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 contribu- tions 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 EJNo of received signals is established. Ex- perimental results are also presented in accor- dance with analysis.

Performance of Order-statistics Constant-false-alarm-rate Detector with Noncoherent Integration and Its Application to OTH Radar

Noncoherent integration is often ed for approving performance in detection of radar signal. Order-statistics constant false alarm rate (OS-CFAR) detector has some advantages in clutter and multiple target situations. AnOS-CFAN detector with noncoherent integration after Square law envelope detector is presented and an analysis of detection performance for the chi-Square family of Swerling fluctuating targets is given. Its application to the high frequency(HF) ground wave over-the-horizon (OTH) radar is discussed as well.

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

he cell averaging and the order statistics are two typical algorithms for constant false alarm rate detector in radar system. They have different advantages in stationary noise background and fluctuation clutter environment respectively. This paper presents a doublethreshold constant false alarm rate detector constructed on the basis of synthesizing the advantages of the two algorithms above and avioding their disadvantages. The performance of the detector is analyzed, and the simulation result is given.

Constant False Alarm Rate Acquisition Algorithm for Compass B1C Signal

In order to improve the sensitivity of the Compass B1C signal acquisition for the receiver,the principle of constant false alarm rate(CFAR)is applied for the B1C pilot channel acquisition to realize the dynamic adjustment of the threshold of acquisition against the carrier to noise ratio.The non-coherent data/pilot combined acquisition algorithm for B1C signal is analyzed to make full use of the power of the B1C signal under the condition of low carrier to noise ratio.On this basis,to improve the acquisition sensitivity of the receiver,the principle of constant false alarm probability is applied for the non-coherent data/pilot combined acquisition algorithm.Theoretical analysis and simulations show that the non-coherent data/pilot combined acquisition algorithm with CFAR improves the B1C signal acquisition sensitivity of the receiver significantly,and achieves a better Receiver Operating Characteristic compared with the traditional acquisition algorithms.

Switching variability index based multiple strategy CFAR detector

A switching variability index （SVl） 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 switching- CFAR 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.

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.

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.

MODIFIED HIGHER ORDER SPECTRAL ANALYSIS BASED TDE ALGORITHM FOR CFAR SIGNAL DETECTION PROBLEM

With the conditions of small data size and low Signal-to-Noise Ratio (SNR), the application of Higher Order Statistics (HOS) is restrained not only by its high estimation variance,but also by its low estimation precision. Therefore, a modified HOS based Time Delay Estimation (TDE) algorithm is proposed to overcome these problems. Comparing with the conventional TDE algorithms, the estimation variance is improved greatly. A typical simulation example is completed in order to test the performance of the algorithm proposed, which shows that the proposed algorithm has advantages over the traditional ones in both detection performance and computation efficiency.

Detection optimization for resonance region radar with dense multi-carrier waveform

Unlike the existing resonance region radar systems （RRRS ） that transmit the orthogonal frequency division multiplexing （OFDM）multi-carrier waveform,the dense multi-carrier （DMC）radar waveform which has a narrower frequency interval than the traditional OFDM waveform is proposed.Therefore,in the same frequency bandwidth,the DMC waveform contains more sub-carriers and provides more frequency diversity.Additionally,to further improve detection performance,a novel optimal weight accumulation target detection （OWATD）method is proposed,where the echo electromagnetic waves at different frequencies are accumulated with the optimal weight coefficients.Then,with the signal-to-noise ratio （SNR）of echo waveform approaching infinity,the asymptotic detection performance is analyzed, and the condition that the OWATD method with the DMC outperforms the matched filter with the OFDM is presented.Simulation results show that the DMC outperforms the OFDM in the target detection performance,and the OWATD method can further improve the detection performance of the traditional methods with both the OFDM and DMC radar waveform.

New CFAR target detector for SAR images based on kernel density estimation and mean square error distance

A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the clutter PDF in the reference window are estimated by the non-parametric density estimation. The target detector is defined as the mean square error （MSE） distance between the two PDFs. The CFAR detection in SAR images having multiplicative noise is achieved by adaptive kernel bandwidth proportional to the clutter level. In addition, for obtaining a threshold with respect to a given probability of false alarm （PFA）, an unsupervised null distribution fitting method with outlier rejection is proposed. The effectiveness of the proposed target detector is demonstrated by the experiment result using the RADATSAT-2 SAR image.

Distribution-based CFAR detectors in SAR images

As traditional two-parameter constant false alarm rate （CFAR） target detec-tion 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.

PERFORMANCE COMPARISON OF A LINEARLY COMBINED ORDERED-STATISTIC DETECTORS UNDER POSTDETECTION INTEGRATION AND NONHOMOGENEOUS SITUATIONS

Several Constant False Alarm Rate （CFAR） architectures, where radar systems often employ them to automatically adapt the detection threshold to the local background noise or clutter power in an attempt to maintain an approximately constant rate of false alarm, have been recently proposed to estimate the unknown noise power level. Since the Ordered-Statistics （OS） based algorithm has some advantages over the Cell-Averaging （CA） technique, we are concerned here with this type of CFAR detectors. The Linearly Combined Ordered-Statistic （LCOS） processor, which sets threshold by processing a weighted ordered range samples within finite moving window, may actually perform somewhat better than the conventional OS detector. Our objective in this paper is to analyze the LCOS processor along with the conventional OS scheme for the case where the radar receiver incorporates a postdetection integrator amongst its contents and where the operating environments contain a number of secondary interfering targets along with the primary target of concern and the two target types fluctuate in accordance with the Swerling Ⅱ fluctuation model and to compare their performances under various operating conditions.

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.

CFAR DETECTORS FOR HIGH RESOLUTION RADAR IN NON-GAUSSIAN CLUTTER

For high resolution radar, the echoes of target come from several points rather than one point as in low resolution radar. In this case the target is called an extended target. This paper presents two CFAR detectors for such a target in non Gaussian clutter, which are CA CFAR and OS CFAR detectors. The detection performances of the two detectors are evaluated.

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)。

改进的SAR图像双参数CFAR舰船检测算法

双参数CFAR检测中设置了目标窗口、保护窗口和背景窗口3个窗口,并且窗口的大小,滑动步长都要进行经验训练得到,效率低,对距离很近的舰船SAR图像会产生漏检。针对这些不足,该文提出了一种改进的双参数CFAR检测算法,该算法只取目标窗口和背景窗口,通过把泄露到背景窗口中的舰船部分去除并对背景窗口中的剩余部分进行均值和方差估计来检测舰船,并且将窗口滑动步长取为目标窗口尺寸。相对双参数CFAR算法,结构得到了简化,检测结果的虚警率减小,对距离很近的舰船不会产生漏检,计算效率得到了改善。仿真结果表明了方法的有效性。

基于熵特征的DRFM有源欺骗干扰CFAR检测

基于数字射频存储(digital radio frequency memory,DRFM)技术的转发式干扰的存在性检测是对抗有源欺骗干扰的前提。干扰机的相位取样量化会导致干扰信号有谐波分量的寄生。在雷达距离/速度波门内同时存在目标信号和欺骗干扰信号的情形下,利用经验模态分解(empirical model decomposition,EMD)算法分离出干扰信号谐波分量,通过提取干扰谐波分量与目标回波在时频域上能量分布特征差异,提出了一种基于时频域熵特征的有源欺骗干扰检测方法。该方法不需要估计噪声参数,且具有恒虚警(constant false-alarm rate,CFAR)特性。蒙特卡罗仿真结果验证了该方法的有效性。

SAR图像CFAR检测的快速算法综述

针对合成孔径雷达(Synthetic aperture radar,SAR)图像目标检测中恒虚警率(Constant false alarm rate,CFAR)算法的广泛应用,进行CFAR检测的快速算法分析具有重要研究价值.首先概述了当前国内外对SAR图像CFAR检测快速算法的研究现状;然后分别从快速预筛选和迭代计算方法两个方面对各类快速算法的实时性及性能进行了分析总结,给出了四种基本CFAR检测器的迭代计算公式,并提出了一种研究CFAR检测快速算法的基本框架,现有的快速算法均可纳入该理论框架予以分析;最后,以经典双参数CFAR检测算法为例,对该基本框架进行仿真实现和性能分析,验证了其可行性与检测性能.结果表明:新的CFAR检测快速算法基本框架充分融合了快速预筛选思想和迭代计算方法的优势,有效提高了CFAR算法在SAR图像检测应用中的执行效率.

相参雷达时频域CFAR检测门限获取方法研究

相参雷达体制下采用时频域处理的CFAR检测器面临的一个共性问题就是由于时频域杂波模型与实际不匹配,以及数据样本有限导致的模型参数无法准确估计,进而导致实际检测器性能总是与理论设计有较大差距.为此,本文通过分析相参雷达时频域恒虚警(CFAR)检测门限与虚警概率的函数关系,提出一种基于最小二乘拟合的检测门限获取方法,并给出了其工程实现途径.最后,采用实测数据对该方法进行检测性能仿真实验,实验结果表明,提出的检测门限获取方法有效可行,具有很好的工程应用前景.