Signal excess in K-distributed reverberation

Active sonar systems have recently been developed using larger arrays and broad-band sources to counter the detrimental effects of reverberation in shallow-water operational areas. Increasing array size and transmit waveform bandwidth improve the signal-to-noise ratio-and-reverberation power ratio (SNR) after matched filtering and beamforming by reducing the size of the range-bearing resolution cell and, thus, decreasing reverberation power levels. This can also have the adverse effect of increasing the tails of the probability density function (pdf) of the reverberation envelope, resulting in an increase in the probability of a false alarm. Using a recently developed model relating the number of scatterers in a resolution cell to a K-distributed reverberation envelope, the effect of increasing bandwidth (i.e., reducing the resolution cell size) on detection performance is examined for additive nonfluctuating and fluctuating target models. The probability of detection for the two target models is seen to be well approximated by that for a shifted gamma variate with matching moments. The approximations are then used to obtain the SNR required to meet a probability of detection and false-alarm performance specification (i.e., the detection threshold). The required SNR is then used to determine that, as long as the target and scatterers are not over-resolved, decreasing the size of the resolution cell always results in an improvement in performance. Thus, the increase in SNR obtained by increasing bandwidth outweighs the accompanying increase in false alarms resulting from heavier reverberation distribution tails for K-distributed reverberation. The amount of improvement is then quantified by the signal excess, which is seen to be as low as one decibel per doubling of bandwidth when the reverberation is severely non-Rayleigh, as opposed to the expected 3-dB gain when the reverberation is Rayleigh distributed.     

基于导航雷达海面回波图像去噪研究

根据海面X波段雷达回波图像数据的时空特点,提出了一种新的去噪方法。该方法利用线检测对雷达图像中的射线状噪声进行分离,然后针对这种特殊的噪声形式提出一种阈值分割的方法,最后在极坐标下针对噪声点进行插值修复。实验表明,与传统的均值滤波和中值滤波等方法相比,新方法无论在主观视觉还是信噪比方面,都有了一定改进,图像保留了更多的细节信息,具有较好的去噪效果。     

尺度自适应分层多阈值热红外遥感舰船检测

针对热红外遥感图像由于低对比度、条带噪声、低空间分辨率等特点而导致的检测效果不佳问题,提出了一种近岸舰船目标尺度自适应选择分层多阈值检测方法。采用舰船模板图像尺度归一化高斯拉普拉斯函数取极大值准则进行尺度自适应选择,利用所选的高斯多尺度空间差分多阈值筛选进行近岸舰船检测,并根据不同类型舰船模板图像尺度和分块数选择对热红外图像舰船目标检测的影响进行验证实验。实验结果表明:所提方法能根据模板尺度特征滤除相似区域,通过设置合理尺度和阈值参数能实现有效检测,且具有一定的抗噪能力。     

基于非锐化掩模引导滤波的水下图像细节增强算法研究

针对水下图像对比度偏低,细节模糊的问题,本文提出基于非锐化掩模引导滤波的细节增强方法。首先由原始图像做引导图进行滤波得到细节层图像,并对细节层使用噪声检测的中值滤波去除斑点噪声;然后对原始图像进行基于均值滤波的非锐化掩模,得到锐化图像,并将锐化图像作为引导图对原始图像进行引导滤波,获取基础层图像;最后将滤波后的细节层进行增益后与引导滤波获取的基础层进行叠加,达到增强水下图像细节的目的。并通过信息熵、局部对比度和平均梯度3种客观评价指标对图像处理结果进行了对比分析,主观和客观测试结果表明,本文采用的算法能够有效提高图像对比度以及增强细节信息,有利于提高水下图像资料解释的准确性。     

地波雷达目标检测跟踪联合处理粒子滤波方法

针对固定粒子数PF-TBD算法计算量大、复杂环境下地波雷达海上船只目标检测与跟踪性能不佳的问题,本文将粒子滤波方法应用于地波雷达船只目标检测与跟踪中,提出了基于自适应粒子滤波的地波雷达目标检测与跟踪联合处理方法。该方法结合地波雷达回波谱中目标展宽特性,充分利用了地波雷达回波谱中面目标的粒子权重信息来设置粒子自适应采样策略,提高了目标检测和跟踪联合处理的效果。通过地波雷达实测数据的目标跟踪结果及与同步AIS信息的比对分析,结果表明:提出的检测跟踪联合处理方法在对低信噪比、快速机动等复杂环境下的多目标跟踪时,可提高目标整体跟踪性能。     

Eddy Detection Over Southern Indian Ocean Using TOPEX/POSEIDON Altimeter Data

Mesoscale eddies constitute the most energetic component of the variability of ocean currents. An attempt has been made for the detection of oceanic mesoscale eddy signatures over the Southern Indian Oceanic (SIO) regions using the dynamic topography derived from TOPEX/POSEIDON (T/P) altimeter data, by the signal processing technique, called matched filtering. After applying all the ocean and atmospheric corrections, data of a complete cycle of T/P over SIO has been used for detection of eddy signatures. The geoid undulations are removed from the data of corrected sea surface height from T/P and the resulting dynamic topographic data are passed through a matched filter designed to detect a generic eddy signature of Gaussian signal embedded in noise. The filter is optimized to detect eddies with amplitude 20 to 30 cm and diameters roughly 100?250 km. Out of all the analyzed data of T/P orbits over SIO a few examples are presented for brevity. Qualitative verification of eddies is done with some independent T/P sea level anomaly data over the region. The analysis shows that the matched filtering technique is most suitable for monitoring eddy signatures along the subsatellite track instantly over the remote and most hostile regions of the southern global oceans.     

基于序列非线性滤波SAR影像水体自动提取

由于合成孔径雷达（SAR）图像中固有斑点噪声的强烈影响,某些对于光学图像有很好效果的目标提取区域分割方法,但是对于SAR图像来说,效果不很好,针对水体目标的亮度及形状分布特征,不作阈值分割处理,而采用序列非线性滤波处理方法,可以快速有效地实现SAR影像水体目标的自动提取识别。     

舰船卫星探测实验中利用AIS获取现场同步数据的可行性分析

在SAR与AIS联合探测探测舰船目标实验中,通过对2010-11-05T06：51渤海海峡Radarsat-2影像的和与之时空匹配的AIS数据比较,发现2种手段探测到的静止的舰船目标能够精确的匹配,但是运动的舰船目标存在一定的偏差.分析了偏差产生的原因,其中距离向偏差是由时间误差引起的;方位向偏差主要是由多普勒频移造成的;这与运动舰船目标的航速、航向及SAR与AIS的探测时间误差有关.在此基础上建立了数学模型,分析上述参数对偏差的影响,并对偏差加以修正,从而实现了SAR与AIS探测结果的匹配.     

Statistical normalization of spherically invariant non-Gaussian clutter

Conventional detection in active sonar involves comparing the normalized matched filter output power to a fixed preset threshold. Threshold crossings from contacts of interest are labeled as detections and those from undesired clutter echoes as false alarms. To maintain a constant false-alarm rate (CFAR) in the presence of strong transient clutter, the system can either increase the threshold or apply some function that suppresses this background down to an acceptable level. The latter approach leads to a more consistent background on the display, which enables operator-assisted detection. Background clutter suppression should not come at the expense of contact detection; to maximize the probability of detection (PD) for a given probability of false alarm (PFA), the likelihood ratio test (LRT) is used. However, the LRT does not address display issues, since the threshold that achieves a desired PFA varies with the input distribution. Ideally, the LRT output is monotonically transformed using a "statistical normalizer" (SN) that returns a consistent CFAR background without degrading the optimized PD. Within the radar community, clutter suppression is proposed using a LRT tuned to a K-distributed spherically invariant random vector (SIRV) model. However, this model does not lend itself to SN, as a closed-form expression for the LRT output density does not exist. In contrast, the proposed SIRV clutter model, with Pareto distributed power, leads to a closed-form density from which the SN function is readily derived. This combined Pareto-LRT/SN detector nearly matches the optimized PD performance of the K-distributed LRT and maintains a consistent CFAR background for display purposes.     

A comparison of inter-frame feature measures for robust objectclassification in sector scan sonar image sequences

This paper presents an investigation of the robustness of an inter-frame feature measure classifier for underwater sector scan sonar image sequences. In the initial stages the images are of either divers or remotely operated vehicles (ROV's). The inter-frame feature measures are derived from sequences of sonar scans to characterize the behavior of the objects over time. The classifier has been shown to produce error rates of 0%-2% using real nonnoisy images. The investigation looks at the robustness of the classifier with increased noise conditions and changes in the filtering of the images. It also identifies a set of features that are less susceptible to increased noise conditions and changes in the image filters. These features are the mean variance, and the variance of the rate of change in time of the intra-frame feature measures area, perimeter, compactness, maximum dimension and the first and second invariant moments of the objects. It is shown how the performance of the classifier can be improved. Success rates of up to 100% were obtained for a classifier trained under normal noise conditions, signal-to-noise ratio (SNR) around 9.5 dB, and a noisy test sequence of SNR 7.6 dB     

基于天绘一号的匹配生长水体提取方法

以国产天绘一号01星多光谱4波段影像为数据源,针对大范围水体提取难度大的问题,提出基于归一化水体指数(NDWI)和单波段阈值法的匹配生长算法。采用NDWI水体指数法提取完整的海洋水体和内陆部分水体,将内陆部分水体与单波段阈值对应位置完整的水体做匹配,再通过连通区提取、掩膜运算获得完整的水体分割二值图。采用两景遥感影像(大连和芝罘)进行实验,并与经典水体提取算法进行对比分析。实验结果表明:该法总体精度在90%左右,Kappa系数在0.8左右,对经典提取算法有了显著改善。在大范围提取水体信息时效果较好,提取水体的同时能有效减少陆地阴影造成的干扰,在海陆边界处,陆地轮廓清晰,较好的将陆地和海洋分割开来。     

一种鲁棒的基于全景视觉的足球机器人目标识别方法

由于光照的变化和全景视觉的畸变,全自主足球机器人对目标识别不稳定且有效性差,为此提出了1种基于Gabor滤波器和支持向量机(SVM)的全自主足球机器人目标识别方法。首先根据颜色特征和面积、长宽比等简单形状特征提取候选目标,候选目标中包含实际的目标和与目标颜色相近且通过上述简单形状特征判断仍无法消除的干扰。将候选目标与Gabor滤波器作卷积来提取特征向量,将特征向量输入SVM进行分类,识别出实际的目标。在机器人MT-R的足球目标识别中对该方法进行了实验,实验表明该种方法具有较好的识别精度,且满足足球机器人的实时性要求。     

联合小波和NLM滤波的侧扫声纳回波信号降噪

为进一步降低侧扫声纳回波信号中非高斯分布的乘性噪声,获取更佳效果的侧扫声纳图像,提出了一种利用小波和NLM(nonlocal means)滤波的组合降噪方法.首先采用同态变换将侧扫声纳回波ping信号中的乘性噪声转换为加性噪声,然后利用小波阈值和NLM滤波对侧扫声纳每ping回波数据实施降噪处理,最后经过小波反变换和指...     

Active sonar detection in shallow water using the Page test

The use of active sonar in shallow water results in received echoes that may be considerably spread in time compared to the resolution of the transmitted waveform. The duration and structure of the spreading and the time of occurrence of the received echo are unknown without accurate knowledge of the environment and a priori information on the location and reflection properties of the target. A sequential detector based on the Page test is proposed for the detection of time-spread active sonar echoes. The detector also provides estimates of the starting and stopping times of the received echo. This signal segmentation is crucial to allow further processing such as more accurate range and bearing localization, depth localization, or classification. The detector is designed to exploit the time spreading of the received echo and is tuned as a function of range to the expected signal-to-noise ratio (SNR) as determined by the transmitted signal power, transmission loss, approximate target strength, and the estimated noise background level. The theoretical false alarm and detection performance of the proposed detector, the standard Page test, and the conventional thresholded matched filter detector are compared as a function of range, echo duration, SNR, and the mismatch between the actual and assumed SNR. The proposed detector and the standard Page test are seen to perform better than the conventional thresholded matched filter detector as soon as the received echo is minimally spread in time. The use of the proposed detector and the standard Page test in active sonar is illustrated with reverberation data containing target-like echoes from geological features, where it was seen that the proposed detector was able to suppress reverberation generated false alarms that were detected by the standard Page test     

船只目标SAR、HFSWR和AIS多手段融合探测的点迹关联分析

A space-borne synthetic aperture radar （SAR）, a high frequency surface wave radar （HFSWR）, and a ship automatic identification system （AIS） are the main remote sensors for vessel monitoring in a wide range. These three sensors have their own advantages and weaknesses, and they can complement each other in some situations. So it would improve the capability of vessel target detection to use multiple sensors including SAR, HFSWR, and A/S to identify non-cooperative vessel targets from the fusion results. During the fusion process of multiple sensors＇ detection results, point association is one of the key steps, and it can affect the accuracy of the data fusion and the efficiency of a non-cooperative target＇s recognition. This study investigated the point association analyses of vessel target detection under different conditions： space- borne SAR paired with AIS, as well as HFSWR, paired with AIS, and the characteristics of the SAR and the HFSWR and their capability of vessel target detection. Then a point association method of multiple sensors was proposed. Finally, the thresholds selection of key parameters in the points association （including range threshold, radial velocity threshold, and azimuth threshold） were investigated, and their influences on final association results were analyzed.     

Mean–Standard Deviation Representation of Sonar Images for Echo Detection: Application to SAS Images

This paper addresses the detection of underwater mines echoes with application to synthetic aperture sonar (SAS) imaging. A detection method based on local first- and second-order statistical properties of the sonar images is proposed. It consists of mapping the data onto the mean-standard deviation plane highlighting these properties. With this representation, an adaptive thresholding of the data enables the separation of the echoes from the reverberation background. The procedure is automated using an entropy criterion (setting of a threshold). Applied on various SAS data sets containing both proud and buried mines, the proposed method positively compares to the conventional amplitude threshold detection method. The performances are evaluated by means of receiver operating characteristic (ROC) curves.     

基于阈值区间的海洋锋面提取模型

A model （Bayesian oceanic front detection, BOFD） of sea surface temperature （SST） front detection in satel- lite-derived SST images based on a threshold interval is presented, to be used in different applications such as climatic and environmental studies or fisheries. The model first computes the SST gradient by using a Sobel algorithm template. On the basis of the gradient value, the threshold interval is determined by a gradi- ent cumulative histogram. According to this threshold interval, front candidates can be acquired and prior probability and likelihood can be calculated. Whether or not the candidates are front points can be deter- mined by using the Bayesian decision theory. The model is evaluated on the Advanced Very High-Resolution Radiometer images of part of the Kuroshio front region. Results are compared with those obtained by using several SST front detection methods proposed in the literature. This comparison shows that the BOFD not only suppresses noise and small-scale fronts, but also retains continuous fronts.     

Performance Analysis for Matched-Field Source Localization: Simulations and Experimental Results

Matched-field methods concern estimation of source locations and/or ocean environmental parameters by exploiting full wave modeling of acoustic waveguide propagation. Typical estimation performance demonstrates two fundamental limitations. First, sidelobe ambiguities dominate the estimation at low signal-to-noise ratio (SNR), leading to a threshold performance behavior. Second, most matched-field algorithms show a strong sensitivity to environmental/system mismatch, introducing biased estimates at high SNR. In this paper, some theoretical developments on matched-field performance analysis are summarized, including Bayesian performance bounds and probabilistic ambiguity analysis, both incorporating environmental/system uncertainty/mismatch. Performance analysis is then implemented for source localization in a typical shallow water environment chosen from the Shallow Water Evaluation Cell Experiments (SWellEX). The performance predictions describe the simulations of the maximum-likelihood estimator (MLE) well, including the mean-square error (MSE) in all SNR regions as well as the bias at high SNR. The threshold SNR and bias predictions are also validated through SWellEX experimental data processing. The results suggest the current environmental, acoustic, and statistical modeling has developed to such a level that the optimum theoretical matched-field performance can be achieved in a well-controlled experiment.     

一种增强型YOLOv3的合成孔径雷达(SAR)舰船检测方法

近年来,海战场成为现代战争的主要作战区域之一,舰船目标逐渐成为海上重点监测对象,能否快速准确地识别海战场舰船目标的战术意图,给指挥员的决策提供必要的支持,这关系到一场海上战役的成败.随着合成孔径雷达(synthetic aperture radar,SAR)成像技术的不断发展,大量SAR图像可用于舰船目标检测与识别.利用SAR图像进行舰船目标检测与识别,已经成为重要的海洋应用之一.针对传统SAR图像舰船检测方法准确率较低的问题,本文在YOLOv3的基础上,结合感受野(receptive field block,RFB)模块,提出一种增强型的SAR舰船检测方法.该方法在最近公开的SAR图像舰船检测数据集上平均准确率值达到了91.50％,与原YOLOv3相比提高了0.92％.实验结果充分表明本文提出的算法在SAR舰船的检测中具有较好的检测效果.     

Mitigation techniques for non-Gaussian sea clutter

This paper deals with the problem of coherent radar detection of targets embedded in clutter modeled as a compound-Gaussian process. We first provide a survey on clutter mitigation techniques with a particular emphasis on adaptive detection schemes ensuring the constant false-alarm rate (CFAR) property with respect to all of the clutter parameters. Thus, we propose a novel decision rule based on a recursive covariance estimator, which exploits the persymmetry property of the clutter covariance matrix. Remarkably, the devised receiver is fully CFAR in that its threshold can be set independently of the clutter distribution as well as of its covariance, even if the environment is highly heterogeneous; namely, the disturbance distributional parameters vary from cell to cell. At the analysis stage, we compare the performance of the novel detector with some classical radar receivers such as that of Kelly and the adaptive matched filter both in the presence of simulated as well as on real radar data, which statistical analysis has shown to be compatible with the compound-Gaussian model. The results show that the new receiving structure generally provides higher detection performance than the others and, for a fluctuating target, it uniformly outperforms the counterparts. We also provide a discussion on the CFAR behavior of the analyzed receivers as well as on their computational complexity.