动态背景下基于金字塔LK光流的运动目标检测

提出了一种动态背景下基于金字塔LK光流的运动目标检测方法。首先采用Shi-Tomasi角点检测法提取图像的强角点,再用金字塔LK光流法计算下一时刻这些特征点的对应位置,得到匹配的多组特征点对。利用这些特征点对建立仿射变换模型并计算仿射参数,对图像做仿射变换消除背景运动带来的误差,最后用帧间差分法处理得到前景目标。实验结果表明,本方法能够以较好的实时性、稳定地检测和提取动背景下的运动目标。     

Multiple moving target detection and trajectory estimation using a single SAR sensor

A novel methodology is presented for determining the velocity and location of multiple moving targets using a single strip-map synthetic aperture radar (SAR) sensor. The so-called azimuth position uncertainty problem is therefore solved. The method exploits the structure of the amplitude and phase modulations of the returned echo from a moving target in the Fourier domain. A crucial step in the whole processing scheme is a matched filtering, depending on the moving target parameters, that simultaneously accounts for range migration and compresses two-dimensional signatures into one-dimensional ones without losing moving target information. A generalized likelihood ratio test approach is adopted to detect moving targets and derive their trajectory parameters. The effectiveness of the method is illustrated with synthetic and real data covering a wide range of targets velocities and signal-to-clutter ratios (SCRs). Even in the case of parallel to platform moving target motion, the most unfavorable scenario, the proposed method yields good results for, roughly, SCR > 10 dB.     

Filtering of moving targets using SBIR sequential frames

In this paper three-dimensional (3-D) finite-impulse response (FIR) filters are proposed for moving target detection and tracking from multiframe space-based infrared (SBIR) data. An optimal, in the l_p sense, 3-D FIR filter design technique is proposed which is suitable for the above application. This technique is the first 3-D FIR design of its kind presented in the open literature. Directional, matched, and adaptive 3-D filtering techniques are proposed. Prior to the filtering, clutter mean estimation and mean subtraction are required. Real time implementation of directional and/or matched filters for processing maneuvering targets is discussed and filter design methods are proposed. Finally, performance comparisons of the proposed and other available 3-D FIR and infinite-impulse response (IIR) filters, on real SBIR data, are presented in which the advantages of the proposed 3-D filters are shown     

Velocity estimation of fast moving targets using a single SAR sensor

A new methodology is presented to retrieve slant-range velocity estimates of moving targets inducing Doppler-shifts beyond the Nyquist limit determined by the pulse repetition frequency (PRF). The proposed approach exploits the linear dependence (not subject to PRF limitations) of the Doppler-shift with respect to the slant-range velocity, at each wavelength. Basically, we propose an algorithm to compute the skew of the two-dimensional spectral signature of a moving target. Distinctive features of this algorithm are its ability to cope with strong range migration and its efficiency from the computational point of view. By combining the developed scheme to retrieve the slant-range velocity with a methodology proposed earlier to estimate the velocity vector magnitude, the full velocity vector is unambiguously retrieved without increasing the mission PRF. The method gives effective results even when the returned echoes of the moving targets and the static ground overlap completely, provided that the moving targets signatures are digitally spotlighted and the signal-to-clutter ratio (SCR) is, roughly, greater than 14 dB. The effectiveness of the method is illustrated with simulated and real data. As an example, slant-range velocities of moving objects with velocities between 6 and 12 times the Nyquist velocity are estimated with accuracy better than 3%.     

Dynamic Programming Solution for Detecting Dim Moving Targets

An on-board scanning or mosaic sensor is staring down from a satellite to a fixed ground point while producing a set of frames that contain target and background signals. Detecting dim moving targets should ideally be done by exhaustively searching over all in he maery(mached fltering), as ppoed possible trajectories in the imagery (matched filtering) as opposed to assembling trajectories from thresholded frames. The dynamic programming approach equivalently substitutes the above prohibitive exhaustive search by a feasible algorithm.     

Application of velocity filtering to optical-flow passive ranging

The performance of the velocity filtering method as applied to optical-flow passive ranging under real-world conditions is evaluated. The theory of the 3-D Fourier transform as applied to constant-speed moving points is reviewed, and the space-domain shift-and-add algorithm is derived from the general 3-D matched filtering formulation. The constant-speed algorithm is then modified to fit the actual speed encountered in the optical flow application, and the passband of that filter is found in terms of depth (sensor/object distance) so as to cover any given range of depths. Two algorithmic solutions for the problems associated with pixel interpolation and object expansion are developed, and experimental results are presented     

基于邻帧差分近邻反相特征的红外运动点目标检测算法

基于运动点目标在邻帧差分图像中所具有的近邻反相特征,即运动点目标的两个位置相邻近、灰度值一正一负,提出一种在复杂背景下,基于红外序列图像的运动点目标检测算法.本算法利用该特征在邻帧差分图像中检测反相点对,进而构造反相点对矢量图,最后依据累积反相点对矢量图中多矢量首位相接的连续性检测出运动的点目标.文中给出并证明应用本算法能以概率1检测到运动点目标的收敛性定理.对典型复杂背景下10幅1000帧图像的仿真结果表明,当信噪比大于或等于1.5时,可以有效检测出运动点目标.     

A Velocity Estimation Algorithm of Moving Targets using Single Antenna SAR

A new algorithm is proposed for velocity estimation of moving targets in single antenna synthetic aperture radar (SAR). Based on the fact that different velocity vectors cause different geometrical figures of the two-dimensional (2-D) signature in the range-Doppler (RD) domain, this algorithm estimates the azimuth and range velocities by a 2-D search such that the range cell migration correction (RCMC) and the second range compression (SRC) are correctly performed. It is shown that, using the proposed algorithm, the Doppler ambiguity problem can be avoided and satisfactory accurate velocity estimation can be obtained in high signal-to-clutter ratio (SCR) scenarios.     

Moving Targets Processing in SAR Spatial Domain

This paper presents a novel technique to estimate the initial coordinates and velocity vector of moving targets, including those with velocities above the Nyquist limit, using a single synthetic aperture radar (SAR) sensor without increasing the pulse repetition frequency (PRF). The basic reasoning is that, although the returned echoes may be undersampled in the azimuth direction, their phase and amplitude are informative with respect to the moving target trajectory parameters. Therefore, the so-called blind angle ambiguity, inherent to systems using a single SAR sensor, is overcome. The proposed method samples the data in the spatial domain, along the signature curve which depends on the moving target trajectory parameters. The resulting algorithm is a highly efficient (from the computational point of view) ID matched filter. The effectiveness of the proposed scheme is illustrated using simulated SAR data and real data from the MSTAR public release data set, corresponding to a static SAR scene and a static BTR-60 with simulated motion.     

Detection of weak, subpixel targets using mesh-connected cellularautomata

Effective use of military cellular automata such as military data array processor (MilDAP) and geometric arithmetic parallel processor (GAPP), in weak, subpixel target detection is shown to be possible by using new signal processing regimes based on binary ranking filter theory. By using binary ranking filters, the MilDAP can furnish 6 dB of processing gain against white Gaussian noise while monitoring from one to four million potential target tracks at 10-40 frames/s. GAPP is shown to be capable of monitoring 3.7 million tracks over 216×384 detectors at 14000 frames/s and, in a time sharing mode, 15 million tracks over 432×768 detectors at 24 frames/s. The special case of threatening targets is discussed, as well as alternate cellular architectures which use multidimensional binary ranking filters in multidimensional coordinate systems     

Satellite intercept targeting DSP algorithm design and evaluation

A unified processing approach for the detection and localization of satellites or other exoatmospheric targets is presented. Enhanced filtering and centroid determination algorithms were developed based on real-time implementation constraints, mission conditions including accuracy requirements, and signature structure. The signature structure consisted of target returns, high-frequency random noise, low-frequency structured noise, and contamination sources resulting from debris and cosmic events. Detailed signal processing analyses were performed to verify the required subsample accuracy and the sensitivity to hardware and system constraints. The resultant system design was functionally verified in a real-time breadboard processor     

Target motion compensation in synthetic aperture radar

In a synthetic aperture radar (SAR) targets on the ground that are moving become smeared as a result of velocity components parallel to the motion of the radar and are moved to radically different angular positions if they have velocity components perpendicular to the motion of the radar. Methods for restoring moving targets to their correct size and position are described. The samples collected for SAR processing are frequency-modulated RF pulses. Mathematically this leads to spectra that are described by Fresnel integrals. For stationary targets, the spectrum is symmetrical around the origin. If there is a moving target in a range cell, its Doppler spectrum will be displaced from the origin and may undergo other changes as a result of its nonzero velocity. Proper compensation to locate the target at the correct position requires that the spectrum be translated to a position dependent on the along-track velocity rather than to the origin. From the central frequency, the along-range velocity component can be estimated and the length of the translation can then be found. After translation, the spectrum is converted back to the time domain and the customary SAR processing is performed     

基于运动特征和中心环绕模型的空对地车辆检测方法

平台的移动基于空基车辆检测以其视野广、速度快、适应性强等优点,近些年成为了智能交通和航空应急救援等领域内的一个热点课题。然而,在城市背景的交通环境下,由于复杂背景造成的干扰、车辆运动的不规律性以及光照等条件变化带来的噪声,有效地获取运动对象特征是空对地视觉监视方法面临的一个难题。为有效解决这一问题,提出了结合运动特征的中心环绕模型进行空对地车辆检测的算法。现有的空对地车辆检测算法,大多是针对固定的摄像头的情况下,基于运动特征进行检测,例如光流法、背景差法等。这些方法在对高速公路等背景相对较为简单的环境下获得了良好的检测结果,但当面对城市复杂背景条件或摄像头自身运动的状况时,难以有效地检测出运动目标。而在对颜色、强度等静态特征进行显著度分析的基础上,加入了对运动特征的分析,可以解决在复杂环境下准确提取车辆目标有效特征的问题。试验表明,相较于基于图像相减的检测算法和单一显著度算法,该算法可以获得更高的检测率与更低的误报率。     

Studies of target detection algorithms that use polarimetric radardata

Algorithms are described which make use of polarimetric radar information in the detection and discrimination of targets in a ground clutter background. The optimal polarimetric detector (OPD) is derived. This algorithm processes the complete polarization scattering matrix (PSM) and provides the best possible detection performance from polarimetric radar data. Also derived is the best linear polarimetric detector, the polarimetric matched filter (PMF), and the structure of this detector is related to simple polarimetric target types. New polarimetric target and clutter models are described and used to predict the performance of the OPD and the PME. The performance of these algorithms is compared with that of simpler detectors that use only amplitude information to detect targets. The ability to discriminate between target types by exploring differences in polarimetric properties is discussed     

Detecting moving targets in SAR imagery by focusing

A new method for detecting moving targets in a synthetic aperture radar (SAR) image is presented. It involves segmenting a complex-valued SAR image into patches, focusing each patch separately, and measuring the sharpness increase in the focused patch. The algorithm is sensitive to azimuth velocities and is exquisitely sensitive to radial accelerations of the target, allowing it to detect motion in any direction. It is complementary to conventional Doppler-sensing moving target indicators, which can sense only the radial velocity of rapidly moving targets.     

航拍视频帧间快速配准算法

 为应对相机运动的影响,提出了一种快速有效的无人机(UAV)视频相邻帧图像配准算法。通过空间分布约束和角点量限制来筛选有效的FAST特征点,引入自适应阈值提高特征点检测的环境适应性,采用训练得到的不相关采样点集对特征点进行二值描述,以获得准确快速的特征描述,并通过最近邻算法根据汉明距离获得特征匹配对,最后运用RANSAC方法得到帧间仿射变换模型参数,消除相机运动带来的影响,为后续运动目标检测与跟踪提供保障。实验结果表明该算法快速、稳定,具有较高的环境适应性,能够满足无人机系统视频图像配准的要求。     

The Effect of Staggered PRF's on MTI Signal Detection

Long-range surveillance radars use MTI techniques to detect moving targets in a clutter background. The transmitter PRF is usually staggered to eliminate the blind speeds due to aliasing of the target and clutter spectra. A spectral analysis of the target and clutter signals is performed for the case of nonuniform sampling, and it is shown that the clutter spectral density continues to fold over at the basic PRF, but the signal spectrum becomes dispersed in frequency, which means that an MTI rader will never be completely blind to moving targets.     

Target-Motion-Induced Radar Imaging

Imaging from ground-based (stationary) radars of moving targets is often possible by utilizing a "synthetic aperture" developed from the target motion itself. The theory and experimental results associated with such processing are addressed. An aircraft is imaged from both a straight flight and a turn with recognizable results. Analysis shows that two-phase components exist in the radar return, one being gross velocity induced, the other being interscatterer interference within the target itself. The former phase must be removed prior to imaging and techniques are developed for this task. Preprocessing, range curvature, range alignment, motion compensation, and presumming are all addressed prior to presenting the experimental results. Coherence processing intervals, range collapsing, and range realignment are all examined during the processing aspects of the paper.     

Track-While-Scan Algorithm in a Clutter Environment

A track-while scan (TWS) algorithm is developed for targets in a clutter environment. The problem has been studied using only the position measurements [1, 5-8], but the simulation results have not been satisfactory. Modern processing techniques (FFT processor) ) in air traffic control and surveillance radar receivers provide both position and radial velocity. The radial velocity measurement may be conveniently used in the target-track correlation process, which will reduce the association ambiguity in the clutter environment. t. In the clear environment the algorithm using the position and radial velocity measurements has been treated in [3, 4]. A TWS algorithm, using both position and radial velocity measurements for targets in a clutter environment, is presented here. The algorithm obtained is nonlinear and adaptive. In order to evaluate the improvement due to radial velocity measurement a simulation has been performed on a digital computer. The algorithm was run with and without radial velocity measurements to compare its performances. An improvement was noted especially when the target path included an accelerated portion.     

基于杂波对消-自聚焦的多通道SAR-GMTI

对超高频(UHF)波段多通道合成孔径雷达(SAR)动目标检测技术进行研究,解决了长相干积累时间导致动目标在方位向散焦严重的问题。采用分块自聚焦技术对多通道SAR地面移动目标指示(GMTI)系统自适应杂波抑制后的SAR图像进行处理,改善杂波抑制后的SAR图像中动目标的聚焦情况,增强动目标与周围剩余杂波的对比度,进而提高恒虚警率(CFAR)检测的性能。与传统杂波抑制后直接进行CFAR检测方法相比较,该方法降低了检测虚警概率。实测数据处理结果显示动目标的信杂比明显提高,动目标方位向聚焦成功,证明了该方法的有效性。