In order to solve the recognition of polyphase code radar signal, this paper gives two methods based on Frank code, i.e. the high-order spectrum recognition method and the fractional Fourier transform (FRFT) method, b...In order to solve the recognition of polyphase code radar signal, this paper gives two methods based on Frank code, i.e. the high-order spectrum recognition method and the fractional Fourier transform (FRFT) method, by analyzing the micro characteristics of polyphase code signals in time and frequency domain respectively. And a recognition algorithm based on Wigner-Hough transform (WHT) is developed in this paper. We verify the validity of each method by computer simulation and give relative merits and demerits. A set of results demonstrate that the algorithm based on Wigner-Hough transform has better recognition performance in low signal-to-noise (SNR) than others.展开更多
A fast parameter estimation algorithm is discussed for a polyphase coded Continuous Waveform(CW) signal in Additive White Gaussian Noise(AWGN).The proposed estimator is based on the sum of the modulus square of the am...A fast parameter estimation algorithm is discussed for a polyphase coded Continuous Waveform(CW) signal in Additive White Gaussian Noise(AWGN).The proposed estimator is based on the sum of the modulus square of the ambiguity function at the different Doppler shifts.An iterative refinement stage is proposed to avoid the effect of the spurious peaks that arise when the summation length of the estimator exceeds the subcode duration.The theoretical variance of the subcode rate estimate is derived.The Monte-Carlo simulation results show that the proposed estimator is highly accurate and effective at moderate Signal-to-Noise Ratio(SNR).展开更多
欺骗干扰能够获得距离和方位向压缩增益,使用较小功率即可实现对合成孔径雷达(SAR)的有效干扰。针对SAR的欺骗干扰抑制问题,提出了基于多个互正交多相编码在脉间捷变的抗干扰方法。利用加权循环算法,优化多相编码,提高自相关峰值,降低...欺骗干扰能够获得距离和方位向压缩增益,使用较小功率即可实现对合成孔径雷达(SAR)的有效干扰。针对SAR的欺骗干扰抑制问题,提出了基于多个互正交多相编码在脉间捷变的抗干扰方法。利用加权循环算法,优化多相编码,提高自相关峰值,降低自相关旁瓣和互相关峰值,提高抗转发式欺骗干扰性能。通过仿真比较了模拟退火算法、遗传算法优化多相编码与本文优化所得多相编码的自相关和互正交性能,并从多个不同干扰功率入手,对研究的多相编码抗欺骗干扰性能与二相编码进行了对比,20 d B干扰时该方法仍可达到88%的检测概率,证明了方法有效性。展开更多
针对低截获概率(Low Probability of Intercept,LPI)雷达多相码信号易混淆,且现有文献鲜有将调制类型识别和参数估计相结合的情况,提出了一种基于时频脊线的特征提取方法。在所提特征的基础上,通过支持向量机分类器进行调制类型识别;同...针对低截获概率(Low Probability of Intercept,LPI)雷达多相码信号易混淆,且现有文献鲜有将调制类型识别和参数估计相结合的情况,提出了一种基于时频脊线的特征提取方法。在所提特征的基础上,通过支持向量机分类器进行调制类型识别;同时,可实现对调制参数的估计,由提取的特征对带宽、编码长度、载频和码元内载频周期数进行估计。仿真结果证明,在较低信噪比(Signal-to-Noise Ratio,SNR)下,该方法对调制类型的平均识别率较为理想,对各调制参数的估计误差均在可接受范围内。对比实验显示,该方法优于传统的互相关法。与深度学习方法对比,该方法的运算量更小,且在小样本情况下具有更好的识别率,具有一定的应用价值。展开更多
针对传统多相码信号识别方法在低信噪比情况下分类精度不高、类识别率不均衡和识别方法不具有通用性的特点,提出了一种利用集成学习中的多类指数损失函数逐步添加模型(stagewise additive modeling using a multi-class exponential los...针对传统多相码信号识别方法在低信噪比情况下分类精度不高、类识别率不均衡和识别方法不具有通用性的特点,提出了一种利用集成学习中的多类指数损失函数逐步添加模型(stagewise additive modeling using a multi-class exponential loss function,SAMME)算法和残差神经网络(residual neural network,ResNet)的多相码信号识别方法。通过仿真实验对5类多相码信号进行了分类识别,验证了模型的有效性,分析了不同数量基学习器对模型的影响,最后与传统分类方法进行了对比。仿真结果表明,在信噪比低于6 dB的情况下,所提方法相对于单个残差网络提高了约10%的分类精度,同时缩小了类之间识别率的差距,相对于常用的分类方法也有很大的优势。展开更多
文摘In order to solve the recognition of polyphase code radar signal, this paper gives two methods based on Frank code, i.e. the high-order spectrum recognition method and the fractional Fourier transform (FRFT) method, by analyzing the micro characteristics of polyphase code signals in time and frequency domain respectively. And a recognition algorithm based on Wigner-Hough transform (WHT) is developed in this paper. We verify the validity of each method by computer simulation and give relative merits and demerits. A set of results demonstrate that the algorithm based on Wigner-Hough transform has better recognition performance in low signal-to-noise (SNR) than others.
文摘A fast parameter estimation algorithm is discussed for a polyphase coded Continuous Waveform(CW) signal in Additive White Gaussian Noise(AWGN).The proposed estimator is based on the sum of the modulus square of the ambiguity function at the different Doppler shifts.An iterative refinement stage is proposed to avoid the effect of the spurious peaks that arise when the summation length of the estimator exceeds the subcode duration.The theoretical variance of the subcode rate estimate is derived.The Monte-Carlo simulation results show that the proposed estimator is highly accurate and effective at moderate Signal-to-Noise Ratio(SNR).
文摘欺骗干扰能够获得距离和方位向压缩增益,使用较小功率即可实现对合成孔径雷达(SAR)的有效干扰。针对SAR的欺骗干扰抑制问题,提出了基于多个互正交多相编码在脉间捷变的抗干扰方法。利用加权循环算法,优化多相编码,提高自相关峰值,降低自相关旁瓣和互相关峰值,提高抗转发式欺骗干扰性能。通过仿真比较了模拟退火算法、遗传算法优化多相编码与本文优化所得多相编码的自相关和互正交性能,并从多个不同干扰功率入手,对研究的多相编码抗欺骗干扰性能与二相编码进行了对比,20 d B干扰时该方法仍可达到88%的检测概率,证明了方法有效性。
文摘针对低截获概率(Low Probability of Intercept,LPI)雷达多相码信号易混淆,且现有文献鲜有将调制类型识别和参数估计相结合的情况,提出了一种基于时频脊线的特征提取方法。在所提特征的基础上,通过支持向量机分类器进行调制类型识别;同时,可实现对调制参数的估计,由提取的特征对带宽、编码长度、载频和码元内载频周期数进行估计。仿真结果证明,在较低信噪比(Signal-to-Noise Ratio,SNR)下,该方法对调制类型的平均识别率较为理想,对各调制参数的估计误差均在可接受范围内。对比实验显示,该方法优于传统的互相关法。与深度学习方法对比,该方法的运算量更小,且在小样本情况下具有更好的识别率,具有一定的应用价值。
文摘针对传统多相码信号识别方法在低信噪比情况下分类精度不高、类识别率不均衡和识别方法不具有通用性的特点,提出了一种利用集成学习中的多类指数损失函数逐步添加模型(stagewise additive modeling using a multi-class exponential loss function,SAMME)算法和残差神经网络(residual neural network,ResNet)的多相码信号识别方法。通过仿真实验对5类多相码信号进行了分类识别,验证了模型的有效性,分析了不同数量基学习器对模型的影响,最后与传统分类方法进行了对比。仿真结果表明,在信噪比低于6 dB的情况下,所提方法相对于单个残差网络提高了约10%的分类精度,同时缩小了类之间识别率的差距,相对于常用的分类方法也有很大的优势。
