in four agroecological zones(Southern area,Yangtze River Basin,Northern area,Northeast area).The results showed that(1)the cultivation amount of A.flavus per gram of soil in the Yangtze River Basin is 1.30 times that of the southern area,1.56 times that of the northern area,and 6.20 times that of the northeast area,with obvious regional characteristics.(2)In the Yangtze River basin,the change of longitude in the east-west direction has no direct impact on the cultivation amount of A.flavus per gram of soil.(3)In the east coast,the A.flavus cultivated per gram of soil increased first and then decreased with the increase of latitude from south to north.(4)A.flavus can be isolated in the soil samples above 1000 m.Field pollution is an important source of aflatoxin contamination in peanut.The study on the distribution of A.flavus in soil in China could provide theoretical support for the early warning and prevention and control measures of aflatoxin contamination in peanut. | Xiaohan Liu Jiayun Fu Mingbo Wen Haohua Gu Pingping Ji Xiaofeng Yue Xiaoqian Tang Meijuan Liang Yang Zhou Qi Zhang Peiwu Li | 2023 | Oil Crop Science2023，8，2： | 0 |
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