一种混合的多机动目标跟踪算法研究

提出了一种混合的多机动目标跟踪算法:交互多模型模糊联合概率数据关联算法(IMM-FJPDA),该算法将交互多模型算法(IMM)和模糊联合概率数据关联算法(FJPDA)相结合,它克服了IMM-JPDA算法计算量大和IMM-FDA算法在强杂波环境中跟踪精度差的问题.给出了基于模糊C均值(FCM)算法的多机动目标跟踪步骤.仿真结果表明IMM-FJPDA算法跟踪精度与IMM-JPDA算法相当,但计算量明显减小,提高了跟踪实时性.     

机载MIMO雷达空时自适应杂波对消器

针对机载多输入多输出(MIMO)雷达杂波分布呈现空时耦合特性,提出一种空时自适应杂波对消器.利用机载MIMO雷达的脉冲回波数据,构造杂波对消器的系数矩阵.通过空时自适应杂波对消器的预处理,可以有效地抑制杂波,并通过与常规空时处理算法的级联,最终可以有效提高动目标的检测性能.实现了由传统地基雷达杂波对消器向机载运动平台的推广.仿真结果表明,这种自适应杂波对消器不仅适用于正侧视雷达,对于非正侧视雷达也同样适用.     

基于杂波子空间估计的MIMO雷达降维STAP研究

 多输入多输出(MIMO)雷达是近年来出现的一种新体制雷达,针对MIMO体制的机载雷达开展空时自适应处理（STAP）技术研究是值得进一步努力的方向。本文研究了机载MIMO雷达STAP技术的降维算法,通过对STAP技术杂波抑制原理进行分析,推导并得到一种基于杂波子空间的降维算法。结合扁长椭球波函数（PSWF）的特点,提出了一种基于杂波子空间估计的降维算法,并与若干降维算法的杂波抑制性能进行比较。结果表明,当存在阵元幅相误差时,该算法在保持杂波抑制性能的同时能够有效地降低STAP算法的运算量。     

基于PD处理技术的雷达弱信号检测方法

针对脉冲跟踪测量雷达普遍存在的远距离弱信号检测能力不足的问题,基于PD（PulseDoppler,脉冲多普勒）雷达的杂波抑制与信号处理技术,提出脉冲雷达中的弱信号检测方法;详细分析了在脉冲跟踪测量雷达中应用PD处理技术的可行性,得出在一定约束条件下,可将PD处理技术运用于脉冲跟踪测量雷达,并提出了具体实现方法;最后,通过数据仿真和脉冲雷达实际测量数据进行验证,结果表明该方法能有效提高信噪比。     

基于空域特性的低空空域雷达目标检测

为实现基于非相参雷达的低空空域监视,提出一种基于空域特性的杂波抑制算法,通过构造"最优分类面"来区分复杂低空空域雷达图像中的小弱目标和杂波,极大改善了非相参雷达的低空探测能力。首先,采用背景差分与固定阈值分割建立前景和背景统计模型。然后,基于该模型提取空域特性,建立马尔可夫随机场模型,从而自适应地调节"最优分类面"中的阈值。前景模型数据反映了待检测像素的聚集程度,背景模型数据反映了其相对位置。将本算法分别应用于X波段和S波段航海雷达获取的图像序列。检测结果表明:本算法在检测到低空空域小弱目标的同时,能够将虚警率保持在较低的水平,优于恒虚警检测等经典算法。最后,将本算法与已经实现的目标跟踪算法相结合,实现了一整套完整的低空空域雷达目标检测与跟踪算法。     

一种机动多目标雷达视频信号模拟器的设计

给出了一种机动多目标雷达视频信号模拟器的软硬件设计方案,它可实时输出所需的多个动目标雷达视频信号,雷达信号的类型、目标的数量、目标的回波特性、目标的运动特性、杂波的类型及参数等均可方便地进行设置。该模拟器可满足各种雷达信号处理算法(如杂波抑制、恒虚警检测、动目标跟踪、多基地数据融合等)的测试与效果分析,以及对雷达信号处理机等进行性能调试与测试的需要。     

改进的特征匹配雷达视频运动目标跟踪算法

针对密集杂波和复杂多目标情况下,特征匹配跟踪算法定位跟踪精度较低的问题,提出一种改进的特征匹配雷达视频运动目标跟踪算法。首先,从单帧雷达图像检测结果中提取目标的面积、位置、不变矩信息,在运动目标得到判定后,利用卡尔曼滤波的预测位置以及上一帧特征信息进行目标匹配;然后,根据匹配位置和预测位置给出目标估计位置,并进行特征信息更新;最后,输出目标的特征信息、位置信息和运动参数。利用某型导航雷达上采集的实测数据验证了算法的有效性。     

中等PRF机载PD雷达频域恒虚警处理性能计算

 一、引言 在中等脉冲重复频率（PRF）工作时,MTI-FFT-CFAR是PD或MTD雷达信号处理器的一种典型结构。Lawrence和Moore对MTD雷达在地杂波和气象杂波背景中的检测性能的计算中,假设了邻近距离单元中的杂波样本是独立同分布的（iid）。而在MTI-FFT-频域单元平均CFAR处理器中,频域单元的杂波样本明显偏离iid假设。门     

基于降维STAP 的自适应单脉冲测角算法

将空域广义单脉冲测角算法扩展至空时二维,提出基于降维STAP的自适应单脉冲测角算法,通过实时自适应修正鉴角曲线来降低角误差,实现杂波环境下的目标角误差估计,并且计算复杂度较低,从而保证机载平台在强杂波环境下对目标的稳定跟踪.仿真结果验证了该方法的有效性与性能优势.     

基于加权模糊C均值聚类的图像分割算法

模糊C均值(FCM)算法用于灰度图像分割是一种非监督模糊聚类后再标定的过程,适合灰度图像中存在着模糊和不确定性的特点。但是这种算法存在着本质上的缺陷,就是仅利用了图像的灰度信息,而没有考虑像素的空间信息,使得其对于实际的含有噪声的图像分割效果不理想。因此,提出了一种新的加权模糊C均值聚类算法,实践证明,该方法可以有效地、实时地把目标从背景中分割出来,并具有较强的鲁棒性。     

Data fusion for ground moving target tracking

The aim of ground surveillance is the large scale, continuous and near real time determination of a dynamical ground picture. This task comprises detection and tracking of moving single targets and convoys, mobile weapon systems, and military equipment. The sensors of choice are airborne Ground Moving Target Indicator (GMTI) radar and synthetic aperture radar (SAR). As ground target tracking often suffers from dense target situations, high clutter, and low visibility, the integration and fusion of external background information is essential for providing precise and continuous tracks. We present Multi Hypotheses techniques for tracking several targets in complex ground situations with clutter. Methods to incorporate topographic information, in particular digital road maps, are described and demonstrated.     

基于3DT的空时自适应单脉冲参数估计算法

空时自适应处理(STAP)是机载预警雷达抑制杂波和干扰的一项关键技术,而多普勒三通道联合自适应处理(3DT)是适合工程实现的降维(RD)STAP方法。STAP目标检测后还需进一步估计目标的角度参数,因此将自适应单脉冲(AM)技术引入3DT,提出了一种高精度联合估计目标速度与方位空间角的空时自适应单脉冲算法。理论分析与仿真实验结果表明,当目标多普勒频率偏离检测多普勒单元中心频率时,该算法能同时减少目标多普勒跨越损失和空时导引矢量失配损失,进而提高输出信杂噪比(SCNR),改善目标测角精度。     

非正侧视阵列机载雷达多空间角补偿算法

 非正侧阵列机载雷达的杂波分布随距离变化而变化,各距离单元的杂波分布不再满足独立同分布条件,造成统计型空时自适应处理(STAP)处理器性能下降。本文提出了一种多空间角补偿(MSAC)的非正侧视机载雷达杂波抑制方法,该方法先通过角度-多普勒补偿(ADC)预处理以消除在谱中心处的杂波非均匀,然后采用MSAC法在多个多普勒方向使参考单元和待检测单元的杂波谱保持一致,从而进一步消除在其余方位的杂波非均匀。仿真结果表明了该方法的性能明显优于ADC法,且运算量增加不多。     

Airborne/spacebased radar STAP using a structured covariance matrix

It is shown that partial information about the airborne/spacebased (A/S) clutter covariance matrix (CCM) can be used effectively to significantly enhance the convergence performance of a block-processed space/time adaptive processor (STAP) in a clutter and jamming environment. The partial knowledge of the CCM is based upon the simplified general clutter model (GCM) which has been developed by the airborne radar community. A priori knowledge of parameters which should be readily measurable (but not necessarily accurate) by the radar platform associated with this model is assumed. The GCM generates an assumed CCM. The assumed CCM along with exact knowledge of the thermal noise covariance matrix is used to form a maximum likelihood estimate (MLE) of the unknown interference covariance matrix which is used by the STAP. The new algorithm that employs the a priori clutter and thermal noise covariance information is evaluated using two clutter models: 1) a mismatched GCM, and 2) the high-fidelity Research Laboratory STAP clutter model. For both clutter models, the new algorithm performed significantly better (i.e., converged faster) than the sample matrix inversion (SMI) and fast maximum likelihood (FML) STAP algorithms, the latter of which uses only information about the thermal noise covariance matrix.     

Multiple moving target feature extraction for airborne HRR radar

This study considers the clutter suppression and feature extraction of multiple moving targets for airborne high range resolution (HRR) phased array radar. To avoid the range migration problems that occur in the HRR radar data, we divide each HRR profile into nonoverlapping low range resolution segments. No information is lost due to the division and hence no loss of resolution occurs. We show how to use a vector auto-regressive filtering technique to suppress the clutter. Then a relaxation-based parameter estimation algorithm is presented for multiple moving target feature extraction. Numerical results are given to demonstrate the effectiveness of the algorithm     

STAP for clutter suppression with sum and difference beams

A unique approach for airborne radar clutter rejection is developed and evaluated. This spatial and temporal adaptive approach employs the sum and difference beams of an antenna, which has significant practical advantages because it can be implemented with no/little change to the front-end electronics of airborne systems where sum and difference beams already exist for other reasons. The low sidelobe implementation of many sum and difference beam systems and the low gain of the difference beam in the direction of the target gives this approach the potential in many radars for a more predictable response pattern. The impact of these factors is shown in an airborne clutter rejection demonstration where the performance of this approach is compared with that of the factored approach (FA) using additional spatial channels and that of conventional pulse-Doppler (PD) processing. Reliable detection of an injected target is only achieved by this approach     

Analysis of array errors and a short-time processor in airbornephased array radars

Array errors are inherent in a realistic phased array radar system. The influence of array errors on the clutter degrees of freedom and the clutter subspace in an airborne phased array radar is analyzed. Based on the presented theoretic results, a method of short-time processing followed by coherent integration is proposed for clutter suppression in airborne phased array radars. It can approximate the two-dimensional optimal processor well even in the presence of array errors, clutter fluctuations and aircraft drift, with a considerable saving in computations