Moving target location and imaging using dual-speed velocity SAR

Velocity synthetic aperture radar (VSAR) is an effective tool for slowly moving target detection, location and imaging. However, it may mislocate fast moving targets because of the azimuth location ambiguity. The VSAR is generalised from flying with single speed to flying with dual-speed to resolve the azimuth location ambiguity. This new system is named dual-speed velocity SAR (DS-VSAR). Using DS-VSAR, the locations of both slowly and fast moving targets can be estimated accurately, and in the meantime the clutter can be suppressed. Some numerical examples are given to prove the effectiveness of DS-VSAR     

Bistatic point target reference spectrum in the presence of trajectory deviations

The point target reference spectrum (BPTRS) of bistatic SAR in the presence of trajectory deviations based on Loffeld?s bistatic formula (LBF) is developed. The presented BPTRS is suitable for the general airborne bistatic configuration. For the air-borne bistatic SAR, both the transmitter and the receiver will contribute to the trajectory deviation. The compensation of trajectory deviations becomes more complex because of the separate locations of the transmitter and receiver. The authors focus on the effects of trajectory deviations on the point target spectrum of bistatic SAR. The proposed BPTRS is verified by simulation experiments performed in the azimuth-invariant configuration.     

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.     

Quality enhancement of image generated with bistatic ground based noise waveform SAR

A new method for quality enhancement in a noise synthetic aperture radar (SAR) image and the first results of its application to the SAR image generated with the use of a bistatic Ka-band ground-based noise waveform SAR (GB NW-SAR) are presented. A SAR image generated with a noise SAR suffers from the masking effect which is tied to residual random fluctuations in noise radar response from bright scatterers in the scene. This is similar to the masking effect present in the deterministic waveform SAR when the signal sidelobes of echoes from bright scatterers may mask the main response from a weaker target. The procedure presented is a variation of the CLEAN algorithm. Knowing precisely the emitted signal and finding positions of the strongest scatterers one may model the echo signal originated from a selected scatterer. Extraction of the modelled signal from the received one reduces the residual fluctuations and makes it possible to clean the image and increase its dynamic range. The final image is constructed from the cleaned signal and the previously removed strongest scatterers. A theoretical background is provided to the proposed procedure and its application to enhance the SAR image using simulated data as well as data generated by the Ka-band bistatic GB NW-SAR is demonstrated. The GB NW-SAR, recently developed and tested in LNDES IRE NASU, may operate in CW and pulse random signal regimes for short range applications.     

Optimal multichannel estimation of the location of a target with nonoverlapping noise

We propose a new algorithm for estimating the location of an object in multichannel images when the noise is spatially disjointed from (nonoverlapping with) the target. This algorithm is optimal for nonoverlapping noise and for multichannel images in the maximum-likelihood sense. We consider the case in which the statistical parameters of the input scene are unknown and are estimated by observation. We assess the results for simulated images with white and Gaussian background, for a large scale of variances of the background noise, and different values of the contrast in the scene. We compare the results of this algorithm with the results obtained with two other algorithms, the optimal algorithm for monochannel nonoverlapping noise and the optimal algorithm for multichannel additive noise, and we show that in both cases improvement can be obtained. We show the efficiency of the estimation for real input scenes when the background noise is correlated clutter noise. This algorithm has the same complexity as correlation, and the improvement is obtained with no more calculation cost than with classic methods.     

Efficient Strip-Mode SAR Raw-Data Simulator of Extended Scenes Included Moving Targets Based on Reversion of Series

The Synthetic Aperture Radar (SAR) raw data generator is required to the evaluation of focusing algorithms, moving target analysis, and hardware design. The time-domain SAR simulator can generate the accurate raw data but it needs much time. The frequency-domain simulator not only increases the efficiency but also considers the trajectory deviations of the radar. In addition, the raw signal of the extended scene included static and moving targets can be generated by some frequency-domain simulators. However, the existing simulators concentrate on the raw signal simulation of the static extended scene and moving targets at uniform speed mostly. As for the issue, the two-dimensional signal spectrum of moving targets with constant acceleration can be derived accurately based on the geometric model of a side-looking SAR and reversion of series. And a frequency-domain algorithm for SAR echo signal simulation is presented based on the two-dimensional signal spectrum. The raw data generated with proposed method is verified by several simulation experiments. In addition to reveal the efficiency of the presented frequency-domain SAR scene simulator, the computational complexity of the proposed method is compared with the time-domain approach using the complex multiplication. Numerical results demonstrate that the present method can reduce the computational time significantly without accuracy loss while simulating SAR raw data.     

Adaptive target detection with a polarization-sensitive optical system

We developed an adaptive polarimetric target detector (APTD) to determine the optimum combination strategy for a multichannel polarization-sensitive optical system. The proposed algorithm is based on scene-derived polarization properties of the target and background, and it seeks to find an optimum multichannel combination of linear polarizing filters that maximizes the signal-to-clutter ratio (SCR) in intensity and Stokes parameter images. The algorithm is validated by performing RX anomaly detection and a generalized likelihood ratio test on both synthetic and real imagery. The experimental results are analyzed through calculated SCR and receiver operating characteristic curves. Compared with several conventional operation methods, we find that better target detection performance is achieved with the APTD algorithm.     

Approach for single channel SAR ground moving target imaging and motion parameter estimation

In recent years, ground moving target imaging in synthetic aperture radar (SAR) has attracted the attention of many researchers all over the world. A novel approach is proposed for the ground moving target imaging and motion parameter estimation using single channel SAR. First, a second-order generalised keystone formatting method is used to compensate for the range curvature. Secondly, the estimated slope of the target echo's envelope is used for the range walk compensation. Thirdly, Doppler parameters of moving targets obtained via spectral analysis are used for the imaging and positioning of ground moving targets. Finally, motion parameters of moving targets can be estimated on the basis of the relationship between Doppler and motion parameters. Both numerical and experimental results are provided to demonstrate the performance of the proposed approach     

一种基于关联处理的声呐图像去噪技术

为了改善声呐图像中存在大量杂波而导致目标跟踪困难,设备虚警率高的缺点,提出一种图像关联降噪算法。首先利用目标特性对静止目标进行剔除,之后利用目标运动的持续性和目标回波在连续多帧图像中的空间位置关联性,对随机噪声进行进一步滤除。仿真和试验数据验证,所提出的算法对于背景比较稳定的图像,降噪效率不低于95%。     

一种有效的机载合成孔径雷达动目标成像方法

为实现机载合成孔径雷达(Synthetic Aperture Radar,简称SAR)实际回波数据中的运动目标聚焦成像,本文在用前置滤波法检测出运动目标的基础上,提出了利用目标子图像匹配方法来估计动目标的方位向速度,得到相应的运动目标聚焦参考函数,然后对运动目标进行聚焦成像,并给出了利用该方法得到的运动目标聚焦图像．成像结果表明,目标子图像匹配方法对动目标成像是有效的,易于工程实现,有实际应用价值．     

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.     

基于H(o)lder指数和ICA的海域SAR图点目标检测

本文将分形H(o)lder指数和信号分离相结合,利用独立成分分析技术(ICA,Independent ComponentAnalysis),实现了海杂波SAR图的散斑抑制和点目标检测.首先,计算点态H(o)lder指数图,并提出二值模糊方法对其处理;接着使用ICA技术得到该图的基图像和独立成分;提出空间分离法,对独立成分进行分离,同时对基图进行对应分类,获得非噪声和噪声两个空间.最后在非噪声空间上重构图像.实验部分,将该算法与传统算法进行对比,证实了该算法的有效性和优越性.     

基于Hǒlder指数和ICA的海域SAR图点目标检测

本文将分形Hǒlder指数和信号分离相结合,利用独立成分分析技术（ICA,Independent Component Analysis）,实现了海杂波SAR图的散斑抑制和点目标检测。首先,计算点态Hǒlder指数图,并提出二值模糊方法对其处理;接着使用ICA技术得到该图的基图像和独立成分;提出空间分离法,对独立成分进行分离,同时对基图进行对应分类,获得非噪声和噪声两个空间。最后在非噪声空间上重构图像。实验部分,将该算法与传统算法进行对比,证实了该算法的有效性和优越性。     

带SSR修正的异步多传感器系统的无味JPDA跟踪

针对杂波环境下多变采样率传感器多目标跟踪问题,考虑到二次雷达(SSR)具有辨别敌我方目标和更精确的高度探测能力,本文提出了一种带SSR修正的异步多传感器系统的无味JPDA跟踪算法.该算法首先通过测量值映射的异步数据处理方法对多传感器数据进行点迹的合成,然后通过二次雷达对敌方目标的高度信息进行自适应修正,最后用无味JPDA算法对按序到来的异步采样量测进行顺序滤波融合.通过蒙特卡洛仿真,表明该算法在提高目标跟踪精度和正确关联概率上是有效的.     

双基雷达空时自适应处理中的杂波特性

基于合适的双基坐标系，得出双基雷达的等距离曲线方程是一族椭圆．文章研究了对齐、平行和垂直三种不同的双基几何配置时的方位-多普勒杂波轨迹特性，并将之与单基情形进行对比，从而揭示了双基杂波的非静态特性；以杂波功率谱特性为工具研究了杂波特性对空时自适应处理性能的影响，双基杂波的非静态特性使得空时自适应处理器的杂波频谱变宽，最小可检测目标速度变大，处理性能大大恶化．本文的分析方法适用于机载和星载双基雷达．     

平飞斜视模式双站合成孔径雷达数据处理算法

研究了发射和接收分离的双站合成孔径雷达成像算法.主要分析了双站合成孔径雷达在平飞斜视工作模式下的方位分辨率,以及二次距离徙动校正判据,研究了利用非线性Chirp Scaling(NLCS)的方法,来消除同一距离单元上的不同方位调频斜率带来的影响,并且推导出了平飞斜视模式下的方位匹配滤波函数的频域表示,通过点目标成像仿真验证了该方法的正确性.     

Autonomous target tracking and following mobile robot

Tracking and following a moving target in real time is a very challenging task in autonomous mobile robot applications, due to the unstructured and unknown environment. In this article, a real time, autonomous, dynamic, whole-field target tracking system (360° coverage) is developed based on a pan/tilt/zoom CCD vision system. The vision system scans and locks the pose of the moving target and commands the tracking mobile robot to follow the target while avoiding obstacles. Bayes’ theorem-based foreground–background segmentation algorithm is applied for motion detection. The color-based particle filter algorithm is used to track the moving object. The system steers the tracking mobile robot toward the moving target based on the angular difference obtained from the tracking module. Fuzzy logic is applied and a sensor data fusion algorithm is developed to reduce the ultrasonic phantom effect of obstacle detection using eight ultrasonic sensors. Multiple behaviors are integrated through the proposed system. Experimental results show the proposed system can successfully track and follow a moving target and avoid obstacles in real time. The tracking accuracy is higher than 80%.     

Real-time adaptive clutter rejection filtering in color flow imaging using power method iterations

We propose a new algorithm for real-time, adaptive-clutter-rejection filtering in ultrasound color flow imaging (CFI) and related techniques. The algorithm is based on regression filtering using eigenvectors of the signal correlation matrix as a basis for representing clutter, a method that previously has been considered too computationally demanding for real-time processing in general CFI applications. The data acquisition and processing scheme introduced allows for a more localized sampling of the clutter statistics and, therefore, an improved clutter attenuation for lower filter orders. By using the iterative power method technique, the dominant eigenvalues and corresponding eigenvectors of the correlation matrix can be estimated efficiently, rendering real-time operation feasible on desktop computers. A new adaptive filter order algorithm is proposed that successfully estimates the proper dimension of the clutter basis, previously one of the major drawbacks of this clutter-rejection technique. The filter algorithm performance and computational demands has been compared to that of conventional clutter filters. Examples have been included which confirms that, by adapting the clutter-rejection filter to estimates of the clutter-signal statistics, improved attenuation of the clutter signal can be achieved in normal as well as more excessive cases of tissue movement and acceleration.     

Statistical-physical model for foliage clutter in ultra-wideband synthetic aperture radar images

Analyzing foliage-penetrating (FOPEN) ultra-wideband synthetic aperture radar (SAR) images is a challenging problem owing to the noisy and impulsive nature of foliage clutter. Indeed, many target-detection algorithms for FOPEN SAR data are characterized by high false-alarm rates. In this work, a statistical-physical model for foliage clutter is proposed that explains the presence of outliers in the data and suggests the use of symmetric alpha-stable (SalphaS) distributions for accurate clutter modeling. Furthermore, with the use of general assumptions of the noise sources and propagation conditions, the proposed model relates the parameters of the SalphaS model to physical parameters such as the attenuation coefficient and foliage density.     

Estimating building dimensions from synthetic aperture radar image sequences

The problem of automatically extracting building dimensions from synthetic aperture radar (SAR) image sequences of urban scenes is considered. An algorithm based on the delineation of shadows using active contours constrained by a simple wire-frame building model has been developed and demonstrated using SAR imagery of a village on Salisbury plain. The core of the algorithm is a novel technique for target delineation involving multiple active contours evolving simultaneously. In particular, a technique referred to as multiple hypothesis delineation, in which contours can be in several states simultaneously, is developed and shown to lead to considerable improvement in convergence time and delineation accuracy when used to delineate multiple targets in close proximity. The technique is applied to the automatic estimation of building dimensions by delineation of shadows in a sequence of SAR images of an urban scene. The estimation of building dimensions is automatic; user interaction is limited identifying a building of interest and a region of background clutter close to the building. Results are presented for six different buildings, in each case two SAR images were used in the estimation process separated in illumination angle by either 28deg or 90deg. The estimates of building dimensions are compared with the actual building dimensions obtained from architectural drawings. The algorithm was found to perform robustly and provide reasonably accurate estimates of the building dimensions, typically within ~10% of the true values.