Constant false-alarm rate algorithm based on test cell information

A new constant false-alarm rate (CFAR) detection algorithm, designated as switching CFAR (S-CFAR), is proposed and analysed. The S-CFAR algorithm selects CFAR reference samples using the magnitude of the sample in the cell under test, which is an information that has not been exploited in any other existing CFAR detectors. S-CFAR closed-form analysis is presented, and comparisons with other representative CFAR algorithms are given. An S-CFAR detector can be tuned such that it has a small CFAR loss when operating on a homogeneous background while achieving improved robustness in the presence of interfering targets and clutter power transition. The S-CFAR detector is also simple to design and implement since no sample ordering is required.     

Performance of the adaptive generalised matched subspace constant false alarm rate detector in non-Gaussian noise: an experimental analysis

The authors deal with the performance analysis of an adaptive version of the generalised matched subspace detector (GMSD) in compound-Gaussian clutter with unknown covariance matrix. The original GMSD was proposed to detect subspace signals in compound-Gaussian noise with known covariance matrix and ensures the constant false alarm rate (CFAR) property. In real situations, this assumption is unrealistic, which means that the covariance matrix must be estimated from training data. The authors use a robust estimate of the covariance matrix called the fixed-point estimate, recently proposed in the literature. The performance of the obtained adaptive detector, in terms of CFAR behaviour and probability of detection, is evaluated in the presence of real sea clutter data, collected by the McMaster IPIX radar.     

Sea clutter transient spatial coherence and scan-to-scan constant false alarm rate

High-resolution radar sea clutter exhibits long-term temporal and spatial correlation features consistent with the sea surface wave structure. Data are presented showing that there is a transient coherence in the long-term fluctuations of the clutter, which locally appears to show the single periodic fluctuation of a dominant wave, but when averaged over a large area is seen to contain a wide band of fluctuation frequencies. This apparently non-stationary behaviour makes it difficult to predict the local sea clutter level for constant false alarm rate (CFAR) thresholding using conventional techniques. A new method of scan-to-scan CFAR processing is therefore proposed, which takes account of this behaviour. The scheme is analysed and its performance characterised.     

非平稳环境下主动声呐检测器研究

针对在水下存在多途、混响及噪声边缘等非平稳背景条件下主动声呐检测器的检测性能,给出了一种变异指数的恒虚警率(Variability Index Constant False Alarm Rate,VI-CFAR)检测器。VI-CFAR结合了单元平均恒虚警率、最大选择恒虚警率和最小选择恒虚警率的检测算法,它在均匀平稳环境和非平稳环境下都具有较强的自适应性。理论分析和仿真结果表明,该检测器在均匀平稳背景下的检测性能与单元平均恒虚警率检测器相似,在多途、混响等干扰背景条件下具有较强的抗干扰能力,在噪声边缘背景下有较好的虚警概率控制能力且运算量小,是一种稳健的检测器。     

合成孔径雷达图像的恒虚警率目标检测

目的　对合成孔径雷达 (SAR)图像实施恒虚警率 (CFAR)目标检测 .方法　利用 K-Gamma和Weibull分布的杂波模型分别对海面和陆地的人造目标实施检测 ;同时 ,对不同杂波背景下 CFAR检测方法进行比较 .结果与结论　通过检测结果的比较 ,证实了 K-Gamma分布和 Weibull分布分别适合于海面和陆地杂波背景下的目标检测 ;在非均匀杂波背景中 ,有序统计量 (OS)较单元平均 (CA)方法具有优越性     

Performance analysis of ordered-statistic greatest of-constant false alarm rate with binary integration for M-sweeps

The performance of the ordered-statistic greatest of (OSGO) constant false alarm rate (CFAR) scheme with binary integration for M non-coherent sweeps in Weibull background was investigated for homogeneous and non-homogeneous backgrounds, with an assumption of known shape parameter. This kind of processing is based on the fact that the clutter can be segmented in regions in many real radar scenarios where a timevarying two-parameter distribution function family can be fitted, but the clutter power may vary locally inside the region. Under the assumption of known shape parameter, the authors examined the changes of the false alarm rate and detection probability of the OSGO-CFAR with binary integration when the shape parameter differs from the nominal one, and compared them to those of the OSGO-CFAR with single pulse processing. The authors have derived analytic expressions of the detection probability and false alarm rate during clutter power transitions for the OSGO-CFAR with binary integration in Weibull background. It is shown that the OSGO-CFAR with binary integration can not only improve the detection performance significantly, but it also control the rise of the false alarm rate at clutter edges more effectively compared to the OSGO-CFAR with single pulse processing. Moreover, it exhibits a good immunity to the variation of the shape parameter.     

Field programmable gate array-based design and realisation of automatic censored cell averaging constant false alarm rate detector based on ordered data variability

The design and field programmable gate array (FPGA)-based realisation of automatic censored cell averaging (ACCA) constant false alarm rate (CFAR) detector based on ordered data variability (ODV) is discussed here. The ACCA-ODV CFAR algorithm has been recently proposed in the literature for detecting radar target in non-homogeneous background environments. The ACCA-ODV detector estimates the unknown background level by dynamically selecting a suitable set of ranked cells and doing successive hypothesis tests. The proposed detector does not require any prior information about the background environment. It uses the variability index statistic as a shape parameter to accept or reject the ordered cells under investigation. Recent advances in FPGA technology and availability of sophisticated design tools have made it possible to realise the computation intensive ACCA-ODV detector in hardware, in a cost-effective way. The architecture is modular and has been implemented and tested on an Altera Stratix II FPGA using Quartus II software. The post place and route result show that the proposed design can operate at 100 MHz, the maximum clock frequency of the prototyping board and for this frequency the total processing time required to perform a single run is 0.21 μs. This amounts to a speedup for the FPGA-based hardware implementation by a factor of ~110 as compared to software-based implementation, which takes 23 μs to perform the same operation.     

Application of the radon transform to detect small-targets in sea clutter

The authors present a novel and heuristic approach for the detection of low radar cross-section targets in high-resolution sea clutter. The proposed technique is based on the application of the Radon transform to range?time matrices formed by column-wise storage of consecutive range profiles. The objective of this paper is 2-fold: to analyse the effect of the transform on real high-resolution sea clutter and to describe a detection scheme based on the insight obtained. The proposed technique emulates the behaviour of traditional motion target detection algorithms without the need for reliable Doppler information. It also constitutes a powerful non-coherent integration strategy of the target?s energy along its specific path on the range?time plot. The performance of the detection technique has been tested against real high-resolution sea clutter data, acquired at the south coast of Spain with an in-house developed continuous wave linear frequency modulated millimetre-wave radar system. Monte Carlo simulations show a significant improvement over the conventional cell averaging constant false alarm rate schemes.     

天基多载频稀疏阵STAP方法的幅相误差影响

地面动目标检测 (GMTI) 是天基分布式雷达的重要应用之一, 采用多载频模式可有效减少孔径稀疏引起的动目标检测盲区, 提高 GMTI 性能. 针对多载频天基稀疏阵雷达的空时自适应处理 (STAP) 方法, 基于多通道幅相误差模型, 推导了多载频模式下存在幅相误差的杂波协方差矩阵表达式. 通过仿真分析了幅相误差对多载频稀疏阵最优 STAP 方法的影响.     

Network Intrusion Detection Using CFAR Abrupt-Change Detectors

In this paper, the constant false alarm rate (CFAR) detectors are proposed for network intrusion detection. By using an autoregressive system to model the network traffic, predictor error is shown to closely follow a Gaussian distribution. CFAR detector approaches are then developed on the prediction error distribution. In the present study, we consider the optimal CFAR, the cell-averaging CFAR, and the order statistics CFAR. The use of these CFAR techniques can significantly improve the detection performance. In addition, we propose the use of fusion of these CFAR detectors by using Dempster-Shafer and Bayesian techniques. Computer simulations based on the DARPA traffic data show that the proposed approach achieves higher detection probabilities than the conventional detection method. Even under different types of attacks, the intrusion detection performances based on the proposed CFAR detectors shows consistent improvement.     

Extraction of mixed-order multicomponent ship target signals from broadened sea clutter in bistatic shipborne surface wave radar

A dynamic geometry model was built to describe the Doppler-broadening characteristics of the first-order Bragg lines for bistatic shipborne surface wave radar. They are time-varying because the Doppler frequency shifts of sea echoes are simultaneously modulated by the velocity components projected from the unavoidably different motions of both platforms, which is more complex than its counterpart in the monostatic mode. The geometrical relation is used to obtain the received signal model: strong first-order sea clutter interferences and submerged ship targets with constant and non-constant speeds are considered as mixed-order multicomponent polynomial-phase signals (mc-PPSs) and both second-order sea clutter continuum and atmospheric noise as additive noise. Then, a scheme based on the product high-order ambiguity function is proposed to extract the targets; it is a recursive procedure in which the first-order sea clutter is removed by an existing time-space cascaded filtering method. Monte Carlo simulations show the validity and efficiency of the proposed scheme.     

Analysis of an automatic sinusoidal detector with FFT and cell‐averaging processor

Abstract

A sinusoidal detector with adaptive thresholding CFAR (constant‐false‐alarm‐rate) processor operating in noise of changing statistics is analyzed for some very general situations. The detector contains FFT and a cell‐averaging processor, which can be easily implemented for real time applications, such as in pulse doppler radar. For signals in stationary noise in particular, the second‐order statistics of the FFT‐based periodogram of the windowed data are derived. In the AWGN case, this detector possesses the desired CFAR characteristics. For Gaussian colored noise, the detector performance is derived analytically with certain reasonable approximations. It is shown from some numerical examples that in this case the variation of the false alarm probability with respect to the unknown sinusoidal frequency and noise spectrum is not significant, which reveals the property of robustness. Moreover, the detection probability is satisfactory for most cases.     

复杂非均匀背景下的鲁棒声呐恒虚警检测算法

针对复杂非均匀水下环境中目标检测问题,提出了一种基于背景统计特性的鲁棒声呐恒虚警(Background Statistical Characteristics based Robust Sonar Target Constant False Alarm Ratio,BSCR-CFAR)检测算法。该算法将自动删除平均级检测(Automatic Censored Mean Level Detection,ACMLD)和排序统计恒虚警(Order Statistic CFAR,OS-CFAR)检测算法引入可变指数恒虚警(Variability Index CFAR,VI-CFAR)检测算法中,并通过评估背景特性,自适应选择更匹配的CFAR检测方法。仿真和声呐实测数据分析结果表明,相比较单元平均恒虚警(Cell Average CFAR,CA-CFAR)、单元平均选大恒虚警(Greatest of CFAR,GO-CFAR)、单元平均选小恒虚警(Smallest of CFAR,SO-CFAR)和OS-CFAR、VI-CFAR等检测算法,该算法在混响边缘、混响区、单/多强离散干扰等典型非均匀背景下的恒虚警检测保持了良好的鲁棒性。     

Azimuth-invariant bistatic multichannel synthetic aperture radar for moving target detection and location

Ground moving target indication (GMTI) is one of the most important applications of the bistatic synthetic aperture radar (SAR) system as well as the monostatic system. An algorithm for moving target detection and location is presented with an azimuth-invariant bistatic multichannel SAR, which consists of one transmitter (channel) and multireceivers (multichannel). The algorithm is based on the discussion of the particularities of the bistatic SAR configuration including coherence improvement and clutter characteristics. Then, the corresponding compensating methods including two-dimensional range-azimuth prefiltering and bistatic differential range correction are proposed to solve these particularities. It is shown that using the compensating methods, the stationary clutter can be suppressed and the moving parameters of ground targets can be estimated accurately. Finally, simulation results demonstrate the effectiveness of the proposed algorithm.     

Kernel wavelet-Reed-Xiaoli: an anomaly detection for forward-looking infrared imagery

This paper describes a new kernel wavelet-based anomaly detection technique for long-wave (LW) forward-looking infrared imagery. The proposed approach called kernel wavelet-Reed-Xiaoli (wavelet-RX) algorithm is essentially an extension of the wavelet-RX algorithm (combination of wavelet transform and RX anomaly detector) to a high-dimensional feature space (possibly infinite) via a certain nonlinear mapping function of the input data. The wavelet-RX algorithm in this high-dimensional feature space can easily be implemented in terms of kernels that implicitly compute dot products in the feature space (kernelizing the wavelet-RX algorithm). In the proposed kernel wavelet-RX algorithm, a two-dimensional wavelet transform is first applied to decompose the input image into uniform subbands. A number of significant subbands (high-energy subbands) are concatenated together to form a subband-image cube. The kernel RX algorithm is then applied to this subband-image cube. Experimental results are presented for the proposed kernel wavelet-RX, wavelet-RX, and the classical constant false alarm rate (CFAR) algorithm for detecting anomalies (targets) in a large database of LW imagery. The receiver operating characteristic plots show that the proposed kernel wavelet-RX algorithm outperforms the wavelet-RX as well as the classical CFAR detector.     

Bistatic clutter analysis and range ambiguity resolving for space time adaptive processing

The clutter characteristics of bistatic airborne radar are more complex than those of monostatic airborne radar. The clutter spectra not only vary severely with range, but also vary with bistatic configuration. The problem of range dependence is more serious in monostatic airborne radar. In this paper, the geometry of arbitrary bistatic airborne radar configuration is firstly analysed, and a formula for Doppler frequency calculation with the variables of azimuth angle and bistatic range is deduced, which is an efficient tool for bistatic clutter analysis. Because of the severe clutter range dependence, the processing of compensation is indispensable in space time adaptive processing (STAP). However, when range ambiguity occurs, the compensation is difficult to be applied to each clutter range cell. To solve this problem, a range ambiguity resolving approach is further proposed by utilising azimuth elements in phased array. Because this approach will result in spatial degrees of freedom (DOF) loss, the overlapped subarray processing is introduced in order obtain enough spatial DOF for STAP. By doing so, the compensation for mitigating range dependence can be applied effectively to bistatic clutter.     

Ionospheric clutter mitigation using one-dimensional or two-dimensional wavelet processing

Ionospheric clutter mitigation is an important issue for high-frequency surface wave radar (HFSWR) signal processing. Clutter results from a sky wave propagation mode, which is backscattered by ionospheric ionisation irregularities. The random behaviour and the high strength of clutter signals can strongly limit the HFSWR detection capabilities. Here, an ionospheric clutter mitigation processing using wavelets is described. This new approach is founded on the ability of wavelets to separate signals having different variation scales or different directions of variations. The results obtained on real clutter signals with simulated targets are reported. Using the proposed method, one can expect, at mid-latitude, an improvement of the target-toclutter ratio of 20?30 dB.     

星载稀疏阵扫描模式干涉雷达动目标检测研究

地面动目标检测(GMTI)是星载分布式雷达的重要应用之一,利用星载稀疏阵可增加系统虚拟孔径,以改善动目标检测性能.扫描模式干涉雷达(Scanning Pattern Interferometric Radar,简称SPIR)是一种雷达天线阵波束扫描的新型GMTI雷达,用点扩展函数(Point Spread Function,简称PSF)与扫描结果进行解卷积,就能恢复出地物后向散射系数,然后利用杂波位置来检测动目标.本文分析了SPIR方法的基本原理,并对有不同位置误差的阵列进行了SPIR仿真,比较仿真结果发现,在一定误差范围内,准确测量孔径实际位置比精确控制孔径位置更重要.     

Two-dimensional pulse-to-pulse canceller of ground clutter in airborne radar

It is well known that in the airborne radar, the location of the ground clutter spectrum in the angle- Doppler space is dependent mainly on the platform velocity and radar parameters. The authors propose a two-dimensional pulse-to-pulse canceller (TDPC) that can make full use of such prior information. The more detailed formulations of the ground clutter model and the signal model are given in a matrix?vector form. The least-squares-typical cost function associated with the filter coefficient matrix of the TDPC is established on the basis of the ground clutter model and the signal model. Like the classical displaced phase centre antenna (DPCA) processing, the proposed TDPC is also a spatial-temporal suppressor of ground clutter and can decrease the ground clutter signals, even though the DPCA condition is not satisfied. The proposed TDPC can also be used as an efficient pre-filtering tool before the conventional moving target indication (MTI) processing and the classical adaptive processing. Moreover, if only the TDPC plus the conventional MTI is used, it takes less computational time than the adaptive canceller. Experimental results show that the proposed TDPC has the satisfactory ground clutter suppression capability by using both simulated data and measured data.     

Target-adaptive polarimetric synthetic aperture radar target discrimination using maximum average correlation height filters

We report the development of a technique for adaptive selection of polarization ellipse tilt and ellipticity angles such that the target separation from clutter is maximized. From the radar scattering matrix [S] and its complex components, in phase and quadrature phase, the elements of the Mueller matrix are obtained. Then, by means of polarization synthesis, the radar cross section of the radar scatters are obtained at different transmitting and receiving polarization states. By designing a maximum average correlation height filter, we derive a target versus clutter distance measure as a function of four transmit and receive polarization state angles. The results of applying this method on real synthetic aperture radar imagery indicate a set of four transmit and receive angles that lead to maximum target versus clutter discrimination. These optimum angles are different for different targets. Hence, by adaptive control of the state of polarization of polarimetric radar, one can noticeably improve the discrimination of targets from clutter.