Quasi-LFM radar waveform recognition based on fractional Fourier transform and time-frequency analysis

Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.

RELATIONSHIP OF TARGET RECOGNITION PERFORMANCE AND RADAR WAVEFORM PARAMETERS

Target recognition performance can be affected by radar waveform parameters.In this paper,we established rigorous relationship between target recognition efficiency and the parameters of a repeatedly transmitted waveform.It is based on Kullback-Leibler Information Number of single observation(KLINs),which measures the dissimilarity between targets depicted by a range-velocity double spread density function in frequency domain.We considered two signal models which are different in the coherence of the observations.The method we proposed takes advantage of the methodology of sequential hypothesis test,and then the recognition performance in terms of correct classification rate is expressed by Receiver Operating Characteristic(ROC).Simulation results about the parameters of LFM signal show the validity of the method.

Wideband MIMO Radar Waveform Optimization Based on Range Profile

Aiming at the signal bandwidth design problem for multi-target imaging task,a kind of multiple input multiple output(MIMO)radar waveform design method is proposed.At first,the closed-loop feedback between the range profile and the signal bandwidth,which can design the minimum bandwidth of a transmitting signal that can distinguish each scatterer of the target in range direction,is established.Then,considering the request of beam pattern and the bandwidth limitation,a waveform optimization model is established and solved.Therefore,the multi-target observation and the dynamic adjustment of the signal bandwidth are accomplished.In the end,the simulation results prove the performance of the algorithm in a low SNR circumstance.

Simutaneous radar imaging and velocity measuring with step frequency waveforms

The principle and method of both radar target imaging and velocity measurement simultaneously based on step frequency waveforms is presented. Velocity compensation is necessary in order to obtain the good High resolution range profile since this waveform is greatly sensitive to the Doppler shift. The velocity measurement performance of the four styles is analyzed with two pulse trains consisted of positive and negative step frequency waveforms. The velocity of targets can be estimated first coarsely by using the pulse trains with positive-positive step frequency combination, and then fine by positive-negative combination. Simulation results indicate that the method can accomplish the accurate estimation of the velocity with efficient computation and good anti-noise performance and obtain the good HRRP simultaneously.

Othogonal Waveform Design for Multiple-Input Multiple-Output (MIMO) Radar

An effective numerical approach is developed for orthogonal waveform design for Multiple-Input Multiple-Output (MIMO) radar. The Doppler shift tolerance is considered in the design cost function. The design results indicate that the Doppler? tolerance of the designed orthogonal waveforms is markedly improved.

High Resolution MIMO-HFSWR Radar Using Sparse Frequency Waveforms

In high frequency surface wave radar (HFSWR) applications, range and azimuth resolutions are usually lim-ited by the bandwidth of waveforms and the physical dimension of the radar aperture, respectively. In this paper, we propose a concept of multiple-input multiple-output (MIMO) HFSWR system with widely sepa-rated antennas transmitting and receiving sparse frequency waveforms. The proposed system can overcome the conventional limitation on resolutions and obtain high resolution capability through this new configura-tion. Ambiguity function (AF) is derived in detail to evaluate the basic resolution performance of this pro-posed system. The advantages of the system of fine resolution and low peak sidelobe level (PSL) are demon-strated by the AF analysis through numerical simulations. The impacts of Doppler effect and the geometry configuration are also studied.

Adaptive waveform design based on Morlet wavelet for ultra-wideband MIMO radar

For the issue of deterioration in detection performance caused by dynamically changing environment in ultra-wideband（UWB） multiple input multiple output（MIMO） radar, this paper proposes a novel adaptive waveform design which is aimed to improve the ability of discriminating target and clutter from the radar scene. Firstly, a sequence of Morlet wavelet pulses with frequency hopping and pulse position modulation by Welch-Costas array is designed. Then a waveform optimization solution is proposed which is achieved by applying the minimization mutual-information（MI） strategy. After that, with subsequent iterations of the algorithm, simulation results demonstrate that the optimal waveform design method brings an improvement in the target detection ability in the presence of noise and clutter.

Performances of Micropower UWB Radar Using Orthogonal Waveforms

Radars and their applications were, for a long time, reserved to national defense, air security or weather service domains. For a few years, with the emergence of new technologies, radar applications have been developed and have become known in the civil domain. In particular, the arrival of UWB—Ultra-Wideband technology allows the design of compact and low-cost radars with multiple fields of application. In this paper, we focus on road applications, such as driving assistance with the objective of increasing safety and reducing accidents. In classical UWB radar systems, Gaussian and monocycle pulses are commonly used. In previous works, original waveforms based on orthogonal functions (Hermite and Gegenbauer) were proposed. These provide a good spatial resolution, suitable for radar detection. Another advantage of these waveforms is their multiple access capability, due to their orthogonality. The aim of the study presented in this article is to compare simulation and experimental results obtained, especially for short-range anticollision radar application, using these waveforms in one part and Gaussian and monocycle pulses in the other part. The originality of this paper relies on the new approach. Indeed, this comparison study using these waveforms has never been done before. Finally, some examples of real experiments in a real road environment with different waveforms are presented and analysed.

基于迭代二次优化算法的低截获波形序列设计

对抗条件下,低截获雷达通过发射特殊波形防止非合作电子侦察系统截获和检测其发射信号,是现代雷达技术的重点研究方向。该文旨在降低电子侦察系统的功率截获概率,在保证目标的辐射能量基础上,针对短时傅里叶变换(STFT)宽带数字侦察接收机特点,从能量的时频分布的角度将波形设计技术应用到无源对抗领域。首先,建立STFT宽带数字侦察接收机检测低截获模型,利用2次优化模型,将低截获问题转变为恒包络序列迭代优化问题;然后,为了获得较好的自相关性能,利用辅助标量,将优化模型转化为2次和形式,结合迭代算法得到了所提低截获波形序列;最后,讨论了计算复杂度。从仿真结果上看,所提序列比常见相位编码信号在相同的接收信噪比下具有更优的低截获能力,另外,引入Pareto权对所提序列的自相关特性进行控制,有效地提高了设计灵活性。

Q-Learning-Based Adaptive Waveform Selection in Cognitive Radar

Cognitive radar is a new framework of radar system proposed by Simon Haykin recently. Adaptive waveform selection is an important problem of intelligent transmitter in cognitive radar. In this paper, the problem of adaptive waveform selection is modeled as stochastic dynamic programming model. Then Q-learning is used to solve it. Q-learning can solve the problems that we do not know the explicit knowledge of state-transition probabilities. The simulation results demonstrate that this method approaches the optimal wave-form selection scheme and has lower uncertainty of state estimation compared to fixed waveform. Finally, the whole paper is summarized.

雷达波形对抗技术发展预见

随着雷达、电子侦察等传感器技术的进步,对电磁空间的操控从能量、频率向更高维度的波形发展,雷达波形对抗应运而生。阐述雷达波形对抗技术产生的背景、概念内涵和发展现状,同时提出可利用博弈思维建立雷达波形“OODA”回路,通过对雷达波形进行伪装、扰乱和利用以达成制造战场迷雾、创造新质杀伤链的效果。此外,介绍实现雷达波形对抗的波形隐匿、波形重建与利用、波形捷变反侦察等关键技术及原理。从波形管控等3个方面提出雷达波形对抗制胜电磁空间的发展建议。

面向外辐射源雷达目标探测的非时变稀疏模型和深度展开网络实现方法

近年来,基于稀疏特征提取的目标探测方法成为了雷达领域的研究热点。基于正交频分复用调制的外辐射源雷达(简称“外源雷达”)由于发射波形不受控,一方面构建的稀疏模型会随未知发射波形时变,导致相应的目标探测方法计算量大;另一方面目标回波常常因被直达波等强杂波掩盖而面临探测困难。在此背景下,利用外源雷达的正交频分复用波形特点,使用导频位置处频域信道响应提出一种非时变稀疏模型。通过将稀疏模型求解的每一次迭代过程替代为一层神经网络,首次研究了基于深度展开网络的智能化外源雷达目标探测实现方法。仿真和实测数据结果表明:所提方法与传统杂波抑制方法在目标探测上性能相近,但有着更低的计算复杂度,且无需人工设计稀疏矩阵等稀疏模型求解参数。

基于Jaya算法的LPI雷达波形设计

随着侦察设备与雷达之间的对抗加剧,雷达系统的射频隐身性能直接影响到武器装备的作战能力和生存能力,低截获概率雷达技术逐渐成为研究热点。文中研究了使用信息论在频域上设计低截获概率雷达波形的方法,利用Jaya算法实现了在满足一定的雷达探测性能前提下,最小化截获接收机性能的波形优化设计。考虑到该算法是不受约束的优化过程,利用罚函数将约束条件合并到适应度函数中。仿真结果表明所提方法不受初始值选择的影响,与传统算法在恰当选取初值后的优化效果相当,具有更高的普适性和稳定性。

一种基于深度强化学习的频率捷变雷达智能频点决策方法

自卫式干扰机发射的瞄准干扰使多种基于信号处理的被动干扰抑制方法失效,对现代雷达产生了严重威胁,频率捷变作为一种主动对抗方式为对抗瞄准干扰提供了可能。针对传统随机跳频抗干扰性能不稳定、频点选取自由度有限、策略学习所需时间长等问题,该文面向频率捷变雷达,提出了一种快速自适应跳频策略学习方法。首先设计了一种频点可重复选取的频率捷变波形,为最优解提供了更多选择。在此基础上,通过利用雷达与干扰机持续对抗收集到的数据,基于深度强化学习的探索与反馈机制,不断优化频点选取策略。具体来说,通过将上一时刻雷达频点及当前时刻感知到的干扰频点作为强化学习输入,神经网络智能选取当前时刻各子脉冲频点,并根据目标检测结果以及信干噪比两方面评价抗干扰效能,从而优化策略直至最优。从提高最优策略收敛速度出发,设计的输入状态不依赖历史时间步、引入贪婪策略平衡搜索-利用机制、配合信干噪比提高奖励差异。多组仿真实验结果表明,所提方法能够收敛到最优策略且具备较高的收敛效率。

一种幅相联合调制雷达波形设计与处理方法

随着脉内特征识别、信号分选等电子侦察技术的发展,雷达波形设计正面临严峻的挑战。幅度调制作为一种新型脉冲调制方式,能够增加信号时域的复杂性,提升波形的反识别能力。本文提出一种幅相联合编码雷达波形,通过幅度相位联合调制提升雷达波形的复杂度,具有良好的反侦察潜力;利用幅度上的稀疏采样特点,提出匹配滤波与压缩感知相结合的回波信号处理方法处理此信号,有效提升低信噪比条件下的检测概率。最后通过仿真实验证明了所提幅相联合调制雷达波形设计与处理方法的有效性。

基于改进混合量子遗传算法的二相编码雷达波形优化

针对当前雷达波形优化算法搜索策略单一、适用范围受限的问题,提出了一种基于改进混合量子遗传算法的二相编码雷达波形优化算法。所提算法采用了一种新的自适应旋转角度策略,根据迭代次数和余弦相似度动态调整旋转角度,提高了算法的收敛速度、全局搜索能力和求解质量。仿真结果表明,与遗传算法、基本量子遗传算法和混合量子遗传算法相比,对于包含了单峰、多峰和非凸优化问题的6个标准测试函数,所提算法在质量和资源消耗上均表现更好;对于二相编码雷达波形优化,证实了使用所提算法优化波形是可行和有效的。

基于数据失真的雷达通信一体化OFDM波形设计方法

正交频分复用(OFDM)波形设计是实现雷达通信一体化的物理层关键技术之一。OFDM波形通常存在峰均功率比(PAPR)高,以及波形自相关旁瓣电平高的问题。该文针对现有联合降低PAPR和自相关旁瓣方法存在的通信速率下降问题,提出了一种基于数据失真的一体化波形设计方法。该文还将通信数据的误差矢量幅度作为优化目标之一,降低了数据失真引起的通信误码率。首先,构建了PAPR约束下最小化积分旁瓣比和误差矢量幅度的优化模型。其次,根据调制星座图特点,通过外围星座调制的数据失真和所有调制数据失真,将多目标高维非凸优化问题转化为两个单目标优化子问题,分别采取凸松弛操作和交替方向乘子法(ADMM)求解简化后的子问题,得到低积分旁瓣比波形和PAPR约束下的低误差矢量幅度波形。仿真结果表明该方法设计的一体化波形可满足PAPR要求,同时具有良好的感知和通信性能。

基于分式二次规划的互模糊函数赋形方法

在开展认知雷达波形设计时,由于发射波形与接收滤波器的非匹配体制,互模糊函数赋形相比传统模糊函数赋形优化自由度更高。该文针对强杂波条件下微弱运动目标检测问题,以最大化信干噪比为优化准则,提出了一种联合发射相位编码序列与接收滤波器设计的互模糊函数赋形方法。在恒模约束下,优化问题被建模为二次分式规划形式;然后通过引入辅助变量,并利用共轭梯度法求解Stiefel流形空间上的最小化问题,非凸优化据此转化为恒模约束二次优化问题;通过交替循环和类幂迭代算法求得最优解。此外考虑到发射波形受硬件限制而难以实现严格恒模,该文构建了一种低峰均比约束二次优化问题模型,并利用最近邻向量法求得最优解。最后,不同参数下的仿真与实测数据实验表明,该文赋形方法相较于传统方法具有较高的信干噪比增益和收敛速度。

MIMO雷达分组正交波形集优化设计方法

在现代电子对抗中,数字射频存储(DRFM)设备能够快速截获机载脉冲多普勒雷达信号,能够实现对多输入多输出(MIMO)雷达的干扰。MIMO雷达可基于多组相互正交的波形集来对抗DRFM干扰。同时,为最大化MIMO雷达波形分集增益,每个脉冲内发射的波形也需要正交。为了平衡组内和组间的正交性,文中建立了一种分组正交波形集优化模型,其目标函数为组内和组间相关函数性能评估指标值的加权和;为了求解该优化问题,提出了一种分组正交波形集设计方法。所提方法将原优化问题简化为p-范数优化问题,基于MM算法导出了最小化目标函数的迭代求解表达式。仿真结果表明,所提方法可通过改变权重系数来灵活平衡MIMO雷达的干扰抑制性能和距离压缩性能。

基于ConvNeXt模型的雷达辐射源信号识别

针对雷达辐射源信号识别问题,提出一种基于ConvNeXt模型的识别算法。首先,由于不同调制方式的信号在时频域中具有不同的特征,因此将雷达辐射源信号的时频变换结果视为图像,并利用计算机视觉技术进行识别。其次,通过Choi-Williams分布(CWD)变换获得不同调制类型雷达信号的时频图像,对图像进行预处理。最后,使用ConvNeXt模型提取时频特征并识别雷达信号,解决低信噪比和有限样本条件下识别准确率不高的问题。实验表明,ConvNeXt模型具有更强的特征学习表征能力,有效提高16类信号的整体识别率,且对时频特性相近的6类信号(Frank、LFM、P1、P2、P3、P4)的识别精度更高。此外,该算法对小样本具有很好的鲁棒性。