Multiple radar targets estimation by exploiting induced amplitude modulation

This work deals with the problem of estimating complex amplitudes, Doppler frequencies, and directions of arrival (DOA) of multiple targets present in the same range-azimuth resolution cell of a surveillance radar. The maximum likelihood (ML) and the asymptotic (large sample size) ML (AML) estimators are derived. To reduce the computational complexity of the maximization of the nonlinear two-dimensional criterion function of the AML estimator, we propose a computationally efficient algorithm based on the RELAXation method. It allows decoupling the problem of jointly estimating the parameters of the signal components into a sequence of simpler problems, where the parameters of each component are separately and iteratively estimated. The proposed method overcomes the resolution limitation of the classical monopulse technique and resolves multiple targets exhibiting an arbitrarily small difference in azimuth as long as their Doppler frequencies differ at least by the inverse of the number of integrated pulses, provided that enough signal-to-noise ratio (SNR) per pulse is available. The performance of the proposed AML-RELAX estimator is numerically investigated through Monte Carlo simulation and Cramer-Rao lower bound (CRLB) calculation.     

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。     

An improved multiple model GM-PHD filter for maneuvering target tracking

In this paper, an improved implementation of multiple model Gaussian mixture probability hypothesis density (MM-GM-PHD) filter is proposed. For maneuvering target tracking, based on joint distribution, the existing MM-GM-PHD filter is relatively complex. To simplify the filter, model conditioned distribution and model probability are used in the improved MM-GM-PHD filter. In the algorithm, every Gaussian components describing existing, birth and spawned targets are estimated by multiple model method. The final results of the Gaussian components are the fusion of multiple model estimations. The algorithm does not need to compute the joint PHD distribution and has a simpler computation procedure. Compared with single model GM-PHD, the algorithm gives more accurate estimation on the number and state of the targets. Compared with the existing MM-GM-PHD algorithm, it saves computation time by more than 30%. Moreover, it also outperforms the interacting multiple model joint probabilistic data association (IMMJPDA) filter in a relatively dense clutter environment.     

Doppler and direction-of-arrival (DDOA) radar for multiple-mover sensing

A low-cost two-element receiving array concept is investigated for detecting multiple moving targets in indoor surveillance applications. Conventional direction-of-arrival (DOA) detection requires the use of an antenna array with multiple elements. Here we investigate the use of only two elements in the receiver array. The concept entails resolving the Doppler frequencies of the returned signals from the moving targets, and then measuring the phase difference at each Doppler frequency component to calculate the DOA of the targets. Simulations are performed to demonstrate the concept and to asses the DOA errors for multiple movers. An experimental system is designed and constructed to test the concept. The system consists of a two-element receiver array operating at 2.4 GHz. Measurement results of human subjects in indoor environments are presented, including through-wall scenarios.     

GLRT subspace detection for range and Doppler distributed targets

A generalized likelihood ratio test (GLRT) is derived for adaptive detection of range and Doppler-distributed targets. The clutter is modeled as a spherically invariant random process (SIRP) and its texture component is range dependent (heterogeneous clutter). We suppose here that the speckle component covariance matrix is known or estimated thanks to a secondary data set. Thus, unknown parameters to be estimated are local texture values, the complex amplitudes and Doppler frequencies of all scattering centers. To do so, we use superresolution methods. The proposed detector assumes a priori knowledge on the spatial distribution of the target and has the precious property of having a constant false alarm rate (CFAR) with the assumption of a known speckle covariance matrix or by the use of frequency agility.     

A space-fed phased array for surveillance from space

A space-fed radar antenna called a venetian blind is proposed for all-weather wide-area surveillance from space. Radar requirements for tasked and untasked operation are discussed, and the process of selecting the venetian blind concept, which can support both, is described. In its untasked form (essentially a space-fed passive lens), it achieves off-axis squint angles of many beamwidths with negligible performance degradation. It is inherently insensitive to mechanical distortion and is a first step in the evolution to the more complex tasked system antenna. The antenna lens consists of easily manufactured slats with microstrip dipole radiating elements and matching networks on a dielectric substrate. Phase control is achieved with low-loss delay lines in the passive lens or active transmit/receive modules if electronic scan is desired     

Detecting the Presence of Target Multiplicity

A method is discussed for detecting the presence of multiple targets in the radar antenna beam. It is assumed that the targets are unresolvable in range, Doppler, and angle using conventional monopulse resolution techniques. The basic approach taken is a generalization of the "quadrature" method, with significantly enhanced performance in the case when multiple pulses are integrated into a single solution. Detection and false alarm probabilities are derived analytically and the receiver operating characteristics are graphed. This study was performed for application to angle processing in a frequency agile automatic tracking radar, but the underlying concept is general and has applications outside this area.     

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.     

一种盲多波束形成GNSS天线阵抗干扰算法

天线阵抗干扰是现代卫星导航接收机抗干扰的重要手段。传统的天线阵波束形成类算法能够在抑制干扰的同时提升抗干扰后输出信噪比,但是在信号捕获阶段,由于缺少先验信息的支持,该类算法无法在信号方向形成增益。因此,提出了一种盲多波束形成的天线阵抗干扰算法,通过形成多个波束覆盖天线阵上半球面,可在无先验信息的条件下对卫星信号形成增益,从而提升信号捕获阶段信噪比,使得接收机在干扰环境中具备更强的信号捕获能力。仿真结果表明:与传统的天线阵抗干扰算法相比,提出的算法能够在有效抑制干扰的同时显著提升接收机信号捕获成功率。     

FrFT-CSWSF:Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.     

复杂背景下红外弱小运动目标检测的新方法

提出了一种用于检测不同类型复杂背景下红外弱小运动目标的新方法。该方法能够根据图像信息自动选择背景预测算子;同时,针对不同类型复杂背景中目标和背景特性的差异,提出了“局部小目标可辨识度”的概念,并定义了一种有效的方法将其量化。在此基础上,采用蒙特卡罗实验方法构造了一种新的阈值函数,实现了单帧目标的检测,然后采用移动加权管道滤波提取目标的运动轨迹。实验结果表明,该方法对不同类型复杂背景的红外弱小运动目标具有很好的检测性能。     

Tracking of crossing targets with imaging sensors

The authors present an algorithm for the tracking of crossing targets using the centroid measurement and the centroid offset measurement of the distributed image formed by the targets. The measurements are obtained by a forward-looking infrared (FLIR) imaging sensor. The joint probabilistic data association merged-measurement coupled filter (JPDAMCF) is used for state estimation which performs filtering in a coupled manner for the targets with common measurements. Two filters are examined: one assuming the displacement noise white and the other one modeling it correctly as autocorrelated. The latter is shown to yield substantially better performance. The proposed algorithm demonstrates the usefulness of the JPDAMCF for tracking crossing targets in combination with the models for the centroid and offset measurements. Even though the centroid offset measurement requires more computations and a more complex model for estimation, it yields significantly better results if the filter accounts for its colored measurement noise     

空间自旋目标宽带雷达干涉三维成像方法

空间目标三维成像可为目标的特征提取、分类与识别提供重要依据。基于L型三天线干涉成像原理,提出了一种宽带雷达条件下空间自旋目标干涉三维成像方法。首先,分析了雷达发射线性调频(LFM)信号条件下,空间自旋目标在距离-慢时间平面上的成像特点,建立了基于距离-慢时间平面的空间自旋目标干涉三维成像模型;其次,针对建立的干涉三维成像模型中,不同散射点的回波在距离-慢时间平面上会相互交叠的问题,对回波曲线分离、交叉点处理以及一维距离旁瓣的影响等进行了讨论,并给出了解决方法,从而获得目标三维图像。与已有方法相比,该方法可有效克服单基雷达三维成像无法获得目标各散射点真实三维位置以及在双/多基雷达三维成像时多部雷达回波联合处理较困难的问题。最后,仿真实验结果验证了所提方法的有效性。     

A Practical PRSD System for Multiple Target Detection

A block diagram of a practical system using the sequential detection technique for radar detection of multiple targets is given. The system is designed to obtain better detection probability with a lower value of signal-to-noise ratio for a given false-alarm probability and average transmitted power. The total pulse duration is divided into a number of range elements which are tested for the presence or absence of a target before switching the antenna beam to the next position.     

协同进化方法求解多中心卫星任务规划问题

 在分析多卫星中心内部特点及中心间关系的基础上建立了多中心协同规划问题(MCCOPP)的数学模型,提出了解决该问题的多中心合作协同进化规划算法(MCCCSPA)。MCCCSPA基于分治-合作策略,根据中心数目以及观测目标集合特点将观测目标分解分配至各中心;提出等长扩展二进制染色体编码方式有效表达问题的解,便于个体的交叉、变异、合作操作;并综合多中心个体代表合作求解本中心个体适应值;其中交叉、变异、合作算子在确保可行解的前提下保证各中心子种群的多样性、加快收敛速度。仿真实验及分析结果表明:该方法能够有效解决多中心协同的卫星任务规划问题。     

Compact wideband FSS-absorber-based low-RCS reflectarray antenna

This paper presents a method to realize compact broadband low-RCS Reflect Array(RA) antenna based on a Frequency Selective Surface(FSS) absorber and a reflective metasurface.Such an FSS absorber consists of a resistance-loaded lossy layer and an FSS layer, which is utilized to reach an absorption-transmission response. The bottom reflective metasurface works as a phase array, reshaping the quasi-sphere wave from the feeding antenna into the quasi-plane wave. As a demonstration, the low-RCS RA an...     

A PDF multisensor multitarget tracker

A previously presented probability density function (pdf) multitarget tracker is extended to a more complex and difficult problem. The input data is bearing measurements from multiple sensors over time, which includes clutter (false alarms) and true measurements (from detected targets) with errors. Targets may be missed. The output is the real-time determination of the number of targets present and their geographic x,y location. The implementation is the recursive numerical computation of the discrete pdf of each target and is derived from the conceptual joint pdf of all targets     

A Gaussian Mixture PHD Filter for Jump Markov System Models

The probability hypothesis density (PHD) filter is an attractive approach to tracking an unknown and time-varying number of targets in the presence of data association uncertainty, clutter, noise, and detection uncertainty. The PHD filter admits a closed-form solution for a linear Gaussian multi-target model. However, this model is not general enough to accommodate maneuvering targets that switch between several models. In this paper, we generalize the notion of linear jump Markov systems to the multiple target case to accommodate births, deaths, and switching dynamics. We then derive a closed-form solution to the PHD recursion for the proposed linear Gaussian jump Markov multi-target model. Based on this an efficient method for tracking multiple maneuvering targets that switch between a set of linear Gaussian models is developed. An analytic implementation of the PHD filter using statistical linear regression technique is also proposed for targets that switch between a set of nonlinear models. We demonstrate through simulations that the proposed PHD filters are effective in tracking multiple maneuvering targets.     

利用分数阶Fourier域滤波的机载SAR多运动目标检测

 强度相差较大的多运动目标检测是机载合成孔径雷达 ( SAR)技术的一个重点和难点,传统的频域滤波和现代的时频分布方法都无法解决这个问题。首先分析了机载 SAR运动目标回波本质上为线性调频信号,据此提出一种基于分数阶 Fourier域滤波的运动目标检测新方法,并且应用逐次消去的思想有效地解决了强度相差较大的多目标检测问题。仿真的结果验证了算法的有效性。     

Senrad: an advanced wideband air-surveillance radar

The generic characteristics and performance of an experimental long-range air-surveillance radar, known at the Naval Research Laboratory as Senrad, is described. Its distinguishing feature is that it can operate with simultaneous transmissions over a very wide bandwidth-from 850 to 1400 MHz. The technology and type of experimental radar equipment employed are discussed and examples are given of its performance capabilities obtained by means of very wideband operation. The unusually wide bandwidth of this radar allows 1) improved detection and tracking performance because of the absence of the nulls that are common in the antenna elevation radiation-pattern of a single-frequency radar; 2) moving target indication (MTI) without loss of targets due to blind speeds and without the need for multiple PRFs (pulse repetition frequencies); 3) accurate height finding with a fan-beam radar by taking advantage of the multipath time difference as a function of target height; 4) a form of limited target recognition based on high range-resolution; and 5) a reduction of the effectiveness of electronic countermeasures that can seriously degrade more narrowband radars