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For pt.1 see ibid., vol.43, no.4, p.28-43 (2001). An integrated maritime surveillance (IMS) system, based on high-frequency surface wave radars (HFSWR), for monitoring surface and low-level air activity within the 200 nautical mile (nm) Exclusive Economic Zone (EEZ) is described in this two-part paper. The science behind the long-range performance of HFSWR was presented in Part 1(Sevgi et al. 2001). The system described was installed on Canada's east coast, where it is being used to demonstrate continuous, all-weather surveillance of the EEZ to beyond 200 nm. The system consists of two land-based HFSWRs and an operations control center (OCC). The two unmanned radars provide coverage of the Grand Banks region of Newfoundland, renowned for its offshore resources, particularly fish and oil. The system has been designed to assist authorities to more efficiently monitor such illegal activities as drug trafficking, smuggling, piracy, illicit fishing and illegal immigration. In addition, the system may be used for tracking icebergs, environmental protection, search and rescue, resource protection, sovereignty monitoring, and remote sensing of ocean surface currents and winds. Extensive performance testing of the system has been conducted using the two fully functional radars. It is shown that the HFSWR system complements existing surveillance assets to dramatically increase the effectiveness of air and surface reconnaissance missions by vectoring them directly to targets of interest 相似文献
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高频地波雷达(high frequency surface wave radar,HFSWR)对于海事监测具有重要的军用及民用意义,然而在HFSWR回波信号中,待检测的目标常常淹没在海杂波和各种背景噪声中.因此,如何有效抑制杂波并实现多目标的自适应检测是HFSWR实现海事检测的关键和难点.该文提出了一种结合误差自校正极限学习机(error self-adjustment extreme learning machine,ES-ELM)和分数阶傅里叶变换(fractional Fourier transform,FRFT)的多目标自适应检测算法.算法根据相空间重构理论获得ELM的最佳状态空间,利用ES-ELM建立海杂波预测模型并对海杂波进行有效抑制;再在分数域根据目标信号的峰值集聚特征,利用Haar-like算子提取目标点的形态特征,并通过ES-ELM神经网络对目标进行自动辨识.实验结果表明,该文提出的算法具有良好的海杂波抑制能力,并可以实现海杂波背景下多运动目标的自适应高精度检测. 相似文献
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电离层杂波的精确预测对提升高频地波雷达的探测性能具有重要作用。提出了一种基于改进非洲秃鹫优化算法优化门控循环单元(Improved African Vultures Optimization Algorithm Optimization Gated Recurrent Unit, IAVOA-GRU)网络的电离层杂波预测方法。首先,依据电离层杂波的混沌特性,通过相空间重构方法对接收到的电离层杂波进行相空间重建,构建GRU网络的输入、输出样本集;然后,利用IAVOA对GRU网络的隐层节点数、迭代次数及初始学习速率3个超参数值执行优选;最后,重新训练优化后的GRU网络,并进行预测。实测结果表明,相较其他6种对比预测模型,所提出的IAVOA-GRU网络模型具有较高的预测精度和可靠性,为有效改善高频地波雷达的探测性能提供了一种思路和方法。 相似文献
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高频地波雷达(high-frequency surface wave radar,HFSWR)中电离层杂波的存在,会极大地影响雷达系统的性能,降低对目标的探测能力.为了精确获得杂波参数,从而更好地抑制电离层杂波,提出了一种基于压缩感知(compressive sensing,CS)的单快拍参数估计方法,用于对电离层杂波的空域和极化域参数估计.该方法基于极化敏感阵列的块稀疏估计模型,应用块正交匹配追踪(block orthogonal matching pursuit,BOMP)算法实现距离-多普勒域的单快拍空间角度和极化参数联合估计,并进一步获得目标和杂波的空间角谱和极化谱.该方法适用于任意极化敏感阵列,在距离-多普勒域单快拍条件下,其估计性能优于传统方法,且计算复杂度极低,可以实现实时处理.仿真结果和某HFSWR系统实测数据处理结果表明了参数估计方法的有效性. 相似文献
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Xin Guo Hongbo Sun Tat Soon Yeo 《Geoscience and Remote Sensing, IEEE Transactions on》2008,46(7):1879-1891
The performance of high-frequency surface wave radar (HFSWR) is known to suffer from external environmental interference and noise, such as cochannel radio-frequency interference from other radiating source, ionospheric clutter, lightning impulsive noise, etc. This paper experimentally evaluates the interference cancellation performance of various adaptive beamforming schemes with respect to the aforementioned three types of interferences in an attempt to find the most promising adaptive cancellation scheme in practical HFSWR environment. 相似文献
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《电子与信息学报》2015,37(9):2177-2182
天地波混合体制高频雷达(简称天地波雷达,HFHSSWR)海面一阶谱的频移和展宽特性,使得其一阶谱的提取比高频地波雷达(HFSWR)更困难。该文研究了天地波雷达一阶谱频移和展宽特性,并基于其在2维距离-多普勒谱上连续分布的特点,将信噪比方法应用于天地波雷达一阶谱提取。通过双基地角、电离层和海流等对一阶谱频移及展宽特性的定量分析,确定了信噪比方法中一阶谱中心位置、谱峰宽度、左右一阶谱间距等参数的计算方法和取值范围。并利用2维信噪比方法,解决由于天地波雷达信噪比下降引起的一阶谱边界检测不精确的问题。最后,将信噪比法分别应用于仿真和实测天地波雷达数据,验证了方法的有效性。 相似文献
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高频地波雷达(High Frequency Surface Wave Radar,HFSWR)能够探测视距外的海上目标和超低空飞行器,但其性能通常被电离层杂波严重影响。该文使用一种空域极化域协同滤波算法用于电离层杂波抑制。针对其中电离层杂波空域和极化域参数的估计问题,在距离-多普勒域上利用基于压缩感知(Compressive Sensing,CS)的DOA测角方法进行空域参数估计,并提出一种基于统计特性的极化参数估计方法完成极化参数估计。这两种估计方法可获得更高的参数估计精度,从而提高了电离层杂波空域极化域抑制方法的性能。某HFSWR系统实测数据处理结果表明了参数估计和电离层杂波抑制方法的有效性。 相似文献
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高频地波雷达工作时, 往往同时接收到大量的电离层反射回波, 这些电离层杂波会对目标检测造成严重影响, 因此, 电离层杂波抑制是当前高频地波雷达领域的研究热点.文章将电离层回波视为可用信源, 从中反演出垂直方向电离层对应的电子浓度与等离子体频率.对R-D(Range-Doppler)谱图进行预处理, 获取垂直方向的电离层回波谱, 建立其回波功率与电离层雷达散射截面积之间的数学模型, 进而得到对应的电子浓度.在高频地波雷达站进行了实验, 并将反演结果与IRI-2012进行对比, 验证了该方法的可行性和有效性. 相似文献
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天波超视距雷达(OTHR)的观测范围非常广,实战中经常要求在短相干积累条件下检测出舰船目标。然而短相干积累时间带来的低多普勒分辨率很难从强大的海杂波中区分出舰船。为了解决这一问题。可以采用海杂波循环对消法,这就要求对杂波参数进行精确估计。传统方法直接利用Fourier谱中的最大幅度估计杂波参数,估计精度不高从而导致对消性能不太理想。该文提出了一种新的基于FFT相位分析的杂波对消法。该方法与传统的杂波对消相比,有效提高了参数估计精度,减小了剩余杂波强度和扩散程度,有利于舰船目标的峰值显露和从剩余杂波中区分出舰船。以上分析和比较得到了实测数据的检验。 相似文献
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为了从高频地波雷达(High Frequency Surface Wave Radar, HFSWR)信号生成的复杂距离多普勒(Range Doppler, RD)图像中准确提取运动点目标, 提出了一种基于冗余小波变换(Redundant Discrete Wavelet Transformation, RDWT)的RD图像点目标检测算法.该算法根据点目标与海杂波、电离层杂波等特征的差异, 首先在距离方向进行自适应RDWT以去除海杂波和地杂波, 并在多普勒方向进行自适应RDWT以去除电离层杂波; 然后利用图像形态学运算对背景噪声进行了抑制; 最后进行阈值自适应分割以得到点目标.实验结果表明:该算法能有效抑制RD图像中的海杂波、电离层杂波和背景噪声, 能从复杂的RD图像中实现点目标的有效检测, 其检测性能优于改进的恒虚警率(Constant False Alarm Rate, CFAR)算法. 相似文献
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Abnormal fluctuations have been observed in detected power levels of some of the targets during trials of the integrated maritime surveillance system (IMS) based on the Canadian east coast surface-wave high-frequency radar (HFSWR). The power level of most of the surface and air targets fluctuated within measurement-error limits (a few dB) during consecutive detections. These fluctuations have been observed to be more than 15 dB for a huge oil platform and nearby large tankers. These fluctuations are quite different than those observed in microwave radars, such as pulse-to-pulse or scan-to-scan fluctuations (which are modeled as different Swerling-type targets), and as are mentioned in most of the classical radar handbooks. In order to understand the reason behind these fluctuations, the behavior of the target reflectivity and radar cross section (RCS) of surface and air targets and their mutual RCS interaction were investigated. Powerful numerical techniques were used to model and understand the target reflectivity and RCS interactions, mostly in the resonance regime. Different scenarios were created, and the mutual RCS behavior of nearby large targets (such as oil tankers and/or fixed offshore oil platforms) as they were maneuvering were modeled. It was shown that 10 dB to 20 dB RCS fluctuations should be expected when targets interact, especially in the resonance regime 相似文献
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高频地波雷达(HFSWR)可以实现大范围海上船只目标的连续探测,但是海杂波等干扰因素的影响容易造成跟踪航迹的断裂。目前关于地波雷达航迹关联的研究中,通常忽略了航迹断裂的情况,将航迹关联视为二分图匹配问题,这会导致可能将单一目标的断裂航迹判断为多个目标,从而引起目标的误关联。针对上述情况,该文结合模糊综合评判和迭代搜索算法,首次将盖尔-沙普利(GS)算法引入航迹关联领域,并且对其进行改进以满足航迹断裂时的多对多航迹关联情况,提出了改进的盖尔-沙普利(IGS)算法。在该算法中,通过计算航迹之间的模糊综合评判值来得到航迹之间的倾向度序列,再由迭代搜索对航迹进行聚类以获得航迹集群,最后将航迹集群及倾向度序列输入盖尔-沙普利算法来进行数轮博弈以给出关联结果。利用双频率高频地波雷达和船只自动识别系统(AIS)的仿真数据与实测数据进行实验测试,实验结果表明:所提出的算法解决了在航迹断裂情况下的多传感器航迹关联问题,且在密集区域的航迹关联效果优于传统算法。 相似文献
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针对高频地波雷达目标检测中电离层杂波的干扰问题,提出了一种基于改进混合蛙跳算法优化Elman神经网络预测抑制电离层杂波的策略。为解决混合蛙跳算法初始种群分布不均匀、收敛精度低、易陷于局部极值等问题,引入Cubic混沌映射、莱维飞行策略、非线性平衡因子和复制操作,增强种群多样性,提高算法搜索能力。利用改进后的算法和其他算法分别优化Elman神经网络预测抑制模型,结果表明,改进后的算法无论是在收敛精度和稳定性上,还是在临近距离单元电离层杂波的预测抑制上,都取得了显著的提升。在基本保留目标信号的基础上,平均信杂比较原始回波提升18.52 dB,较原始混合蛙跳算法提升1.08 dB,对于电离层杂波的抑制具有较高应用价值。 相似文献