Track-before-detect algorithm for maneuvering infrared weak multiple targets via particle filter

We present a particle filter （PF）-based algorithm to detect and track maneuvering infrared weak multiple targets at different signal-to-noise ratios for the scenes with the multiple targets number unknown and vary- ing. A detecting filter and a tracking filter based on sequential likelihood ratio （LR） testing with fixed sample size are designed, respectively, for capturing new target and tracking confirmed targets. The algorithm is optimized with selectively particles sampling and adaptive process noise. Targets birth and death time are accurately estimated according to the change degree of the LR along with the corresponding state amended through PF backward recursion. Simulation results show that it is positive to detect and track maneuvering infrared weak multiple targets with the appearance and disappearance of more than one, which also achieves a significant improvement in state estimation especially for the time targets which appear and disappear.     

基于运动方向估计的管道滤波算法

管道滤波算法提出了从时域角度解决弱小目标检测问题的思路,对于红外强起伏天空背景中弱点目标的检测问题,管道内强噪音的干扰以及低信噪比的条件会导致检测概率降低的情况出现.本文提出了一种运动方向估计的管道滤波算法,分析了红外弱点目标的运动特性,依据弱点目标在相邻帧间位置具有连贯性的特征,建立了弱点目标的运动方向估计模型.在模型中利用弱点目标逐帧检测的先验位置信息,估计弱点目标的运动方向和轨迹,根据估计结果去除管道内噪音对弱点目标的干扰.仿真结果表明,该方法能够很好地抑制管道内噪音的影响,提高弱点目标的检测概率,增强弱点目标抗管道内噪音干扰的能力.     

基于粒子滤波的运动目标光电定位仿真研究

运动目标的光电定位不能像静止目标那样简单做均值滤波,鉴于此,引入粒子滤波算法,它不仅可以应用于线性系统,而且还适用于非线性系统。结合光电定位需求,详细推导了计算公式及初值和参数选取公式,对只含测量噪声以及含有测量和运动噪声等的海面运动目标光电无源定位算法进行了仿真计算,验证了算法的有效性,讨论了噪声强度对滤波效果的影响,滤波参数选择对滤波效果的影响,目标运动方式对滤波跟随性的影响,重采样算法对滤波效果的影响等。所得结论为:粒子滤波可用于运动目标光电定位过程,可有效降低定位误差;粒子滤波算法具有较强鲁棒性,适用于噪声较大、目标运动形态变化大等情况。     

基于形态学带通滤波和尺度空间理论的红外弱小目标检测

针对复杂背景下的红外弱小目标检测问题,提出了一种基于形态学带通滤波和尺度空间理论的红外弱小目标检测算法。采用形态学带通滤波对红外图像进行预处理,得到红外弱小目标的潜在区域;利用高斯差分算子获得预处理后的红外图像的尺度空间,并通过尺度空间的极大值检测获得候选目标的位置和尺度;通过对候选目标的信杂比进行阈值化实现红外弱小目标的检测。实验结果和现有方法的对比证明了算法的有效性和稳健性。     

Modified particle filter-based infrared pedestrian tracking

Tracking infrared pedestrian targets is a crucial part in video surveillance. Many factors make this problem decidedly non-linear and non-Gaussian, and the appropriate solution at present is based on the particle filter technique which is powerful and simple to implement. But in many cases, the traditional particle filter tracking algorithm fails to track the targets robustly and accurately. To solve these problems, a modified particle filter algorithm that combines intensity and edge cues is proposed. The algorithm firstly extracts the intensity cue and edge cue of the target based on the visual models which are originally learnt from the first frame and will be updated during the tracking process according to an automatic model updating strategy. Secondly, these two cues are combined into the particle filter framework by an adaptive integration scheme. Furthermore, its performance is evaluated with real-world infrared pedestrian sequences and extensive experimental results show that the presented method can track the infrared pedestrian more effectively and reliably than the traditional particle filter algorithm.     

4×2×3阵列式放大器参数测量系统优化设计

采用软边光阑和多级空间滤波器组合技术实现了光束的空间整形和等像面传输，利用Fresnel光束传输计算程序对4×2×3阵列式放大器参数测量系统进行了优化设计，分析了空间滤波器中小孔尺寸对光束波面传输的影响，并对优化设计结果进行了分析和讨论，所用方法和所得结论对高功率固体激光放大系统的设计有应用意义。     

Target detection beneath foliage using polarimetric synthetic aperture radar interferometry

Abstract

In this paper, we demonstrate how the new technology of polarimetric synthetic aperture radar (SAR) interferometry can be used to enhance the detection of targets hidden beneath foliage. The key idea is to note that for random volume scattering, the interferometric coherence is invariant to changes in wave polarization. On the other hand, in the presence of a target the coherence changes with polarization. We show that under general symmetry constraints this change is linear in the complex coherence plane. These observations can be used to devise a filter to suppress the returns from foliage clutter while maintaining the signal from hidden targets. We illustrate the algorithm by applying it to coherent L-band SAR simulations of corner reflectors hidden in a forest. The simulations are performed using a voxel-based vector wave propagation and scattering code coupled to detailed structural models of tree architecture. In this way, the spatial statistics and radar signal fluctuations closely match those observed for natural terrain. We demonstrate significant improvements in the detection of hidden targets, which suggests that this technology has great potential for future foliage penetration (FOPEN) applications.     

Target detection beneath foliage using polarimetric synthetic aperture radar interferometry

In this paper, we demonstrate how the new technology of polarimetric synthetic aperture radar (SAR) interferometry can be used to enhance the detection of targets hidden beneath foliage. The key idea is to note that for random volume scattering, the interferometric coherence is invariant to changes in wave polarization. On the other hand, in the presence of a target the coherence changes with polarization. We show that under general symmetry constraints this change is linear in the complex coherence plane. These observations can be used to devise a filter to suppress the returns from foliage clutter while maintaining the signal from hidden targets. We illustrate the algorithm by applying it to coherent L-band SAR simulations of corner reflectors hidden in a forest. The simulations are performed using a voxel-based vector wave propagation and scattering code coupled to detailed structural models of tree architecture. In this way, the spatial statistics and radar signal fluctuations closely match those observed for natural terrain. We demonstrate significant improvements in the detection of hidden targets, which suggests that this technology has great potential for future foliage penetration (FOPEN) applications.     

无源声呐场景中使用辅助粒子滤波的邻近目标检测前跟踪方法

针对无源声呐多目标方位跟踪问题,研究了一种基于粒子滤波的检测前跟踪方法,关注于改善邻近目标和机动目标的跟踪性能。首先,提出了一种考虑了邻近目标影响的似然函数;其次,采用辅助变量利用量测信息优化粒子采样,当算法运动模型与目标实际运动状态失配时,这种策略具有很大优势。结合以上两点,提出了一种检测前跟踪算法,该算法将邻近目标划分为一组,使用邻近目标的预测状态计算目标的似然,计算效率较高。利用仿真生成的数据和海上采集的实际数据分别验证了该算法的性能,并与其他多目标粒子滤波检测前跟踪算法进行比较,证明了该算法具有良好的跟踪性能。在目标邻近和目标机动的情况下,该算法的优势更加明显。     

基于稀疏信道重建技术的相邻多目标序贯检测算法研究

为进行强目标相关旁瓣干扰下的相邻弱目标检测,采用稀疏重建理论进行多目标方位估计。高信噪比情况下,由方位估计结果即可完成目标检测;对于低信噪比弱目标回波,为提高系统检测能力,结合方位估计结果,提出了两种检测算法,前者类似于传统CLEAN算法,从能量角度进行目标检测;后者则利用相关函数能量集中于主瓣的特点,通过计算将目标方位估计结果中非零元素置零前后匹配滤波峰值的差值,采用Page-test序贯检测器进行多目标检测。仿真和试验数据处理结果表明,相同检测概率下,第二种方法具有更加优良的弱目标检测性能。      

Detection of infrared small target based on fusion of multi-filters北大核心CSCD

Aiming at solving accuracy problem of infrared small target detection in sky and ocean background scenarios of infrared image sequences, a novel infrared small target detection based on multi-filters algorithm fusion method is presented in this paper. Firstly infrared small target and imaging, time and space characteristics of the corresponding background noise are analyzed. Tophat algorithm with improved Robinson guard filter are then integrated to highlight target and suppress clutter background by using infrared small target imaging features. Adaptive threshold segmentation is used to extract candidate targets, while Unger smoothing filter and multi-objects association filter are used to eliminate random noise and false targets in the candidate targets. Multiple experiments of infrared small target image sequences are implemented, and experimental results show that proposed method can detect infrared small targets at 99% detection rate with high reliability and good real-time performance. © 2017, Editorial Board, Journal of Applied Optics. All right reserved.     

云层背景目标识别的匹配滤波器设计

提出一种利用最大平均相关高度(MACH)算法识别复杂云层背景目标的改进滤波器设计方法。在MACH滤波器设计中,通过对云层背景功率谱的统计特性分析,数据拟合得到云层背景功率谱的分布函数,用以代替传统的白噪声模型;提取飞行目标的姿态变化图像,并作阈值化处理,得到训练样本。对不同云层背景和姿态变化目标的相关识别结果表明:改进滤波器的平均峰值相关能量比为0.71%,峰值鉴别率为0.92,可以有效抑制云层背景的干扰,对姿态变化目标识别的鲁棒性较好。     

Trading detection for resolution in active sonar receivers

This paper proposes an active sonar receivers that offers a smooth trade-off between detection and resolution. A matched filter is the optimal detector of known signals in white Gaussian noise but may fail to resolve the targets if the time separation of targets is less than the mainlobe width of the autocorrelation function of the transmitted signal. An inverse filter achieves optimal resolution performance for multiple targets in the absence of noise, but amplifies the noise outside the signal bandwidth in a manner that makes it impractical in many realistic scenarios. The proposed active sonar receiver, the variable resolution and detection receiver (VRDR) combines the matched and inverse filter properties to achieve a smooth trade-off between detection and resolution. Simulated receiver operating characteristics demonstrate that for a range of dipole sonar targets, the performance of the VRDR is superior to the matched and inverse filter, as well as another previously proposed bandlimited inverse filter.     

Using filtering effects to identify objects

Reflecting signals off of targets is a method widely used to locate objects, but the reflected signal also contains information that can be used to identify the object. In radar or sonar, the signal amplitudes used are small enough that only linear effects are present, so we can consider the effect of the target on the signal as a linear filter. Using the known effects of linear filters on chaotic signals, we can create a reference that allows us to match a particular target to a particular reflected signal. Furthermore, if some parts of this "filter" vary only slowly as the aspect angle of the object changes, we can produce a reference that averages out the parts that are highly angle dependent so that one reference can be used to identify the target over a range of angles.     

一种新的相位编码幅值调节联合变换相关器

给出了一种对经典联合变换相关器进行相位编码和幅值调节的新方法,使联合变换相关器具有优化的相关输出信号和很强的抗干扰能力.在相位编码幅值调节联合变换相关器中,输入的待识别信号首先通过相位模板进行相位编码,然后对联合功率谱进行幅值调节滤波.在进行幅值调节滤波时采用了增强型幅值调节滤波器,其调节因子可根据输信号的噪音干扰情况进行调节变化.相位编码幅值调节有效地祛除了多目标识别联合变换相关器的冗余信号,可广泛的应用于多目标识别.     

A tracking filter method of active sonar subject to unknown target maneuver

A tracking filter algorithm based on the maneuvering detection delay is presented in order to solve the fuzzy problem of target maneuver decision introduced by the measure?ment errors of active sonar. When the maneuvering detection is unclear, two target moving hypotheses, the uniform and the maneuver, derived from the method of multiple hypothesis tracking, are generated to delay the final decision time. Then the hypothesis test statistics is constructed by using the residual sequence. The active sonar?s tracking ability of unknown prior information targets is improved due to the modified sequential probability ratio test and the integration of the advantages of strong tracking filter and the Kalman filter. Simulation results show that the algorithm is able to not only track the uniform targets accurately, but also track the maneuvering targets steadily. The effectiveness of the algorithm for real underwater acoustic targets is further verified by the sea trial data processing results.     

Passive Tracking of Multiple Underwater Targets in Incomplete Detection and Clutter Environment

A major advantage of the use of passive sonar in the tracking multiple underwater targets is that they can be kept covert, which reduces the risk of being attacked. However, the nonlinearity of the passive Doppler and bearing measurements, the range unobservability problem, and the complexity of data association between measurements and targets make the problem of underwater passive multiple target tracking challenging. To deal with these problems, the cardinalized probability hypothesis density (CPHD) recursion, which is based on Bayesian information theory, is developed to handle the data association uncertainty, and to acquire existing targets’ numbers and states (e.g., position and velocity). The key idea of the CPHD recursion is to simultaneously estimate the targets’ intensity and the probability distribution of the number of targets. The CPHD recursion is the first moment approximation of the Bayesian multiple targets filter, which avoids the data association procedure between the targets and measurements including clutter. The Bayesian-filter-based extended Kalman filter (EKF) is applied to deal with the nonlinear bearing and Doppler measurements. The experimental results show that the EKF-based CPHD recursion works well in the underwater passive multiple target tracking system in cluttered and noisy environments.     

Infrared small target enhancement via phase spectrum of Quaternion Fourier Transform

Small target enhancement is one of the crucial stages in infrared small target detection. In this paper, we propose a new method using phase spectrum of Quaternion Fourier Transform to enhance small targets while suppressing backgrounds for infrared images. This is inspired by the property that regularly Gaussian-like shape small targets could be considered as attractively salient signal in infrared images and the location information of such signal is implicitly contained in the phase spectrum from frequency domain. Formally, in the proposed method, we adopt the phase spectrum of Quaternion Fourier Transform instead of using traditional Fourier Transform to enhance the targets since the quaternion provides at most four data channels than only one for the latter, which could be helpful to broad types of background clutters by adding more information. For the construction of the quaternion, we present a second-order directional derivative filter via facet model to compute four second order directional derivative maps from four directions respectively as the four data channels. This filter is used to suppress noises and distinguish the targets and backgrounds into separably different textures so that it would boost the robustness of small target enhancement. In experiments, some typical infrared images with various scenes are tested to validate the effectiveness of the proposed method. The results demonstrate that our method actually has good performance and outperforms several state-of-the-art methods, which can be further used for infrared small target detection and tracking.     

ESR Study on Scavenging Effect of Squalene on Free Radicals in Mainstream Cigarette Smoke

Radicals in mainstream cigarette smoke (MCS) have been proposed to contribute to the harm caused by cigarette smoking. In the present study, we used natural antioxidant, squalene, to treat cigarette filters and tobacco for scavenging gas- and particulate-phase free radicals in MCS. The scavenging activities of cigarette filter and tobacco containing squalene against gas and particulate-phase free radicals were detected and quantified using spin-trapping or directly electron spin resonance spectroscopy method. The results revealed that squalene could significantly scavenge gas- and particulate-phase free radicals in MCS in a dose-dependent manner. The radical-scavenging activity of cigarette filter treatment was higher than that of tobacco treatment, irrespective of either gas-phase free radicals, or particulate-phase free radicals in MCS. Among them, 3 mg squalene/filter treatment showed that the highest scavenging effects against gas- and particulate-phase free radicals were 35.9 and 35.4%, respectively. The use of squalene as potential scavenger for reducing free radicals in cigarette smoke is discussed.