Stepped frequency chirp signal imaging radar jamming using two-dimensional nonperiodic phase modulation

Stepped frequency chirp signal obtains high-resolution radar images by synthesizing multiple narrowband chirp pulses.It has been one of the most commonly used wideband radar waveforms due to its lower demand for radar instant bandwidth.In this paper,we propose a radar jamming method using two-dimensional nonperiodic phase modulation against stepped frequency chirp signal imaging radar.Using the unique property of nonperiodic phase modulation,the proposed method can generate high-level sidelobes that perform as a special blanket jamming along both the range and azimuth directions and make the target unrecognizable.Then,the influence of different modulation parameters,such as the code width and duty ratio,are further discussed.Based on this,the corresponding parameter design principles are presented.Finally,the validity of the proposed method is demonstrated by the Yake-42 plane data simulation and measured unmanned aerial vehicle data experiment.

HIGH RESOLUTION RANGE PROFILE FORMATION BASED ON LFM SIGNAL FUSION OF MULTIPLE RADARS

This paper presents a new method of High Resolution Range (HRR) profile formation based on Linear Frequency Modulation (LFM) signal fusion of multiple radars with multiple frequency bands. The principle of the multiple radars signal fusion improving the range resolution is analyzed. With the analysis of return signals received by two radars,it is derived that the phase difference between the echoes varies almost linearly with respect to the frequency if the distance between two radars is neg-ligible compared with the radar observation distance. To compensate the phase difference,an en-tropy-minimization principle based compensation algorithm is proposed. During the fusion process,the B-splines interpolation method is applied to resample the signals for Fourier transform imaging. The theoretical analysis and simulations results show the proposed method can effectively increase signal bandwidth and provide a high resolution range profile.

Adaptive digital self-interference cancellation based on fractional order LMS in LFMCW radar

Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.

Speed-Direction Sensing under Multiple Vehicles Scenario Using Photonic Radars

Recent reports from World Health Organization(WHO)show the impact of human negligence as a serious concern for road accidents and casualties worldwide.There are number of reasons which led to this negligence;hence,need of intelligent transportation system(ITS)gains more attention from researchers worldwide.For achieving such autonomy different sensors are involved in autonomous vehicles which can sense road conditions and warn the control system about possible hazards.This work is focused on designing one such sensor system which can detect and range multiple targets under the impact of adverse atmospheric conditions.A high-speed Linear Frequency Modulated Continuous Wave(LFMCW)based Photonic Radar is proposed to detect multiple targets by integrating Mode division multiplexing(MDM).Reported results in terms of range frequency,Doppler frequency and range resolution are demonstrated using numerical simulations with the bandwidths of 1 and 4 GHz and under adverse atmospheric conditions carrying 75 dB/km of attenuation.To prove the effectiveness of the proposed photonic radar,moving targets are also demonstrated with different speed.System reported substantial range resolution of 15 cm using 1 GHz of bandwidth and 3 cm using 4 GHz of bandwidth.

Parameter estimation method for a linear frequency modulation signal with a Duffing oscillator based on frequency periodicity

In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.

Transfer characteristics of dynamic biochemical signals in non-reversing pulsatile flows in a shallow Y-shaped microfluidic channel: signal filtering and nonlinear amplitude-frequency modulation

The transports of the dynamic biochemical signals in the non-reversing pulsatile flows in the mixing microchannel of a Y-shaped microfluidic device are ana- lyzed. The results show that the mixing micro-channel acts as a low-pass filter, and the biochemical signals are nonlinearly modulated by the pulsatile flows, which depend on the biochemical signal frequency, the flow signal frequency, and the biochemical signal transporting distance. It is concluded that, the transfer characteristics of the dynamic biochemical signals, which are transported in the time-varying flows, should be carefully considered for better loading biochemical signals on the cells cultured on the bottom of the microfluidic channel.

An approach for parameter estimation of combined CPPM and LFM radar signal

In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation （CPPM） and linear frequency modulation （LFM）, which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval （PRI） of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform （CHT） algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio （SNR） is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.

Parameter estimation of LFM signals based on time reversal

In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propagation effect,resulting in a higher signal to noise ratio(SNR)threshold,a parameter estimation method for LFM signals based on time reversal is proposed.The proposed method avoids SNR loss in the process of estimating the frequency,thus reducing the SNR threshold.The simulation results show that the threshold is reduced by 5 dB compared with the discrete polynomial transform(DPT)method,and the root-mean-square error(RMSE)of the proposed estimator is close to the Cramer-Rao lower bound(CRLB).

基于线性调频连续波的合作式通信辐射源测距

针对加速运动目标参数估计中,离散多项式变换方法无法进行非整数估计的问题,本文提出基于瑞夫算法的离散多项式变换法和基于Chirp-Z变换的离散多项式变换法2种新型离散多项式变换算法,对加速运动目标速度和加速度进行估计,并对2种算法的估计误差和计算量进行了分析比较。结果表明:2种算法在信噪比-20 dB时均方误差开始接近克拉美罗界。基于瑞夫算法的离散多项式变换法与3次迭代基于Chirp-Z变换的离散多项式变换法均可在较低信噪比下可实现任意频率的有效估计且性能接近,二者均可实现低信噪比下速度、加速度的有效估计,但基于瑞夫算法的离散多项式变换法计算量远小于3次迭代基于Chirp-Z变换的离散多项式变换法。

面向高速移动环境的二级信号检测算法

正交时间序列复用(OTSM)可以以更低的复杂度实现类似正交时频空间(OTFS)调制的传输性能,为未来需要低复杂度收发器的高速移动性通信系统提供一种有前景的解决方法。针对现有的基于时域的高斯-赛德尔(GS)迭代均衡效率不高的问题,提出二级信号检测算法。首先在时域进行低复杂度线性最小均方误差(LMMSE)检测,其次采用连续超松弛(SOR)迭代算法进一步消除残余符号干扰。为进一步提高收敛效率和检测性能,对SOR算法进行线性优化得到改进SOR(ISOR)算法。仿真实验结果表明,与SOR算法相比,ISOR算法在增加较低复杂度前提下可以提升检测性能并加快算法收敛。与GS迭代算法相比,ISOR算法采用16QAM调制且误码率为10-4时有1.61 dB的增益。

基于FRFT的低信噪比LFM信号参数快速估计算法

基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)对线性调频(Linear Frequency Modulated,LFM)信号参数进行估计,问题关键是确定FRFT最佳阶数,根据误差迭代思想提出新的参数估计算法,该算法利用归一化带宽和旋转角的转化关系,由估计误差推算角度差值,有效降低了运算量,不需要调频斜率正负的先验信息,改进的对数搜索算法可以进一步提高参数估计结果的稳定性和可靠性。仿真结果表明,信噪比在-8 dB以上时该方法在高效率的前提下仍具有良好的参数估计性能,平均估计误差在1%以内,估计结果接近Cramer-Rao下限,满足工程实时处理需求。

高频雷达中射频干扰的RD图表现机理与建模仿真

射频干扰对于高频超视距雷达是一大威胁。本文研究射频干扰的距离-多普勒图表现机理和建模方法,分析了射频干扰频域特性与距离-多普勒图表现的关系,讨论了雷达信号处理中的射频干扰信号频谱变化。根据高斯白噪声通过线性滤波器的特性,设计滤波器响应函数来产生不同频谱和距离-多普勒图形态的射频干扰。基于以上研究,本文将射频干扰分为单频、窄带和宽带3类,归纳出射频干扰的距离-多普勒图表现机理,并提出了基于卷积的射频干扰新型建模方法。实测数据和仿真表明:本文对射频干扰距离-多普勒图表现机理分析合理,建模方法能很好地模拟多数实测干扰距离-多普勒图形态。

一种面向低成本轻量级雷达的单比特复用阵列信号收发框架

面向低成本轻量级雷达的应用需求,该文提出了一种联合单比特采样量化和时分复用接收机的雷达信号收发框架。首先,通过介绍该框架的工作原理,阐述其在节省接收机数量方面的优势。从雷达资源配置的角度,分析了单比特采样量化在该框架中的重要性,并提出了该框架可利用时间换空间,获得比经典线性调频连续波雷达更好的探测性能。接着,推导了雷达测距、测速和测角公式,以及目标参数估计的克拉美罗界。在此基础上,验证了该框架的性能优势,同时也给出了其稳定工作的信噪比条件。最后,利用一种基于单比特二维多重信号分类的速度维配对算法,验证了该框架获取目标原理的正确性,以及性能分析的可靠性。

基于非负矩阵分解的双曲调频信号目标回波增强

双曲调频信号是主动声呐中常用的多普勒不敏感信号。在实际使用中,由于信道变化和混响影响,目标回波较弱。针对水下航行器主动声呐探测性能下降问题,本文提出基于非负矩阵分解的双曲调频信号目标回波增强方法。该方法对目标回波和干扰信号的基矩阵分别定义,将发射信号的时频图作为目标回波的频率信息矩阵,对目标回波的时间信息矩阵做出约束,迭代处理完成目标回波的增强,获得较高增益的匹配回波检测结果。数值仿真和海上试验结果表明:本文方法与传统匹配滤波方法相比,其峰均比值提高了2 dB以上,提高了回波检测结果。

超短基线在低频基阵指向性测量中的应用

随着水声换能器工作频率的降低,实验室空间很难达到自由场和远场测量的要求。而开阔水域的水下环境复杂,基阵很难实现更深层次的吊放,需要安装价格昂贵的吊装平台来获取标准声源与待测基阵之间的相对位姿,效率低且维护成本高。文章采用超短基线定位技术,信号选用线性调频脉冲信号与伪随机编码脉冲信号,并分别基于脉冲压缩法和复相关算法实现距离和相位测量。比对湖上定位精度试验和基阵指向性标定静态试验的结果显示:角度误差为2.5°以内;-6 dB波束宽度在2~10 kHz频率范围内测量误差在5.38%以内。证明超短基线定位在低频基阵指向性标定的可行性。

基于延迟断点映射FMCW的双功能雷达通信系统设计

基于调频连续波(Frequency Modulated Continuous Wave, FMCW)的双功能雷达通信(Dual-Functional RadarCommunication, DFRC)系统具有时频利用率高、抗多普勒性能强、距离旁瓣低的特点。现有的FMCW-DFRC波形系统产生双功能性能恶化,并增加通信接收机的链路复杂度。设计了一种基于延迟断点映射(Delayed Breakpoint Mapping, DBM)FMCW的DFRC系统,通过啁啾周期内延迟断点位置的映射和被分割的簇间的相位进行数据调制。通信接收端在载波混频和欠采样后,在数字域实现去啁啾、码片对齐和数据解调,极大降低了接收端生成相干信号和ADC性能的需求。在雷达处理链路中,设计了断点区域删除与拼接(Breakpoint Area Deletion and Splicing, BADS)方案,使DFRC的雷达性能与无调制的FMCW一致。仿真结果表明,与无补偿的方案相比,BADS方案距离图像的副瓣幅度减小约37 dB,且不受调制数据的影响。与现有基于啁啾波形的DFRC方案的通信性能相比,DBM-FMCW降低了约3 dB误符号率。

基于多核DSP的星载双基FMCW SAR成像算法实现

调频连续波(frequency modulated continuous wave,FMCW)合成孔径雷达(synthetic aperture radar,SAR)降低了传感器的峰值传输功率,使系统的重量和成本最小化,被广泛应用于机载平台。将双基地构型与FMCW技术相结合,应用于星载平台,即构成星载双基地FMCW SAR。本文对距离多普勒(range-Doppler,RD)算法进行改进,建立起一种高性能的适宜星载双基地平台的FMCW SAR成像频域算法,这种算法的处理精度明显提高,成像效果更好。基于多核数字信号处理器(digital signal processor,DSP)构建适用于星载双基SAR成像算法的并行处理架构,完成软硬件设计实现。验证了所提软件架构可以满足实时成像需求,以及算法工程化实现的可行性。

基于CNN-Swin Transformer Network的LPI雷达信号识别

针对在低信噪比(SNR)条件下,低截获概率雷达信号调制方式识别准确率低的问题,提出一种基于Transformer和卷积神经网络(CNN)的雷达信号识别方法。首先,引入Swin Transformer模型并在模型前端设计CNN特征提取层构建了CNN+Swin Transformer网络(CSTN),然后利用时频分析获取雷达信号的时频特征,对图像进行预处理后输入CSTN模型进行训练,由网络的底部到顶部不断提取图像更丰富的语义信息,最后通过Softmax分类器对六类不同调制方式信号进行分类识别。仿真实验表明:在SNR为-18 dB时,该方法对六类典型雷达信号的平均识别率达到了94.26%,证明了所提方法的可行性。

同步提取变换去噪的雷达信号调制识别方法

针对已有Cohen类时频分布等方法时频聚焦能力不足、在低信噪比(signal to noise ratio,SNR)情况下调制识别准确率低的问题,提出一种基于同步提取变换(synchro-extracting transform,SET)去噪的分组卷积神经网络调制识别方法。所提方法使用SET对雷达信号进行时频分析,以获得良好的时频聚焦性,提高时频分析的计算效率;通过Viterbi算法搜索估计时频系数矩阵中的瞬时频率轨迹,综合考虑信号能量强度分布与瞬时频率轨迹的平滑性,并对得到的瞬时频率轨迹进行中值滤波以去除脉冲噪声;保留瞬时频率轨迹邻域的时频系数,以达到时频图去噪的目的。最后,将去噪后的时频图送入具有残差连接的分组卷积神经网络进行特征提取与调制识别。实验结果表明,当SNR为-12 dB时,去噪后的SET时频图时频聚焦性好,调制识别准确率比未去噪的识别准确率提高了13.69%,证明所提出的雷达信号调制识别方法在低SNR条件下对多种复杂调制类型的信号具有良好的识别性能。

对调制识别网络隐身的雷达发射信号生成方法

雷达对抗场景中,电子侦察系统通过引入基于深度学习方法的智能脉冲调制识别网络,极大提升了对雷达信号的识别准确率。为了提高雷达信号的调制隐身抗识别能力,提出一种可以令深度识别网络错误预测的雷达发射信号生成方法。该方法首先通过短时傅里叶变换得到信号的时频谱;然后迭代生成携带调制隐身信息的时频谱;最后利用改进逆短时傅里叶变换得到时域调制隐身发射信号。该方法生成的雷达信号对以时频图为输入的调制识别网络隐身,并可实现回波信号的脉冲压缩处理。仿真结果验证了所生成信号的抗识别有效性、噪声鲁棒性和脉压可行性。