基于稀疏重建的MIMO-OTH雷达多模杂波抑制算法

针对由多模传播引起的多普勒扩展杂波(SDC)严重影响天波超视距雷达(OTHR)对慢速船舰目标的检测这一问题,在基于多输入多输出体制的新一代天波超视距(MIMO-OTH)雷达系统下,利用空域信息抑制多模SDC。传统处理方法需要目标角度先验信息,而在实际中,该信息往往很难获得。为此,提出一种新的基于稀疏重建的多模杂波抑制算法。该算法将二维的稀疏角度搜索转变为一维的角度搜索,使运算量大大降低,且估计出的收发角(DOA-DOD)自动配对,同时可获得各个传播路径下信号的时间多普勒信息,达到了理想的MIMO-OTH雷达多模杂波抑制效果。仿真结果证明了所提算法的有效性。     

Stochastic-constraints method in nonstationary hot-cluttercancellation. II. Unsupervised training applications

For pt. I see ibid., vol. 34, pp. 1271-1292 (1998). This paper considers the use of “stochastically constrained” spatial and spatio-temporal adaptive processing in multimode nonstationary interference (“hot clutter”) mitigation for scenarios that do not allow access to a group of range cells that are free from the backscattered sea/terrain signal (“cold clutter”). Since supervised training methods for interference covariance matrix estimation using the cold-clutter-free ranges are inappropriate in this case, we introduce and analyze adaptive routines which can operate on range cells containing a mixture of hot and cold clutter and possible targets (unsupervised training samples). Theoretical and simulation results are complemented by surface-wave over-the-horizon data processing, recently collected during experimental trials in northern Australia     

Spatial adaptive subspace detection in OTH radar

The work presented here addresses the problem of target detection against spatially structured interference composed of jamming plus noise, where for practical reasons, the received target wavefront may also deviate from the traditional plane wave model. This detection problem arises in over-the-horizon (OTH) radar systems where spatially distributed targets often compete for detection against directional interference that is spread over the entire range-Doppler search space. Conventional detection processing schemes are compared with a recently proposed adaptive subspace detector (ASD) that takes both the spatial structure of the interference and the possibility of target wavefront distortions into account. Experimental array data recorded by the Jindalee sky-wave and Iluka surface-wave OTH radar systems, located in central and northern Australia respectively, is used to evaluate detection performance.     

基于OTHR与纯角度传感器群数据关联的模式辨识与定位精度提升

 天波超视距雷达(OTHR)目标跟踪面临着"三低"(低检测概率、低数据率和低测量精度)和"多径"(多条传播路径)的挑战,因此传播模式的准确辨识与目标定位精度提升是改善跟踪能力的关键。首先利用纯角度传感器群获得目标地理位置的初步估计,然后采用极大似然估计建立了OTHR的传播模式和杂波模式的辨识规则,进而利用最小方差估计准则实现OTHR和纯角度传感器群的量测融合。仿真结果表明,此算法的模式辨识正确率很高,能明显提升方位角的测量精度,但是不能明显提升径向距的精度。     

Robust altitude estimation for over-the-horizon radar using a state-space multipath fading model

In previous work, a matched-field estimate of aircraft altitude from multiple over-the-horizon (OTH) radar dwells was presented. This approach exploits the altitude dependence of direct and surface reflected returns off the aircraft and the relative phase changes of these micro-multipath arrivals across radar dwells. Since this previous approach assumed high dwell-to-dwell predictability, it has been found to be sensitive to mismatch between modeled versus observed micro-multipath phase and amplitude changes from dwell-to-dwell. A generalized matched-field altitude estimate is presented here based on a state-space model that accounts for random ionospheric and target-motion effects that degrade the dwell-to-dwell predictability of target returns. The new formulation results in an efficient, robust recursive maximum likelihood (ML) estimation of aircraft altitude. Simulations suggest that the proposed technique can achieve accuracy within 5,000 ft of the true aircraft altitude, even with relatively high levels of uncertainty in modeling of dwell-to-dwell changes in the target return. A real data result is also presented to illustrate the technique.     

Target detection and tracking with HF radar using reciprocal SARtechniques

Sustained research and development at Memorial University of Newfoundland has led to an operational High Frequency Ground Wave Radar (HF-GWR) system for coastal surveillance. This radar system has demonstrated over-the-horizon detection of targets such as vessels, ice hazards and low-flying aircraft, and performed ocean parameter measurements over a large area. The industrial developers of offshore hydrocarbon reserves in ice infested regions have an urgent requirement for the long range detection and tracking of icebergs from their production platforms. However, due to space restrictions, a rig- or ship-based system can only accommodate a compact antenna array. The uniform trajectory and low velocity of icebergs is ideal for Reciprocal Synthetic Aperture Radar (RSAR) processing with long target dwell times. The proven ice detection capability of HF-GWR systems, coupled with the compact antennas suggested by the RSAR technique, can be used to develop a rig- or ship-based all-weather surveillance device for ice hazards. It is also anticipated that the results of this research will allow the use of shorter antenna arrays for many other applications. Preliminary results using real data from the operational HF-GWR system are presented     

基于兰彻斯特方程的战斗机超视距空战隐身效能分析

随着军事科技的进步,超视距空战逐步成为了现代与未来空战的主要战斗方式.而隐身技术作为提高战斗机空战能力的主要手段之一,正被各国所关注.本文通过分析基于影响图的兰彻斯特微分方程,对战斗机在超视距空战中的隐身效能进行了分析.最后给出算例,计算了不同RCS下的战斗机超视距空战交换比,从而分析了战斗机RCS对战场走势的影响.     

Optimum Estimation of Bit Synchronization

In digital communication systems, optimum estimation and detection algorithms require that precise knowledge of the bit transition time be known to the receiver before bit-by-bit detection can be made. This paper presents the derivation of Bayes or maximum a posteriori estimation algorithms for optimum estimation of bit timing. Performance of the optimum system is evaluated and suboptimal realizations suggested.     

Robust adaptive beamforming for HF surface wave over-the-horizon radar

Adaptive beamforming is used to enhance the detection of target echoes received by high frequency (HF) surface wave (HFSW) over-the-horizon (OTH) radars in the presence of spatially structured interference. External interference from natural and man-made sources typically masks the entire range-Doppler search space and is characterized by a spatial covariance matrix that is time-varying or nonstationary over the coherent processing interval (CPI). Adaptive beamformers that update the spatial filtering weight vector within the CPI are likely to suppress such interference most effectively, but the intra-CPI antenna pattern fluctuations result in temporal decorrelation of the clutter which severely degrades subclutter visibility after Doppler processing. A robust adaptive beamformer that effectively suppresses spatially nonstationary interference without degrading subclutter visibility is proposed here. The proposed algorithm is computationally efficient and suitable for practical implementation. Its operational performance is evaluated using experimental data recorded by the Iluka HFSW OTH radar, located near Darwin in far north Australia.     

A multipath data association tracker for over-the-horizon radar

A new algorithm, multipath probabilistic data association (MPDA), for initiation and tracking in over-the-horizon radar (OTHR) is described. MPDA is capable of exploiting multipath target signatures arising from discrete propagation modes that are resolvable by the radar. Nonlinear measurement models exhibiting multipath target signatures in azimuth, slant range, and Doppler are used. Tracking is performed in ground coordinates and therefore depends on the provision of estimates of virtual ionospheric heights to achieve coordinate registration. Although the propagation mode characteristics are assumed to be known, their correspondence with the detections is not required to be known. A target existence model is included for automatic track maintenance. Numerical simulations for four resolvable propagation modes are presented that demonstrate the ability of the technique to initiate and maintain track at probabilities of detection of 0.4 per mode in clutter densities for which conventional probabilistic data association (PDA) has a high probability of track loss, and suffers from track bias. A nearest neighbor version of MPDA is also presented     

Detection and range/Doppler estimation for colocated sensors

The problem of multisensor detection and high resolution signal state estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques is addressed. The model-based fusion approach offers the potential for increased target resolution in range/Doppler/azimuth space. The approach employs joint detection/estimation filters (JDEF) for target detection and localization. The JDEF approach segments the aggregate nonlinear model over the entire target resolution space into a number of localized nonlinear models by partitioning the resolution space into a number of resolution subcells. This partitioning leads to extremely accurate state estimation. The proposed JDEF approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, decentralized, and distributed data fusion.     

Model-based robust estimation and fault detection for MEMS-INS/GPS integrated navigation systems

In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation（RE） and fault detection（FD）. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.     

航空发动机在线综合诊断结构设计及仿真验证

随着机载航空电子设备的快速发展,使得传统地面系统承担的发动机诊断任务可以在线实现。实时数据的使用,可以在线监测发动机性能退化,减少故障检测和隔离的潜伏期,增加间歇性故障的检测率。为此,提出并设计了一种用于航空发动机气路故障检测和隔离、健康监测及参数估计的在线综合诊断结构。基于xPC Target 原理搭建了硬件实时仿真平台,对该结构进行了仿真验证。仿真结果表明,该结构中的机载自适应模型对发动机健康参数、可测参数和不可测参数的估计误差在0.5%以内;气路故障诊断系统采用实时数据,可以更早地检测和隔离包含间歇性故障在内的各种气路故障。     

基于支持向量机和卡尔曼滤波器的航空发动机故障诊断研究

针对航空发动机上可用传感器测量参数偏少情况下的健康参数估计问题,提出1种先分类后估计的方法。将传感器测量参数输入异常监测模块,对发动机工作状态进行监测,若监测结果为无故障则直接给出无部件故障的诊断结论;否则将测量参数输入最小二乘支持向量机(LSSVM),对部件故障进行分类,卡尔曼滤波器根据分类结果只对故障部件的健康参数进行估计。仿真结果表明:该方法可以减少需要估计的健康参数,提高估计精度。     

Generalized input-estimation technique for tracking maneuveringtargets

A new input estimation technique for target tracking problem is proposed. Conventional input estimation techniques assume that the target maneuver level is constant within the detection window, which has been the major drawback of the techniques. The proposed technique is developed to overcome this drawback by modeling the target maneuver as a linear combination of some basic time functions. The resulting algorithm has a generalized formulation including earlier works on input estimation. A detection performance of the proposed algorithm is analyzed by investigating the detection sensitivity according to the selection of maneuver models and other design parameters such as the detection window size, measurement noise level, and sampling step size. A computer simulation study shows that the estimation performance of the proposed algorithm is comparable to Bogler's input estimation method while the computation time is greatly reduced     

基于TOPSIS的空战效能多指标评估模型

战斗机空战效能评估在武器装备研制采购、对比敌我双方作战实力等方面发挥着重要作用,传统评估 模型只能在宏观上对空战效能进行评估,无法通过对比不同战机的优劣指标来进行微观评估。借鉴双基点法 改进多指标评估模型,构建空战效能评估模型;针对超视距空战和视距内空战,分别建立不同的指标体系;根据 评估指标赋权时主观法与客观法存在的缺陷,利用最小信息熵原理综合结构熵和信息熵两种不同类型的赋权 技术,构造组合赋权法。算法验证表明:组合赋权法不仅可以反映两种视距条件下指标重要程度的不同特点, 而且改进模型能纠正传统模型的评估错误,可以对空战效能进行有效评估。     

Adaptive detection schemes in compound-Gaussian clutter

Radar detection of coherent pulse trains embedded in compound-Gaussian disturbance with partially known statistics is discussed. We first give a thorough derivation of two recently proposed adaptive detection structures. Next, we derive a different detection scheme exploiting the assumption that the clutter is wide-sense stationary. Resorting to the theory of circulant matrices, in fact, we demonstrate that the estimation of the structure of the clutter covariance matrix can be reduced to the estimation of its eigenvalues, which in turn can be (efficiently) done via fast Fourier transform codes. After a thorough performance assessment, mostly carried on via computer simulations, the results show that the newly proposed detector achieves better performance than the two previously introduced adaptive detectors. Moreover, a sensitivity analysis shows that, even though this detector does not strictly guarantee the constant false alarm rate property with respect to the clutter covariance matrix, it is robust, in the sense that its performance is only slightly affected by variations in the clutter temporal correlation     

Modeling and performance of HF/OTH radar target classificationsystems

The effects of a class of multipath propagation channels on the performance of a over-the-horizon (OTH) radar target classification system are considered. A Rician frequency-selective fading channel model is employed to characterize the effects of the multipath propagation medium and evaluate the performance of radar target classification systems. The performance of classification algorithms that employ relative amplitude, relative phase, and absolute amplitude measurements as features is investigated. Performance estimates of the various classification algorithms for interesting sets of channel parameters are obtained by means of Monte-Carlo simulations     

Waveform fusion in sonar signal processing

In active sonar systems, proper selection of the transmitted waveform is critical for target detection and parameter estimation, especially with the existence of clutter (reverberation). Two commonly used waveforms (constant frequency (CF) and linear frequency modulated (LFM)) are studied. Their characteristics are complementary both with respect to their accuracies and their sensitivity to the blind zero-Doppler ridge. Several fusion schemes of the two kinds of waveforms are explored and fusion results are studied both analytically and from simulation. It is concluded that fusion of the information of different waveforms can be not only more robust, but in some cases outright preferable, in term of detection probability and estimation accuracy.     

基于自联想神经网络的发动机控制系统传感器故障诊断与重构

研究自联想神经网络及其在发动机控制系统传感器故障诊断及重构中的应用。自联想神经网络关键在于特征提取和噪声滤波。综合自联想网络的最优估计与故障诊断 ,自动区分估计误差和传感器故障。仿真结果表明这种方法不需要模型 ,能诊断传感器硬、软故障 ,当发动机性能蜕化时也能提供很好的解析余度。