MIMO雷达射频隐身性能优化的目标跟踪算法

随着现代战场中电子对抗的日益激烈,雷达的生存环境受到了严重的威胁。射频（RF）隐身技术是一种提高雷达及其运载平台战场生存能力的重要途径。为提高雷达射频隐身性能,针对具有MIMO探测模式的新体制雷达提出了隐身性能优化的目标跟踪算法。该算法基于射频隐身性能优化模型,通过自适应控制系统的子阵划分个数、平均发射功率、波束驻留时间以及采样周期,在满足系统跟踪性能要求的前提下优化系统射频隐身性能,其中的射频隐身性能综合考虑了截获因子及采样周期。仿真结果表明,与传统相控阵雷达相比,本文所提出的目标跟踪算法使MIMO雷达具有更好的射频隐身性能。     

Evaluation of multiple radar target trackers in stressfulenvironments

This paper evaluates the performance of multiple target tracking (MTT) algorithms in real-life stressful radar tracking environments. Real closely spaced maneuver radar data, generated by six F-18 fighters and other targets, were collected jointly by the defence departments of Canada and United States to support this practical MTT algorithm evaluation study. A set of performance metrics was defined here to compare the suboptimal nearest neighbor (SNN), global nearest neighbor (GNN), and various variants of the joint probabilistic data association (JPDA) MTT trackers. Results reveal an interesting result that all these MTT algorithms exhibited very close performance. In addition, the weighted sum approach of the PDA/JPDA trackers which are theoretically effective were observed to perform poorly in tracking closely spaced targets. Overall speaking, the GNN filter based on the Munkres algorithm had the best performance in terms of both tracking performance and robustness     

An Algorithm for Tracking a Maneuvering Target in Clutter

We consider the problem of tracking a maneuvering target in clutter. In such an environment, missed detections and false alarms make it impossible to decide, with certainty, the origin of received echoes. Processing radar returns in cluttered environments consists of three functions: 1) target detection and plot formation, 2) plot-to-track association, and 3) track updating. Two inadequacies of the present approaches are 1) Optimization of detection characteristics have not been considered and 2) features that can be used in the plot-to-track correlation process are restricted to a specific class. This paper presents a new approach to overcome these limitations. This approach facilitates tracking of a maneuvering target in clutter and improves tracking performance for weak targets.     

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.     

应用卡尔曼滤波的机载雷达跟踪系统

本文论述将滤波理论应用于机载雷达中对单个目标进行距离、速度、方位角和高低角跟踪的多环反馈系统。首先根据目标和天线的相对运动建立控制四坐标跟踪环所需的状态矢量微分方程,然后推导相应的非线性滤波算法。最后给出计算机的模拟结果。计算机模拟的结果清晰地说明采用最佳滤波的系统性能比通常的有很大改善,并且这种瞄准轴坐标系的最佳系统对目标的随机机动是不灵敏的。 本文所讨论的方法和得出的结论可以延用到地面雷达、舰载雷达以及其他有源和无源的跟踪系统。     

基于SAS算法的起飞一发失效应急路径规划方法

为解决起飞一发失效应急程序（EOSID）手动设计的不足,提出一种基于SRTM数据的稀疏A*搜索（SAS）算法的EOSID路径规划方法。首先采用航天飞机雷达地形测绘使命（SRTM）的网格地形数据,结合起飞一发失效相关规章,考虑爬升梯度与保护区限制确定可行搜索空间;然后基于可行搜索空间运用稀疏A*搜索算法搜索应急离场路径,在传统A*算法寻找扩展节点时加入起飞性能约束条件,同时利用地形高程数据进行地形和威胁回避,生成一条三维应急离场航迹;最后利用三次样条曲线对规划的应急离场航迹进行平滑处理。实验结果表明该方法能自动搜索出有效的EOSID三维航迹。     

Robust space-time adaptive processing for airborne radar in nonhomogeneous clutter environments

Space-time adaptive processing (STAP) holds tremendous potential for the new generation airborne surveillance radar, in which the phased array antennas and pulse Doppler processing mode are adopted. A new STAP approach using the multiple-beam and multiple Doppler channels is presented here for airborne phased array radar. The approach with space-time multiple-beam (STMB) architecture is robust to array errors and has very low system degrees of freedom (DOFs). Hence, it has low sample support requirement and it is very suitable for the practical planar phased array radar under nonhomogeneous clutter environments. Meanwhile, a new nonhomogeneous detector (NHD) based on the correlation dimension (CD) is also proposed here, which is used as an effective method to screen tracing data prior to detection processing. It can further improve the performance of the STAP approach in the severely nonhomogeneous clutter environments. Therefore, a scheme that incorporates the correlation dimension nonhomogeneity detector (CD-NHD) with the STMB is recommended, which we term CD-NHD-STMB. The experimental simulation results indicate that: 1) the STMB processor is robust to array element error and has high performance under nonhomogeneous clutter environments; 2) the CD-NHD is also effective on the nonhomogeneous clutter. As a result, the CD-NHD-STMB scheme is robust to array element error and nonhomogeneous clutter, and therefore available for airborne phased array radar applications.     

Effectiveness of MMW aerosols in defeating a battlefieldsurveillance radar: field demonstration preliminary results

The US Army ERDEC is developing advanced aerosol systems to combat threat surveillance, fire control, and seeker systems operating in the visible, infrared, and millimeter wave portions of the electromagnetic spectrum. One such system is the M56 multispectral smoke generator, which presently operates in the visible and infrared portions of the spectrum; a millimeter wave (MMW) Module is in development to extend the M56 spectral range. This paper documents preliminary results of a field demonstration test of the M56 MMW Module. An MMW instrumentation radar was modified to simulate the scan pattern and radar parameters of a tactical battlefield surveillance radar system. A test grid was populated with both stationary and moving tactical targets, and the radar scanned the grid to simulate a surveillance radar in operation. Once a realistic tactical engagement scenario was developed, MMW aerosols were deployed to demonstrate the impact such aerosols could have on radar detection and classification performance     

Multiple model particle flter track-before-detect for range ambiguous radar

The middle pulse repetition frequency（MPRF）and high pulse repetition frequency（HPRF）modes are widely adopted in airborne pulse Doppler（PD）radar systems,which results in the problem that the range measurement of targets is ambiguous.The existing data processing based range ambiguity resolving methods work well on the condition that the signal-to-noise ratio（SNR）is high enough.In this paper,a multiple model particle flter（MMPF）based track-beforedetect（TBD）method is proposed to address the problem of target detection and tracking with range ambiguous radar in low-SNR environment.By introducing a discrete variable that denotes whether a target is present or not and the discrete pulse interval number（PIN）as components of the target state vector,and modeling the incremental variable of the PIN as a three-state Markov chain,the proposed algorithm converts the problem of range ambiguity resolving into a hybrid state fltering problem.At last,the hybrid fltering problem is implemented by a MMPF-based TBD method in the Bayesian framework.Simulation results demonstrate that the proposed Bayesian approach can estimate target state as well as the PIN simultaneously,and succeeds in detecting and tracking weak targets with the range ambiguous radar.Simulation results also show that the performance of the proposed method is superior to that of the multiple hypothesis（MH）method in low-SNR environment.     

Novel radar target detection

Herein, a novel method of radar target detection based on 2-dimensional (2-D) fractal dimension is proposed. The proposed approach exploits both range information and azimuth information to estimate fractal dimension. Moreover, the approach can increase the number of data points. The above two merits result in the fractal dimension estimated by this method are more accurate and robust than the previous method. The detection performance is also better than the previous, which only makes use of 1-dimensional (1-D) information to estimate fractal dimension. Theoretical analysis and experimental results show that the proposed method performs well in a strong clutter background. The proposed method is also validated by real-life radar data, and the better result has been achieved.     

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     

Maritime border control multisensor system

This focuses on the classification task performed into a multi-sensor system for the coastal surveillance. The system is composed of two platforms of sensors: a land-based platform equipped with a land based radar, an Automatic Identification System (AIS) and an infrared camera (IR); an airborne platform carrying an airborne radar that can operate in a spotlight Synthetic Aperture Radar (SAR) mode, a video camera, and a second IR camera. The tasks performed by the system are the detection, tracking, identification, and classification of multiple targets, the evaluation of their threat level, and the selection of an intervention on them. The classification algorithm implemented inside the system exploits an analytical approach based on the confusion matrix (CM) of the imaging sensors that belong to the system. Some measures of effectiveness (MoE) of the system are evaluated, considering both cases where an ideal error-free classification process and a non-ideal classification process are performed.     

IMMPDAF for radar management and tracking benchmark with ECM

A framework is presented for controlling a phased array radar for tracking highly maneuvering targets in the presence of false alarms (FAs) and electronic countermeasures (ECMs). Algorithms are presented for track formation and maintenance; adaptive selection of target revisit interval, waveform and detection threshold; and neutralizing techniques for ECM, namely, against a standoff jammer (SOJ) and range gate pull off (RGPO). The interacting multiple model (IMM) estimator in combination with the probabilistic data association (PDA) technique is used for tracking. A constant false alarm rate (CFAR) approach is used to adaptively select the detection threshold and radar waveform, countering the effect of jammer-induced false measurements. The revisit interval is selected adaptively, based on the predicted angular innovation standard deviations. This tracker/radar-resource-allocator provides a complete solution to the benchmark problem for target tracking and radar control. Simulation results show an average sampling interval of about 2.5 s while maintaining a track loss less than the maximum allowed 4%     

Radar target novel characteristic detection method

In this paper, a method of radar target detection based on 2-dimensional (2D) fractal dimension is proposed. The proposed approach exploits both range information and azimuth information to estimate fractal dimension. Moreover, the approach can increase the number of the data points. The above two merits result in the fractal dimension estimated by this method is more accurate and robust than the previous method. The detection performance is also better than the previous one, which only makes use of 1-dimensional (1-D) information to estimate fractal dimension. Theoretical analysis and experimental result show that the proposed method performs well in strong clutter background. The proposed method is also validated by real-life radar data, and the better result has been achieved.     

Maneuvering Target Tracking Using Adaptive State Estimation

Two approaches to a nonlinear state estimation problem are presented. The particular problem addressed is that of tracking a maneuvering target in three-dimensional space using spherical observations (radar data). Both approaches rely on semi-Markov modeling of target maneuvers and result in effective algorithms that prevent the loss of track that often occurs when a target makes a sudden, radical change in its trajectory. Both techniques are compared using real and simulated radar measurements with emphasis on performance and computational burden.     

Design of a practical tracking algorithm with radar measurements

The extended Kalman filter (EKF) has been widely used as a nonlinear filtering method for radar tracking problems. However, it has been found that if cross-range measurement errors of the target position are large, the performance of the conventional EKF degrades considerably due to nonnegligible nonlinear effects. A new filtering algorithm for improving the tracking performance with radar measurements is developed based on the fact that correct evaluation of the measurement error covariance is possible in the Cartesian coordinate system. The proposed algorithm may be viewed as a modification of the EKF in which the variance of the range measurement errors is evaluated in an adaptive manner. The filter structure facilitates the incorporation of the sequential measurement processing scheme, and this makes the resulting algorithm favorable to both estimation accuracy and computational efficiency. Computer simulation results show that the proposed method offers superior performance in comparison to previous methods. Moreover, our developed algorithm provides some useful insight into the radar tracking problem     

Synthetic Vision-a view in the fog

A program called the Synthetic Vision Technology Demonstration Program, which is aimed at evaluating and demonstrating technologies permitting aircraft to land in very low visibilities over a wide range of airports, is described. The idea is to provide an electronic image of the runway to the pilot on a head-up display with an overlay on the display of symbology providing all the navigation and performance information needed to fly and land the aircraft. Millimeter-wave radar, infrared sensor, head-up display, and airborne computer processing technologies are being tested. The theoretical performance of the system concept at 35 GHz is compared to the actual performance of the 35-GHz experimental demonstration system for typical approach and runway intrusion detection conditions     

Adapitive waveform design for distributed OFDM MIMO radar system in multi-target scenario

In order to improve detection and estimation performance of distributed Orthogonal-Frequency-Division Multiplexing (OFDM) Multiple-Input Multiple-Output (MIMO) radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design (AWD) based on a constrained Multi-Objective Optimization (MOO). The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.     

Automatic Checkout and Monitoring in the AN TPQ-27 Radar System

This paper describes automatic monitoring equipment built in to a precision tracking radar system to detect and isolate faults. The purpose of the monitoring equipment is to minimize the mean time to repair faults and to exercise the overall system for pre-mission alignment and calibration. In addition, it is used to periodically check for performance degradation in key areas of the system. The paper describes the design approach used to meet the above requirements. Three types of signals are monitored: analog, digital, and switch closure. A list of each type is given and the technique used to monitor each is described. The design approach for pre-mission alignment and calibration is outlined. Tests performed are: RF alignment of the boresight axis, range tracking accuracy, angle servo calibration and accuracy, and receiver figure of merit measurements.