Frame Detection Based on Cyclic Autocorrelation and Constant False Alarm Rate in Burst Communication Systems

Frame detection is important in burst communication systems for its contributions in frame synchronization.It locates the information bits in the received data stream at receivers.To realize frame detection in the presence of additive white Gaussian noise(AWGN) and frequency offset,a constant false alarm rate(CFAR) detector is proposed through exploitation of cyclic autocorrelation feature implied in the preamble.The frame detection can be achieved prior to bit timing recovery.The threshold setting is independent of the signal level and noise level by utilizing CFAR method.Mathematical expressions is derived in AWGN channel by considering the probability of false alarm and probability of detection,separately.Given the probability of false alarm,the mathematical relationship between the frame detection performance and E_b/N_0 of received signals is established.Experimental results are also presented in accordance with analysis.

A Double-threshold Constant False Alarm Rate Detector And Its Performance Analysis

ＡＤｏｕｂｌｅ┐ｔｈｒｅｓｈｏｌｄＣｏｎｓｔａｎｔＦａｌｓｅＡｌａｒｍＲａｔｅＤｅｔｅｃｔｏｒＡｎｄＩｔｓＰｅｒｆｏｒｍａｎｃｅＡｎａｌｙｓｉｓＷａｎｇＷｅｉ（王威），ＰｅｎｇＹｉｎｇｎｉｎｇ（彭应宁）（Ｄｅｐｔ．ｏｆＥｌｅｃｔｒｏｎｉｃＥｎｇｉｎ...

Adaptive detection of range-spread targets in homogeneous and partially homogeneous clutter plus subspace interference

Adaptive detection of range-spread targets is considered in the presence of subspace interference plus Gaussian clutter with unknown covariance matrix.The target signal and interference are supposed to lie in two linearly independent subspaces with deterministic but unknown coordinates.Relying on the two-step criteria,two adaptive detectors based on Gradient tests are proposed,in homogeneous and partially homogeneous clutter plus subspace interference,respectively.Both of the proposed detectors exhibit theoretically constant false alarm rate property against unknown clutter covariance matrix as well as the power level.Numerical results show that,the proposed detectors have better performance than their existing counterparts,especially for mismatches in the signal steering vectors.

Modeling Target Detection and Performance Analysis of Electronic Countermeasures for Phased Radar

Interference is a key factor in radar return misdetection.Strong interference might make it difficult to detect the signal or targets.When interference occurs in the sidelobes of the antenna pattern,Sidelobe Cancellation(SLC)and Sidelobe Blanking are two unique solutions to solve this problem(SLB).Aside from this approach,the probability of false alert and likelihood of detection are the most essential parameters in radar.The chance of a false alarm for any radar system should be minimal,and as a result,the probability of detection should be high.There are several interference cancellation strategies in the literature that are used to sustain consistent false alarms regardless of the clutter environment.With the necessity for interference cancellation methods and the constant false alarm rate(CFAR),the Maisel SLC algorithm has been modified to create a new algorithm for recognizing targets in the presence of severe interference.The received radar returns and interference are simulated as non-stationary in this approach,and side-lobe interference is cancelled using an adaptive algorithm.By comparing the performance of adaptive algorithms,simulation results are shown.In a severe clutter situation,the simulation results demonstrate a considerable increase in target recognition and signal to noise ratio when compared to the previous technique.

Switching variability index based multiple strategy CFAR detector

A switching variability index(SVI) constant false alarm rate(CFAR) detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switchingCFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVICFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.

Improved Ship Target Detection Accuracy in SAR Image Based on Modified CFAR Algorithm

A novel algorithm for the detection of ship target with high accuracy in the synthetic aperture radar(SAR) with high spatial resolution image is proposed. The SAR image may include not only the ship targets but also the interferences such as the sea clutter,the strong reflection target,the sidelobe and so on.The conventional constant false alarm rate(CFAR) algorithm has some disadvantages,and it has not enough prior information about the size of the ships. Hence,it cannot separate the adjacent ships correctly. A comprehensive algorithm based on the modified CFAR algorithm and opening operation is presented to solve the problem,and the detection accuracy can be improved consequently. The results of SAR image illustrate the effectiveness of the method in this paper.

A New Two-Stage Tunable Space-Time Adaptive Detector

In order to improve the rejection capability of mismatched interferer signals,a new two-stage detector is proposed under homogeneous scenarios with unknown covariance matrix,which is obtained by cascading the adaptive matched filter(AMF)detector and the enhanced RAO(EnRAO)detector.The new detector has constant false alarm performance,and the closed-form expression of probability of false alarm and probability of detection is derived.The performance of the new detector is assessed,and analyzed in comparison with other detectors.The results show that,the proposed detector can provide enhanced rejection capability in the case of mismatch,but the performance of the detector is slightly lost under the condition of matching.

一种机载组网雷达协同目标检测算法

多机协同的机载雷达组网联合目标探测可有效提高复杂电磁干扰环境下对隐身弱目标的探测能力。文中针对机载雷达组网探测时空间配准误差大、协同探测难以实现的难题,提出了一种基于轨迹空间配准的协同目标检测算法,通过雷达间少量距离-多普勒域数据及低检测门限下目标轨迹域数据的交互,采用极大似然估计广义似然比检测器对目标进行联合恒虚警检测(CFAR),并通过轨迹域空间配准与CFAR的迭代计算,实现配准精度和目标联合检测性能的双提升。数值仿真实验的结果表明,在四部雷达组网工作时,在相参积累后信噪比9 dB、虚警概率10-4的典型场景下,经过迭代处理,空间配准精度可达到一个距离-多普勒分辨单元;对目标的检测概率由单部雷达的28.5%提高到四部雷达协同下的83.67%。

基于等分剔除的毫米波雷达恒虚警检测研究

为解决车载毫米波雷达目标检测过程中在相邻多目标情况下会提高检测门限值,从而导致目标遮蔽现象,引发传统恒虚警(constant false alarm rate, CFAR)检测在多目标环境下产生漏检的问题,提出一种等分剔除恒虚警检测算法(equipartition deletion CFAR,ED-CFAR)。通过将目标两侧的参考单元等分取平均值得到子参考单元,对大于所有参考单元平均值的部分进行处理后排序,剔除部分较大子参考单元,计算得到门限值,与目标的信号幅度进行比较判断目标是否存在。仿真结果表明,在多目标检测的仿真场景下,信噪比为10 dB时,ED-CFAR算法的检测概率比单元平均恒虚警(CA-CFAR)算法提高0.39,比筛选平均恒虚警(CMLD-CFAR)算法提高了0.08,有效解决了传统均值类恒虚警检测在相邻多目标条件下的遮蔽问题。

基于双边截断的双参数海上风电站SAR图像CFAR检测

文章提出了1种基于双边截断的双参数海上风电站SAR图像CFAR检测器DTCS-TPCFAR,目的是提高在具有多个目标海上区域和石油泄漏区域等环境下对海上风电站的检测性能。DTCS-TPCFAR所提出的双边截断杂波的方法,能够同时消除高强度和低强度异常值的干扰,同时保留真实的杂波样本。通过使用最大似然估计计算双边截断后样本的均值和标准差,然后通过这2个参数估计值计算出截断阈值,最后再结合指定的虚警率(Probability of False Alarm,PFA)来对测试单元(Test Cell,TC)进行判断,完成最终的目标检测。这也是首次将CFAR检测器用于检测海上风电站。文章通过Sentinel-1数据集来验证该方法的有效性。实验结果表明,文章所提出的算法在相同指定虚警率下,具有更高的检测率(Detection Rate,DR)和更低的误报率(False Alarm Rate,FAR)。

Distribution-based CFAR detectors in SAR images

As traditional two-parameter constant false alarm rate (CFAR) target detection algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images increases, small targets present more pixels in SAR images. So the target distribution is of much significance. Distribution-based CFAR detection algorithm is presented. We unite the pixels around the test cell, and estimate the distribution of test cell by them. Generalized Likelihood Ratio Test (GLRT) is used to deduce the detectors. The performance of the distribution-based CFAR (DBCFAR) detectors is analyzed theoretically. False alarms of DBCFAR detection are fewer than those of CFAR at the same detection rate. Finally experiments are done and the results show the performance of DBCFAR is out of conventional CFAR. False alarms of DBCFAR detection are concentrated while those of CFAR detection are dispersive.

一种改进的高分辨率SAR图像超像素CFAR舰船检测算法

合成孔径雷达(SAR)图像舰船目标检测一直受到学者广泛关注,恒虚警率(CFAR)检测算法作为雷达图像经典目标检测算法被广泛应用于SAR图像舰船目标检测中。然而经典CFAR检测性能容易受到相干斑噪声影响,基于滑窗的检测结果对滑窗的尺寸选择非常敏感,难以保证杂波背景中不存在目标像素,并且计算效率较低。针对上述问题,该文提出了一种新的基于超像素无窗快速CFAR的SAR图像舰船目标检测算法。首先,利用基于密度的快速噪声空间聚类(DBSCAN)超像素生成方法生成SAR图像的超像素。在SAR数据服从混合瑞利分布的假设下,定义了超像素相异度。然后利用超像素精确估计每个像素的杂波参数,即使在多目标情况下,也可以克服传统CFAR滑动窗口的缺点。此外,基于SAR图像变异系数,提出了一种基于变异系数的局部超像素对比度来优化CFAR检测,以此消除大量杂波虚警,如陆地区域人造目标。对5幅SAR图像的实验结果表明,与其他方法相比,该文方法对不同场景SAR图像海面舰船目标检测都十分稳健。

基于线性模型广义似然比检验的突发信号检测方法

针对突发信号检测问题,分别建立了实信号检测和复信号检测的二元假设检验模型,基于线性模型广义似然比检验构建了检验统计量,得出了两种假设条件下检验统计量的概率分布函数,并根据检验统计量的概率分布函数推导出了检测器性能的解析表达式。用仿真的方法对推导结果进行了验证,仿真结果和理论结果完全一致。

利用相位特征筛选参考单元的改进CFAR方法

在传统单元平均恒虚警的基础上,提出一种利用相位特征筛选参考单元的改进恒虚警方法:通过判断连续脉冲回波在同一参考单元时的相位线性情况,剔除相位线性度强的参考单元,形成待检测单元适应性更好的检测门限,并通过仿真与实测数据测试,对比该算法与其他均值类恒虚警算法在不同环境背景下的检测性能。结果表明:在均匀单目标背景下,改进的恒虚警算法与单元平均恒虚警检测性能相当,比其他均值类检测器检测性能更好;而在多目标环境与杂波边缘环境下,改进的恒虚警算法相比其他均值类恒虚警算法能更好地避免目标遮蔽现象,检测性能更好。

子空间信号失配下的加权自适应检测器

对于多通道雷达系统,通常存在阵元误差及旁瓣干扰,此时雷达系统假定的目标导向矢量与真实值不同,从而导致信号失配。针对子空间模型下的失配信号检测问题,提出了一种具有恒虚警特性的加权自适应检测器,得到了检测器解析的检测概率和虚警概率计算表达式。根据系统需要,通过调整加权系数,所提出的检测器能够实现对失配信号的灵活检测。此外,对无信号失配的检测环境,在合适的权系数下,所提出的检测器能够提供比现有检测器更高的检测概率。

一种高速可配置二维CFAR检测器设计实现

恒虚警率(constant false alarm rate,CFAR)检测是雷达在干扰背景下检测目标的重要自适应算法。二维CFAR算法随着参考窗口尺寸增大,运算量较大,仅靠软件实现并不能满足较高的实时性需求。文章基于现场可编程门阵列(field programmable gate array,FPGA)设计实现了一种兼容CA-CFAR、GO-CFAR、SO-CFAR和OS-CFAR 4种二维CFAR算法的硬件加速器,同时实现标称化因子、检测器类型、排序值K、参考窗口和保护窗口大小可配置的灵活性,对于256×2048点距离-多谱勒矩阵(Range Doppler Matrix,RDM)数据,4种检测器均可在2.71 ms内完成检测。设计采用全流水结构,具有高实时性。

一种新的红外舰船图像分割方法

为了能够较好地分割出舰船目标,实现后续的目标检测和识别,提出一种基于显著性检测的红外舰船图像分割方法。首先利用AC算法和FT算法对图像进行处理,将两种方法处理后的显著图合并,提高目标轮廓亮度,然后利用选大恒虚警检测的原理对图像进行二值化分割。通过对比其他几种分割算法,证明此算法有更强的抗干扰能力,分割效果更好。

低信噪比下离散频率编码波形脉冲信号联合积累检测算法

雷达电子侦察环境下,非合作目标发射的离散频率编码(DFC)波形信号具有低截获、抗干扰的特性,在低信噪比(SNR)条件下传统方法难以实现波形的稳健积累及准确的脉冲检测,容易造成数据漏检与情报缺失。针对以上问题,该文提出一种联合的积累检测算法,该算法通过相关积累和非相干积累的联合处理实现了低信噪比下稳健脉冲信号包络的获取,并利用双向恒虚警(CFAR)检测和脉冲沿判决准则抑制了突跳噪声对脉冲检测的影响,实现了准确而稳健的脉冲到达时间和脉冲宽度的估计。相比于常规算法,该文在不需要任何先验信息的条件下能够实现离散频率编码波形信号的准确检测,检测虚警率低且具有良好的稳健性。仿真实验验证了所提算法的有效性和稳健性。

基于Grubbs准则的改进的2D CA-CFAR

在不同程度的噪声存在下,现代雷达通过恒虚警率(constant false alarm rate, CFAR)检测算法最大化提升目标的检测概率。针对车载毫米波雷达目标检测过程中传统2维单元均值类恒虚警率(two-dimensional cell averaging CFAR,2D CA-CFAR)检测算法在相邻多目标条件下出现的目标遮蔽问题,提出了一种基于格拉布斯(Grubbs)准则的2D CA-CFAR的改进算法。该方法利用Grubbs准则剔除参考窗中的奇异值和干扰目标,从而获得更加准确的检测阈值。仿真结果表明:改进的算法极大地降低了多目标环境中传统2D CA-CFAR检测器的“遮盖效应”,验证了所提算法的有效性。

基于SAR影像数据的多分辨率CFAR目标检测算法及精度分析

本文的研究目标是利用极化合成孔径雷达图像统计特性提高目标检测精度。从合成孔径雷达(SAR)成像机理出发,通过研究目标杂波的统计特性以及不同分辨率情况下人造目标的检测效果,探讨一种基于小波变换和恒虚警率(CFAR)的多分辨率算法进行目标检测的方法。实验分析比较传统CFAR目标检测算法与基于小波变换的多分辨率CFAR目标检测算法,实验结果表明,本文算法检测效果明显优于传统CFAR目标检测算法。