一种基于特征空间的自适应天线旁瓣相消算法

把常规自适应天线旁瓣相消算法和特征空间技术相结合,提出了一种新的自适应天线旁瓣相消算法。该算法把常规自适应天线旁瓣相消算法的权矢量向由干扰特征矢量组成的干扰子空间投影,避免了由小特征值对应特征矢量组成的噪声子空间对权矢量的影响,与常规自适应天线旁瓣相消算法相比,该算法具有更好的干扰对消性能,其输出干扰对消比和波束方向图都能在很少的快拍下收敛。计算机仿真结果证实了这种算法的有效性。     

非合作无源探测中的假设检验弱目标检测方法

在非合作无源探测系统中,弱目标回波不仅会受到强直达波、强多径的干扰,还会受到强目标的掩盖干扰,因此很难对其进行有效检测。为了解决这一问题,提出了一种基于多择复合假设检验的弱目标检测方法。首先将接收信号投影到多径干扰的正交补子空间内,以消除强直达波和强多径干扰,然后将目标检测看作一个多择复合假设检验问题,建立了与之相应的基本框架模型,利用最大后验估计方法对目标时延、多普勒频移及信号幅度等参数进行估计,构造检验统计量,设置相应的门限,根据假设检验结果,逐个消除强目标干扰从而达到检测弱目标的目的。仿真结果表明,本方法可以有效抑制强直达波、强多径及强目标干扰,有效检测出弱目标,且虚警率低。     

Angular mean and variance for selected two-source radar-target combinations

Angle tracking of the desired target in the presence of interference is a common radar problem. It can occur when the desired target is competing with a jammer, clutter, or multipath. Angle statistics can vary significantly for a tracking radar depending upon the nature of this interference. The angular mean and variance are presented for three different statistical two-target types for single and multiple measurements. Previously derived values are presented for completeness in conjunction with derivations not found in the open literature. The signal-to-noise ratio is assumed to be large so that the effects of receiver noise may be neglected.     

Cancellation of specular and diffuse jammer multipath using ahybrid adaptive array

It has been demonstrated that specular or diffuse jammer multipath can be canceled to a desired level by using an adaptive array that combines bandwidth partitioning with tapped delay lines. Such hybrid systems are studied. In particular, the author studies an ideal two-element array that uses bandwidth partitioning in both the main and auxiliary channels, with an Mth-order adaptive finite impulse response filter in each subband of the auxiliary. The ability of this system to cancel specular moderately diffuse and diffuse multipath is studied. The combinations of bandwidth partitioning and filter order that can achieve a specified jammer cancellation level are discussed     

两种自适应方向图峰值副瓣控制方法比较

自适应阵列（或称自适应波束形成）目前已广泛应用到雷达、声纳和通信领域中用来抑制各种干扰（有意的干扰，杂波干扰和多用户干扰等）。在雷达应用中，为了减轻脉冲欺骗式干扰或旁瓣目标并利用单脉冲雷达来准确测量目标波达方向．要求自适应方向图具有低副瓣和稳定的主瓣形状。在实际应用中，各种失配误差将降低自适应阵列的性能．这些误差包括由于目标的波达方向不精确引起的信号指向误差，由通道失配和位置扰动引起的阵列校准误差和由小样本教引起的协方差矩阵估计误差。在此情况下，自适应波束形成的性能大大下降（干扰抑制性能变差。主瓣失真和高的副瓣）。已提出了一种基于二次约束的集成峰值副瓣控制（integrated peak sidelobe control，简称IPSC）方法。该方法可以精确地控制峰值副瓣电平并产生具有稳定的主瓣形状的自适应方向图。研究IPSC中目标信号的影响和信号消除方案以进一步提高IPSC的性能。并将IPSC方法和最新提出的基于二阶锥规划（second-order cone programming，简称SOCP）的分布式峰值副瓣控制（distfibuted peak sidelobe control，简称为DPSC）新方法在性能上进行了比较。仿真结果表明。在干扰抑制性能和方向图控制质量方面IPSC比DPSC性能优越。此外IPSC比DPSC计算高效。     

Adaptive digital beamforming for angle estimation in jamming

A radar digital beamforming (DBF) architecture and processing algorithm is described for nulling the signal from a mainlobe electronic jammer and multiple sidelobe electronic jammers while maintaining monopulse angle estimation accuracy on the target. The architecture consists of a sidelobe jamming (SLJ) cancelling adaptive array (AA) followed by a mainlobe jamming (MLJ) canceller. A mainlobe maintenance (MLM) technique or constrained adaptation during the sidelobe cancellation process is imposed so that the results of the SLJ cancellation process do not distort the subsequent mainlobe cancellation process. The SLJ signals and the MLJ signals are thus cancelled sequentially in separate processes. This technique was developed for improving radar processing in determining the angular location of a target, and specifically for improving the monopulse technique by maintaining the accuracy of the target echo monopulse ratio in the presence of electronic jamming by adaptive suppression of the jamming signals before forming the monopulse sum and difference beams     

A Multistage Processing Algorithm for Disturbance Removal and Target Detection in Passive Bistatic Radar

The paper examines the problem of cancellation of direct signal, multipath and clutter echoes in passive bistatic radar (PBR). This problem is exacerbated as the transmitted waveform is not under control of the radar designer and the sidelobes of the ambiguity function can mask targets including those displaced in either (or both) range and Doppler from the disturbance. A novel multistage approach is developed for disturbance cancellation and target detection based on projections of the received signal in a subspace orthogonal to both the disturbance and previously detected targets. The resulting algorithm is shown to be effective against typical simulated scenarios with a limited number of stages, and a version with computational savings is also introduced. Finally its effectiveness is demonstrated with the application to real data acquired with an experimental VHF PBR system.     

Clutter Suppression by Complex Weighting of Coherent Pulse Trains

Uniform coherent pulse trains offer a practical solution to the problem of designing a radar signal possessing both high range and range-rate resolution. The Doppler sensitivity provides some rejection of off-Doppler (clutter) returns in the matched filter receiver. This paper considers the use of a processor in which members of the received pulse train are selectively weighted in amplitude and phase to improve clutter suppression. The techniques described are particularly suitable for rejecting interference entering the processor through ambiguous responses (range sidelobes) of the signal. The complex weights which are derived are optimum in the sense that they produce the maximum clutter suppression for a given detection efficiency. In determining these weights, it is assumed that the distribution of clutter in range and range rate relative to targets of interest is known. Thus, clutter suppression is achieved by reducing the sidelobe levels in specified regions of the receiver response. These techniques are directly applicable to array antennas; the analogous antenna problem would be to reduce sidelobe levels in a particular sector while preserving gain. Complex weighting is most successful when the clutter is limited in both range and velocity.     

Sum-difference Reduced-dimensional Processing in SAR Image Domain and Statistical Analysis for Ground Moving Target Indication

In this article, a new reduced-dimensional adaptive processing algorithm based on joint pixels sum-difference data for clutter rejection is proposed. The sum-difference data are obtained by orthogonal projection of the joint pixels data of different synthetic aperture radar (SAR) images generated by a multi-satellite radar system. In the sense of statistical expectation, the sum-differ- ence data contain the common and different information of the SAR images. Therefore, the objective of clutter cancellation can be achieved by adaptive processing. Moreover, based on the residual image after clutter rejection, statistical analysis of constant false-alarm rate (CFAR) detection of moving targets is also presented. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm even with heterogeneous clutter and image co-registration error.     

Equivalent transformation for a partially adaptive array

A partially adaptive array is one in which elements of a phased array are controlled or adaptively weighted in groups or in which certain elements, called auxiliary elements, are made controllable. Mathematically, this type of array is formed by transforming all of the elements of an array by a nonsquare matrix such that the resulting output vector has a length less than the number of array elements. It is shown that there is an equivalent matrix transform that can effectively be utilized in analyzing the partially adaptive array's performance when a small number of external jammers are present. Processor implementation and convergence rate considerations lead to the desirability of reducing the dimensionality of the cancellation processor while maintaining good sidelobe interference protection. A meaningful measure of canceller performance is to compute the optimal output signal-to-noise ratio. This expression is a function of the jammer, direction-of-arrival vectors (DOAVs), jammer powers, the array steering vector, and internal noise. It is shown that if this expression is computed for the fully adaptive array then it is easily computed for the partially adaptive array by transforming the jammer DOAVs and the steering vector by the orthogonal projection matrix defined by the rows of the subarray transformation matrix and substituting these vectors back into the original expression for the fully adaptive array     

A new CFAR sidelobe canceler algorithm for radar

Signal or target detection is sometimes complicated by the presence of strong interference. When this interference occurs mainly in the sidelobes of the antenna pattern, a solution to this problem is realized through a sidelobe canceler (SLC) implementation. Since the false-alarm probability is a system parameter of special importance in radar, an interference-canceling technique for radar application should maintain the false-alarm probability constant over a wide range of incident interference power. With the requirements of sidelobe interference cancellation and constant false alarm rate (CFAR), a new algorithm for radar detection in the presence of sidelobe interference is developed from the generalized likelihood ratio test of Neyman-Pearson. In this development, the received interference is modeled as a nonstationary but slowly varying Gaussian random process. Cancellation of the sidelobe interference is based upon a `synchronous' estimate of the spatial covariance of the interference for the range gate being tested. This algorithm provides a fixed false-alarm rate and a fixed threshold which depend only upon the parameters of the algorithm     

Passive localization of moving emitters using out-of-planemultipath

The purpose of this work is to establish how a moving emitter, such as a jammer, can be localized by a passive receiver through the use of out-of-plane multipath signals reflected by the terrain. This is a novel localization technique that assumes no a priori knowledge of the localization of the multipath sources. The emitter parameters of range, heading, velocity, and altitude are estimated by exploiting the correlation between the direct-path signal and the delayed and Doppler modulated signals. Two basis assumptions about the scattering properties of the terrain lead to different maximum likelihood estimators (MLEs). The Cramer-Rao lower bounds (CRLB) are used to study estimator performance versus emitter velocity for each case. The proposed estimators are successfully demonstrated using field data collected at White Sands Missile Range (WSMR) during the DARPA/Navy Mountaintop program     

A model for target detection with over-the-horizon radar

The effects of including Faraday rotation and multipath on the probability of detecting low-flying, distant, fluctuating and nonfluctuating targets immersed in Rayleigh noise plus clutter are studied. The effect of ionospheric fluctuations is also considered. It is found that both multipath and Faraday rotation strongly influence the detection statistics, with the effect being greatest for linearly polarized targets and less marked for symmetric targets     

直达与非直达环境中的多目标解耦直接定位方法

针对直达（LOS）与非直达（NLOS）环境中的定位问题,提出了一种波形已知条件下的单阵地多目标直接定位（DPD）算法。该算法针对发射时间已知和未知两种情况,利用多径信号到达角度与时延关于障碍物（或反射体）、观测站与目标位置参数的数学关系,建立了三维目标位置的最大似然（ML）函数,无需估计测量参数,避免了传统两步定位方法所需的非直达径识别与数据关联。为了克服多目标定位中的高维非线性优化问题,该算法利用独立波形信息将多目标定位解耦为对各个目标单独求解。通过对目标函数有效近似,算法在发射时间已知和未知两种情况下均仅需三维网格搜索,比相应的两步定位方法具有更低的计算量。此外,基于多径定位场景,推导了发射时间已知和未知两种情况下的位置估计克拉美罗界（CRB）。仿真结果表明：算法的定位性能能够逼近相应的克拉美罗界,比传统两步定位方法和子空间直接定位算法具有更高的定位精度。     

一次相消技术在雷达成像中的应用

一次相消技术是一种经典的固定点目标对消方法。本文讨论了在ISAR成像处理过程中利用一次相消技术来剔除地杂波,分析了在成像处理中的杂波相消方法,并在最后的计算机仿真中,验证了该方法的有效性,分别比较了两种成像方式、两种地杂波分布的成像结果。     

Nonlinear clutter cancellation and detection using a memory-basedpredictor

In this paper, a nonlinear prediction (NLP) method is proposed as an alternative to the conventional linear prediction (LP) method for clutter cancellation. Because of the nonlinearity and non-Gaussianity of a clutter process, a nonlinear predictor is therefore needed to suppress clutter optimally. A memory-based predictor which uses a table look-up strategy to perform NLP is used in this work. The advantages of the memory-based approach are fast learning, algorithmic simplicity, robustness and suitability for parallel implementation. The memory-based predictor is then used as an adaptive detector for small surface target detection embedded in clutter. The effectiveness of the new method is demonstrated using real sea clutter data, and the results show improvement when compared with the conventional LP techniques     

Beam resource scheduling for a VHF-MIMO radar network in low-angle tracking

The low-angle tracking in multipath interference is a challenging problem for the Very High Frequency (VHF) radar. The colocated Multi-Input Multi-Output (MIMO) technique can remedy such a defect. In this paper, a Joint Beam-Target Assignment and Power Allocation (JBTAPA) strategy is proposed for the VHF-MIMO radar network tracking low-angle targets. The core of the JBTAPA strategy is to improve the worst tracking accuracy among multiple targets by assigning appropriate beams to targets and allocating the power resource in each beam using the feedback information in the tracking cycle. Taking into account the transmit multipath and receive multipath, we derive the Cramér-Rao Lower Bound (CRLB) on angle estimate, which is then incorporated in the Predicted Conditional CRLB (PC-CRLB). A more accurate and consistent lower bound is provided as the optimization metric since the PC-CRLB is based on the most recently realized measurements. A two-stage-based technique is proposed to solve the JBTAPA problem, which is originally NP-hard. Simulation results verify the effectiveness and efficiency of the proposed method. The results also imply that the target reflectivity plays one of the important roles in resource allocation.     

A multiobjective optimization approach to determine the parameters of stepped frequency pulse train

Frequency stepping techniques are commonly used in modern radar system to get high range resolution with the disadvantage that its autocorrelation function (ACF) yield undesirable “grating lobes”. Wider mainlobe deteriorates the range resolution capability of the waveform and higher peak sidelobe either hides the small targets or causes the false target detection. Several techniques have been used to choose the parameters of linear frequency modulated (LFM) pulse train to suppress the grating lobes without paying much attention to the mainlobe width and peak sidelobe level. In this paper a multiobjective optimization (Nondominated Sorting Genetic Algorithm-II (NSGA-II)) approach is proposed to optimize the parameters of the LFM pulse train to achieve reduced grating lobes, low peak sidelobe level and narrow mainlobe width. The optimization problem has been studied in two different ways: first one is associated with the reduction of grating lobes and the minimization of peak sidelobe level of the ACF with constraints and second one is related to the minimization of the peak sidelobe level and mainlobe width of the ACF with constraints. Simulation studies have been carried out to justify the potentiality of the proposed approach.     

Stochastic-constraints method in nonstationary hot-cluttercancellation. I. Fundamentals and supervised training applications

This paper considers the use of spatio-temporal adaptive array processing in over-the-horizon radar (OTHR) and airborne radar applications in order to remove nonstationary multipath interference, known as “hot clutter”. Since the spatio-temporal properties of hot clutter cannot be assumed constant over the coherent processing interval (CPI), conventional adaptive techniques fail to provide effective hot-clutter mitigation without simultaneously degrading the properties of the backscattered radar signals, known as “cold clutter”. The approach presented incorporates multiple “stochastic” (data-dependent) constraints to achieve effective hot-clutter suppression, while maintaining distortionless output cold-clutter post-processing stationarity     

密集杂波环境下的数据关联快速算法

基于联合概率数据互联（JPDA）的思想,提出了一种新的数据关联快速算法（Fast Al-gorithm for Data Association,简称FAFDA算法）.该方法不需象在最优JPDA算法中那样生成所有可能的联合互联假设,因而具有计算量小,易于工程实现的特点。仿真结果表明,与最优JPDA算法相比,FAFDA算法的跟踪性能令人满意,并且在密集杂波环境下可实时、有效地跟踪100批次以上的目标。