Overall Detection Probability for Fluctuating and Nonfluctuating Target Models

The power selection of a search radar is best obtained in the framework of the overall detection probability concept. This concept is here applied to fluctuating target models for single- and multiple-scan detection. The approach combines the pulse train statistics over the detection interval to the mean target statistics over the search region and directly relates the overall detection probability POD to a single system parameter ?0, proportional to the transmitted power.     

Systematic Approach for Classification of Modern Surveillance Radar Systems

Inherent search volume is proposed as a tool for systematic comparison of modern phased-array surveillance radar systems. The advantage of the inherent search volume over the existing approaches based on single-scan and cumulative probability of detection is that the inherent search volume depends only on the unadjustable parameters of the radar. A comparison algorithm based on the inherent search volume criterion is presented.     

Moving target detection via airborne HRR phased array radar

We study moving target detection in the presence of temporally and spatially correlated ground clutter for airborne high range resolution (HRR) phased array radar. We divide the HRR range profiles into large range segments to avoid the range migration problems that occur in the HRR radar data. Since each range segment contains a sequence of HRR range bins, no information is lost due to the division and hence no loss of resolution occurs. We show how to use a vector autoregressive (VAR) filtering technique to suppress the ground clutter. Then a moving target detector based on a generalized likelihood ratio test (GLRT) detection strategy is derived. The detection threshold is determined according to the desired false alarm rate, which is made possible via an asymptotic statistical analysis. After the target Doppler frequency and spatial signature vectors are estimated from the VAR-filtered data as if a target were present, a simple detection variable is computed and compared with the detection threshold to render a decision on the presence of a target. Numerical results are provided to demonstrate the performance of the proposed moving target detection algorithm     

New Clutter Rejection Waveforms for Long-Range Radar

A frequent compromise in the design of long-range search radars has to be made between the maximum unambiguous detection range and the achievable coherent clutter rejection performance. A new class of waveforms is introduced which offers the designer a previously unavailable flexibility in arriving at radar designs with improved clutter rejection without seriously affecting the maximum unambiguous search range. The key to these new waveforms is the recognition that a class of useful N-pulse, nonrecursive, moving target indicator (MTI) canceler designs exists which only requires the radar to transmit a total of N -1 (nonuniformly spaced) pulses.     

Performance Data for a Double-Threshold Detection Radar

A problem f requently encountered by radar systems analysts is the evaluation of the "double-threshold" or M out of N detection process. Detection probabilities of this process are binomially distributed, making it difficult to obtain exact results for large values of the number of samples and for low probabilities of false alarm. In this paper, the M out of N detection algorithm is defined and detection performance is calculated for the special cases of the nonfluctuating target and Swerling cases I and 11 for false alarm probabilities of 106, 10-8 and 10-10.     

Improved SAR target detection via extended fractal features

The utility of the extended fractal (EF) feature is evaluated for the enhancement of the focus of attention (FOA) stage of a synthetic aperture radar (SAR) automatic target recognition (ATR) system. Unlike more traditional SAR detection features that distinguish target pixels from the background only on the basis of contrast, the EF feature is sensitive to both the contrast and size of objects. Furthermore, the structure for the EF feature computational algorithm lends itself to very fast implementation, and it can be shown that the new feature has a CFAR-like (constant false alarm rate) property. We demonstrate the improved performance using the new feature by testing a number of different detection approaches over two databases of SAR imagery     

Spatial adaptive subspace detection in OTH radar

The work presented here addresses the problem of target detection against spatially structured interference composed of jamming plus noise, where for practical reasons, the received target wavefront may also deviate from the traditional plane wave model. This detection problem arises in over-the-horizon (OTH) radar systems where spatially distributed targets often compete for detection against directional interference that is spread over the entire range-Doppler search space. Conventional detection processing schemes are compared with a recently proposed adaptive subspace detector (ASD) that takes both the spatial structure of the interference and the possibility of target wavefront distortions into account. Experimental array data recorded by the Jindalee sky-wave and Iluka surface-wave OTH radar systems, located in central and northern Australia respectively, is used to evaluate detection performance.     

Target State Estimation in a Multitarget Environment Using Multiple Sensors

An approach for target detection/state estimation that views theproblem as one of a finite state search over the target parameterspace is presented. This approach allows for a natural way toassociate different types of measurements, such as frequency andcoherence from multiple sensors, and also for dealing with multipletargets, dropouts, and clutter. We describe our model and present acomputationally efficient search algorithm for target detection andtarget state estimation in a multitarget environment based on thismodel. The results of a two-sensor, multitarget computer simulationare discussed.     

探测点序列的最优化与简化计算方法

在搜索状态建模和求解一阶搜索状态方程的特征迹线解的基础上,建立了对随机运动进行离散时间探测的发现概率最优控制模型,结合动态规划原理给出一种最优探测点序列的逼近算法,并给出了短时计算的算法简化形式。在满足一阶搜索状态方程的随机恒速目标条件以及有限指数探测函数条件下,将给出的算法及其简化形式应用到算例。算例表明,当随机恒速运动目标初始位置和速度均服从圆正态分布时,该算法及其简化形式均能够由任意给定的初始探测点序列优化收敛到满足精度要求的最优探测点序列。     

基于改进型CFAR的SAR图像目标检测算法

针对传统的双参数恒虚警率(Constant False Alarm Rate,CFAR)算法存在的虚警率高、实现过程繁琐、算法执行效率低等问题,提出了一种改进型的CFAR检测算法。该算法根据SAR图像的统计直方图,对可疑的目标像素进行预筛选,再用2个滑动窗口对像素进行判别。改进型的CFAR检测算法简化了原检测算法的结构,降低了检测结果的虚警率,提高了算法的计算效率,并在国际公开的雷达数据集上进行软件与DSP硬件的应用验证,测试表明该算法的有效性。     

PAR辅助光电设备的飞机着陆监测与评估系统设计

针对数据链在着陆阶段存在盲区和塔台无法获得着陆飞机实时姿态、接地参数等问题,提出利用多功能光电跟踪技术建立飞机着陆实时监测与评估系统,设计出飞机着陆监测与评估系统的技术方案。由于光电跟踪平台的视场有界,无法保证着陆飞机准确进入光电设备视场,采用精密进场雷达（PAR）牵引光电转台对准即将着陆飞机的方式,辅助光电设备捕获目标飞机,再经过图像检测算法处理,检测出目标飞机,进而转入跟踪锁定,计算出最终下降阶段目标飞机的姿态和偏航信息。详细阐述了该系统的PAR初始化光电设备的方法、步骤。该系统在飞机下降阶段辅助塔台指挥,实现整个着陆过程的监视与评估,满足未来作战飞机精密进近引导的着陆保障和训练要求,具有很高的实用价值。     

An intelligent target detection method of UAV swarms based on improved KM algorithm

Complete and efficient detection of unknown targets is the most popular application of UAV swarms. Under most situations, targets have directional characteristics so that they can only be successfully detected within specific angles. In such cases, how to coordinate UAVs and allocate optimal paths for them to efficiently detect all the targets is the primary issue to be solved. In this paper, an intelligent target detection method is proposed for UAV swarms to achieve real-time detection requirements. First, a target-feature-information-based disintegration method is built up to divide the search space into a set of cubes. Theoretically, when the cubes are traversed, all the targets can be detected. Then, a Kuhn-Munkres (KM)-algorithm-based path planning method is proposed for UAVs to traverse the cubes. Finally, to further improve search efficiency, a 3D real-time probability map is established over the search space which estimates the possibility of detecting new targets at each point. This map is adopted to modify the weights in KM algorithm, thereby optimizing the UAVs’ paths during the search process. Simulation results show that with the proposed method, all targets, with detection angle limitations, can be found by UAVs. Moreover, by implementing the 3D probability map, the search efficiency is improved by 23.4%–78.1%.     

Optimum detection and location estimation of target lines in the range-time space of a search radar

The average likelihood ratio detector is derived as the optimum detector for detecting a target line with unknown normal parameters in the range-time data space of a search radar, which is corrupted by Gaussian noise. The receiver operation characteristics of this optimum detector is derived to evaluate its performance improvement in comparison with the Hough detector, which uses the return signal of several successive scans to achieve a non-coherent integration improvement and get a better performance than the conventional detector. This comparison, which is done through analytic derivations and also through simulation results, shows that the average likelihood ratio detector has a better performance for different SNR values. This result is justified by showing the disadvantages of the Hough method, which are eliminated by the optimum detector. To have an estimate for the location of the detected target line in the optimum detection method as the Hough method, which detects and localizes the target lines simultaneously, we present the maximum a posteriori probability estimator. The estimation performance of the two methods is then compared and it is shown that the maximum a posteriori probability estimator localizes the detected target lines with a better performance in comparison with the Hough method.     

A new CFAR sidelobe canceler algorithm for radar

Signal or target detection is sometimes complicated by the presence of strong interference. When this interference occurs mainly in the sidelobes of the antenna pattern, a solution to this problem is realized through a sidelobe canceler (SLC) implementation. Since the false-alarm probability is a system parameter of special importance in radar, an interference-canceling technique for radar application should maintain the false-alarm probability constant over a wide range of incident interference power. With the requirements of sidelobe interference cancellation and constant false alarm rate (CFAR), a new algorithm for radar detection in the presence of sidelobe interference is developed from the generalized likelihood ratio test of Neyman-Pearson. In this development, the received interference is modeled as a nonstationary but slowly varying Gaussian random process. Cancellation of the sidelobe interference is based upon a `synchronous' estimate of the spatial covariance of the interference for the range gate being tested. This algorithm provides a fixed false-alarm rate and a fixed threshold which depend only upon the parameters of the algorithm     

Beam overlap impact on phased-array target detection

The impact of beam overlap on the probability of detection during a single scan of a phased-array volumetric scan radar is examined. Rectangular and triangular beam packing arrangements are considered. Beam positions near the beam most centered on the target are allowed to contribute to the detection process. The treatment of the impact of beam overlap on target detection for a phased array is consistent with the results that would be achieved by proper use of the search radar range equation     

Optimization of multiframe target detection schemes

We optimize the performance of multiframe target detection (MFTD) schemes under extended Neyman-Pearson (NP) criteria. Beyond the per-track detection performance for a specific target path in conventional MFTD studies, we optimize the overall detection performance which is averaged over all the potential target paths. It is shown that the overall MFTD performance is limited by the mobility of a target and also that optimality of MFTD performance depends on how fully one ran exploit the information about the target dynamics. We assume a single target situation and then present systematic optimization by formulating the MFTD problems as binary composite hypotheses testing problems. The resulting optimal solutions suggest computationally efficient implementation algorithms which are similar to the Viterbi algorithm for trellis search. The optimal performances for some typical types of target dynamics are evaluated via Monte-Carlo simulation     

Evaluating a multiple-hypothesis multitarget tracking algorithm

The performance evaluation of multiple-hypothesis, multitarget tracking algorithm is presented. We are primarily interested in target-detection/track-initiation capabilities as measures of performance. Through Monte Carlo simulations, a multiple-hypothesis tracking algorithm was evaluated in terms of 1) probability of establishing a track from target returns and 2) false track density. A radar was chosen as the sensor, and a general multiple-hypothesis, multitarget tracking algorithm was used in the Monte Carlo simulations. The simulation results predict the probability of establishing a track from returns of a target as well as the false track density per scan volume per unit time. The effects of the target radar cross section and the radar power, measured through the mean signal-to-noise ratio (SNR) were studied, as were the effects of detection threshold and track quality threshold. Computational requirements were also investigated     

Prescreening during image formation for ultrawideband radar

Standard radar image formation techniques waste computational resources by full resolving all areas of the scene, even regions of benign clutter. We introduce a multiscale prescreener algorithm that runs as part of the image formation processing step for ultrawideband (UWB) synthetic aperture radar (SAR) systems. The prescreener processes intermediate radar data generated by a quadtree backprojection image former. As the quadtree algorithm iterates, it is resolving increasingly finer subpatches of the scene. After each quadtree stage, the prescreener makes an estimate of the signal-to-background ratio of each subpatch and applies a constant false alarm rate (CFAR) detector to decide which ones might contain a target of interest. Whenever the prescreener determines that a subpatch is not near a detection, it cues the image former to terminate further processing of that subpatch. Using a small database of UWB radar field data, we demonstrate that the prescreener is able to decrease the overall computational load of the image formation process. We also show that the new multiscale prescreener method produces fewer false alarms than the conventional two-parameter CFAR prescreener applied to the completely formed image     

基于傅里叶变换的航迹对准关联算法

研究了在组网雷达存在系统误差情况下的目标航迹关联问题,理论分析了雷达系统误差对目标航迹的影响,并将该影响表示为目标航迹的旋转和平移量。在此基础上,提出了一种基于傅里叶变换的系统误差配准前航迹对准关联算法,该算法将组网雷达的航迹数据看做为一种整体信息,采用傅里叶变换理论来估计和补偿组网雷达目标航迹数据到融合中心航迹数据的相对旋转量和平移量,将雷达网中雷达上报的目标航迹数据对准到融合中心,从而不依赖于估计雷达网系统误差,实现了误差配准前的航迹准确关联,能够为后端的系统误差配准提供可靠的关联目标航迹数据。     

联合截获威胁下的雷达射频隐身目标搜索算法

针对基于射频(RF)隐身需求的机载雷达目标搜索问题进行了研究。通过分析实际作战中射频辐射面临的截获威胁,提出了一种基于联合截获威胁的射频隐身性能表征方法,并给出了具体的值估算方法;对机载雷达搜索任务中辐射参数的优化问题进行了建模,并采用优化算法对目标函数进行求解。通过分析典型情景下解集的分布特点,给出了从最优解集中选取最终解的方法。结果表明,提出的射频隐身性能表征方法能更好地反映截获实现过程的多域需求,提出的雷达搜索方法能够在保证探测性能的同时,提高射频隐身性能和搜索速度,能够为相控阵雷达搜索任务中参数的优化控制提供方法和依据。