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周文 , 郝新红 , 董二娃 , 等 . 基于滑动多周期FFT的调频引信抗扫频干扰方法 [J ] . 兵工学报 , 2023 , 44 ( 6 ): 1744 - 1753 . DOI: 10.12382/bgxb.2022.0119 http://doi.org/10.12382/bgxb.2022.0119 针对调频引信快速傅里叶变换(FFT)谐波包络提取方法对抗扫频干扰效果差的问题,提出一种滑动多周期FFT处理方法。在分析扫频干扰作用下调频引信的失效机理的基础上,提出通过多周期FFT进行回波能量的相干积累,实现对干扰的有效抑制,并在相邻处理窗口间滑动更新处理数据,进一步提取预定炸高对应的差频谐波包络进行门限判决。仿真及实测结果表明:滑动多周期FFT处理方法能在扫频干扰下有效提取目标谐波包络特征,相较于传统单周期FFT处理方法,显著改善峰值旁瓣比,提高了调频引信抗扫频干扰的能力。

ZHOU W , HAO X H , DONG E W , et al. Anti-frequency sweeping jamming method for FM fuze using sliding multi-cycle FFT [J ] . Acta Armamentarii , 2023 , 44 ( 6 ): 1744 - 1753 . (in Chinese) DOI: 10.12382/bgxb.2022.0119 http://doi.org/10.12382/bgxb.2022.0119 This study proposes a sliding multi-cycle fast Fourier transform (FFT) processing method to address the problem of poor performance of the FFT harmonic envelope extraction method used in FM fuze under frequency sweeping jamming conditions. The proposed method aims to achieve effective interference suppression by coherently accumulating echo energy through multi-period FFT processing. The processing data is updated by sliding between adjacent processing windows, and the difference frequency harmonic envelope corresponding to the predetermined blast height is further extracted for threshold judgment. The simulated and measured results show that compared with traditional single-cycle FFT processing method, the new method can effectively extract the target harmonic envelope characteristics under frequency sweeping jamming, significantly improve the peak-to-side lobe ratio, and enhance the anti-frequency sweeping jamming performance of FM fuze.

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刘冰 , 郝新红 , 周文 , 等 . 基于BAS-BPNN的调频无线电引信目标与扫频干扰识别方法 [J ] . 兵工学报 , 2023 , 44 ( 8 ): 2391 - 2403 . DOI: 10.12382/bgxb.2022.0248 http://doi.org/10.12382/bgxb.2022.0248 针对调频无线电引信在复杂电磁战场环境对抗调幅扫频式干扰能力不足的问题,提出一种基于频域信息熵、范数熵和倒频谱熵的调频无线电引信目标识别方法。基于目标和调幅扫频干扰作用下的调频无线电引信检波端输出信号,提取频域信息熵、范数熵和倒频谱熵构建特征矩阵,并利用天牛须搜索(BAS)算法对反向传播神经网络(BPNN)初始权重值和阈值进行优化,利用优化后的BPNN对目标和调幅扫频干扰信号进行分类识别。实测数据实验结果表明,特征提取方法构成的特征矩阵在目标与干扰之间具备可分性,BAS算法优化获得最优参数的BPNN时,该分类器的识别准确率可以达到99.96%,显著提升了调频无线电引信对抗调幅扫频干扰的能力。

LIU B , HAO X H , ZHOU W , et al. Recognition method of target and sweep jamming signal for FM radio fuze based on BAS-BPNN [J ] . Acta Armamentarii , 2023 , 44 ( 8 ): 2391 - 2403 . (in Chinese) DOI: 10.12382/bgxb.2022.0248 http://doi.org/10.12382/bgxb.2022.0248 In order to solve the problem that the FM radio fuze is unable to counter AM frequency sweep jamming signals on battlefield in a complex electromagnetic environment, a target recognition method based on frequency domain information entropy, norm entropy and cepstrum entropy is proposed. Based on the output signal of the FM radio fuze under the action of the target and AM frequency sweep jamming signal, the frequency information entropy,norm entropy and cepstrum entropy are extracted to construct the feature matrix. The BAS algorithm is used to optimize the initial weight values and threshold of the back propagation neural network (BPNN). Then the optimized BPNN is used to classify and recognize the target and AM frequency sweep jamming signal. The experimental results with the measured data show that the feature matrix formed by feature extraction has separability between the target and the jamming signal. When the BPNN with optimal parameters is obtained by the optimization of the BAS algorithm, the recognition accuracy of the classifier can reach 99.96%, which significantly improves the ability of the FM radio fuze to counter AM frequency sweep jamming signals.

周文 , 郝新红 , 杨瑾 , 等 . 基于多尺度色散熵与支持向量机的调频引信扫频干扰信号识别方法 [J ] . 探测与控制学报 , 2023 , 45 ( 6 ): 21 - 26 .

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LI X X , ZHANG S N , ZHAO H C , et al. Identification of fuzzy small-sample terrain targets based on 1DC-CGAN and wavelet energy features [J ] . Acta Armamentarii , 2022 , 43 ( 10 ): 2545 - 2553 . (in Chinese) DOI: 10.12382/bgxb.2021.0505 http://doi.org/10.12382/bgxb.2021.0505 The carrier-free UWB fuze is featured by high distance resolution, strong anti-interference capability, and rich information about target structure. Also, it is not easily affected by light and climate conditions. When striking ground targets, different terrain will affect the blast height of the fuze, which in turn affects the damage effect. A terrain identification system based on carrier-free UWB fuze is thus proposed, which requires rich experimental data for accurate target identification. The acquisition of terrain echoes is time-consuming and costly, and the number of acquired echoes is often limited, which may affect the recognition accuracy. To expand the data set, an improved conditional generation adversarial network is proposed, replacing the fully connected layers of the generator and discriminator with one-dimensional convolution, adding batch normalization to achieve signal generation while reducing pattern collapse, and enhancing the sequence generation effect under small sample conditions. In addition, the wavelet energy features of the expanded echo signals are used as input features, and the particle swarm optimized BP (PSO-BP) neural network is used to achieve intelligent terrain classification. Experimental results show that the PSO-BP neural network trained on the expanded training set has improved the accuracy by more than 4% compared with training on the original training set.

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